crowdsourcing

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pages: 368 words: 96,825

Bold: How to Go Big, Create Wealth and Impact the World by Peter H. Diamandis, Steven Kotler

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3D printing, additive manufacturing, Airbnb, Amazon Mechanical Turk, Amazon Web Services, augmented reality, autonomous vehicles, cloud computing, crowdsourcing, Daniel Kahneman / Amos Tversky, dematerialisation, deskilling, Elon Musk, en.wikipedia.org, Exxon Valdez, fear of failure, Firefox, Galaxy Zoo, Google Glasses, Google Hangouts, Google X / Alphabet X, gravity well, industrial robot, Internet of things, Jeff Bezos, John Harrison: Longitude, Jono Bacon, Just-in-time delivery, Kickstarter, Kodak vs Instagram, Law of Accelerating Returns, Lean Startup, life extension, loss aversion, Louis Pasteur, Mahatma Gandhi, Mark Zuckerberg, Mars Rover, meta analysis, meta-analysis, microbiome, minimum viable product, move fast and break things, Narrative Science, Netflix Prize, Network effects, Oculus Rift, optical character recognition, packet switching, PageRank, pattern recognition, performance metric, Peter H. Diamandis: Planetary Resources, Peter Thiel, pre–internet, Ray Kurzweil, recommendation engine, Richard Feynman, Richard Feynman, ride hailing / ride sharing, risk tolerance, rolodex, self-driving car, sentiment analysis, shareholder value, Silicon Valley, Silicon Valley startup, skunkworks, Skype, smart grid, stem cell, Stephen Hawking, Steve Jobs, Steven Levy, Stewart Brand, technoutopianism, telepresence, telepresence robot, Turing test, urban renewal, web application, X Prize, Y Combinator

So, while the point of the Freelancer and the Tongal case studies were to explore two different crowdsourcing platforms that offer today’s entrepreneur astounding leverage, the point of reCAPTCHA and Duolingo is the inverse—an example of the kind of crowdsourcing platform a bold entrepreneur might be interested in creating, the kind that both makes money and betters the world at the same time. How to Crowdsource As you can see from our case studies, crowdsourcing is a diverse and growing field, with more novel applications being dreamed up every day. So, before we dive into lessons learned, to give you a better sense of what’s going on, I’ve broken this section into four of the most common uses for crowdsourcing and provided a short explanation for each. 1. Crowdsourcing Tasks Tasks are work. Crowdsourcing tasks means getting someone somewhere to do the work for you.

Known as one of the most influential and credible authorities in the crowdsourcing space, they are recognized for their in-depth industry analyses, definitive crowdsourcing platform directory, and unbiased thought leadership. Their mission is to serve as a complete resource of information for analysts, researchers, journalists, investors, business owners, crowdsourcing experts, and participants in crowdsourcing platforms. Crowdsortium: Using the crowd to dissect, organize, and collectively move the young and evolving crowdsourcing industry forward, Crowdsortium helps organizations find, evaluate, and execute new ideas by working with online crowds and providing events, meet-ups, resources, and guides. Crowdsortium was formed by a group of industry practitioners that have the mission of advancing the industry through best practices, education, data collection, and public dialogue. 4.

If you don’t have a perfectly formatted and ready-to-go .csv file, you can turn to the crowd for help. Most of the time crowdsourcing workers have actually crowdsourced projects themselves, so they know all the best ways to prepare your data for this process. vi. QUALIFY YOUR WORKERS Unfortunately, crowdsourcing does have the potential to create undesired results. The quality of the results can sometimes be inadequate, and crowdsourcing is not sheltered from the scammers and bots lurking on the Internet. Luckily, qualifying your workers and curating a trustworthy work force can help you avoid these issues. To qualify a work force, simply put out a few very simple and inexpensive requests to see how quickly and accurately the job gets done. For example, if you have one hundred images you need created, and a dozen crowdsourced workers to choose from, rather than choosing a single graphic artist immediately, consider taking a few of your images and asking a few freelancers to show you their style and speed.


pages: 502 words: 107,657

Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die by Eric Siegel

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Albert Einstein, algorithmic trading, Amazon Mechanical Turk, Apple's 1984 Super Bowl advert, backtesting, Black Swan, book scanning, bounce rate, business intelligence, business process, call centre, computer age, conceptual framework, correlation does not imply causation, crowdsourcing, dark matter, data is the new oil, en.wikipedia.org, Erik Brynjolfsson, experimental subject, Google Glasses, happiness index / gross national happiness, job satisfaction, Johann Wolfgang von Goethe, Machine translation of "The spirit is willing, but the flesh is weak." to Russian and back, Moneyball by Michael Lewis explains big data, Nate Silver, natural language processing, Netflix Prize, Network effects, Norbert Wiener, personalized medicine, placebo effect, prediction markets, Ray Kurzweil, recommendation engine, risk-adjusted returns, Ronald Coase, Search for Extraterrestrial Intelligence, self-driving car, sentiment analysis, software as a service, speech recognition, statistical model, Steven Levy, text mining, the scientific method, The Signal and the Noise by Nate Silver, The Wisdom of Crowds, Turing test, Watson beat the top human players on Jeopardy!, X Prize, Yogi Berra

PA competitions do for data science what the X Prize did for rocket science. Mindsourced: Wealth in Diversity [Crowdsourcing is] a perfect meritocracy, where age, gender, race, education, and job history no longer matter; the quality of the work is all that counts. —Jeff Howe, Crowdsourcing: Why the Power of the Crowd Is Driving the Future of Business When pursuing a grand challenge, from where will key discoveries appear? If we assume for the moment that one cannot know, there’s only one place to look: everywhere. Contests tap the greatest resource, the general public. A common way to enact crowdsourcing, an open competition brings together scientists from far and wide to compete for the win and cooperate for the joy. With crowdsourcing, a company outsources to the world. The $1 million Netflix Prize attracted a white-hot spotlight and built a new appreciation for the influence crowdsourcing has to rally an international wealth of bright minds.

As he explains it, aspects of his work mapping the edges of glaciers from satellite photos could extend to mapping galaxies as well. Crowdsourcing Gone Wild Given the right set of conditions, the crowd will almost always outperform any number of employees. —Jeff Howe, Crowdsourcing: Why the Power of the Crowd Is Driving the Future of Business The organizations I’ve worked with have mostly viewed the competition in business as a race that benefits from sharing, rather than a fight, where one’s gain can come only from another’s loss. The openness of crowdsourcing aligns with this philosophy. —Stein Kretsinger, Founding Executive of Advertising.com One small groundbreaking firm, Kaggle, has taken charge and leads the production of PA crowdsourcing. Kaggle has launched 53 PA competitions, including the essay-grading and dark matter ones mentioned above.

Mehul Patel, Kaggle, and Giles Pavey, “Predicting Retail Customer Behaviour,” Predictive Analytics World London Conference, December 1, 2011, London, UK. www.predictiveanalyticsworld.com/london/2011/agenda.php#day1–16a. Crowdsourcing in general, beyond analytics projects: Jeff Howe, Crowdsourcing: Why the Power of the Crowd Is Driving the Future of Business (Three Rivers Press, 2008). Quote from Anthony Goldbloom about Kaggle’s crowdsourcing: Tanya Ha, “Lucrative Algorithms,” Catalyst Online, August 18, 2011. www.abc.net.au/catalyst/stories/3296837.htm. Regarding the shortage of analytics experts: James Manyika, Michael Chui, Brad Brown, Jacques Bughin, Richard Dobbs, Charles Roxburgh, and Angela Hung Byers, “Big Data: The Next Frontier for Innovation, Competition, and Productivity,” McKinsey Global Institute, May 2011. www.mckinsey.com/Insights/MGI/Research/Technology_and_Innovation/Big_data_The_next_frontier_for_innovation. More on Kaggle and crowdsourcing predictive analytics: Kaggle, “About Us: Our Team,” www.kaggle.com/about.


pages: 369 words: 80,355

Too Big to Know: Rethinking Knowledge Now That the Facts Aren't the Facts, Experts Are Everywhere, and the Smartest Person in the Room Is the Room by David Weinberger

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airport security, Alfred Russel Wallace, Amazon Mechanical Turk, Berlin Wall, Black Swan, book scanning, Cass Sunstein, corporate social responsibility, crowdsourcing, Danny Hillis, David Brooks, Debian, double entry bookkeeping, double helix, en.wikipedia.org, Exxon Valdez, Fall of the Berlin Wall, future of journalism, Galaxy Zoo, Hacker Ethic, Haight Ashbury, hive mind, Howard Rheingold, invention of the telegraph, jimmy wales, John Harrison: Longitude, Kevin Kelly, linked data, Netflix Prize, New Journalism, Nicholas Carr, Norbert Wiener, openstreetmap, P = NP, Pluto: dwarf planet, profit motive, Ralph Waldo Emerson, RAND corporation, Ray Kurzweil, Republic of Letters, RFID, Richard Feynman, Richard Feynman, Ronald Reagan, semantic web, slashdot, social graph, Steven Pinker, Stewart Brand, technological singularity, Ted Nelson, the scientific method, The Wisdom of Crowds, Thomas Kuhn: the structure of scientific revolutions, Thomas Malthus, Whole Earth Catalog, X Prize

Our traditional knowledge-based institutions are taking their first hesitant steps on land, and knowledge is beginning to show its new shape: Wide. When British media needed to pore through tens of thousands of pages of Parliamentarians’ expense reports, they “crowd-sourced” it, engaging thousands of people rather than relying on a handful of experts. It turns out that, with a big enough population engaged, sufficient width can be its own type of depth. (Note that this was not particularly good news for the Parliamentarians.) Boundary-free. Evaluating patent applications can’t be crowd-sourced because it would require expertise that crowds don’t have. So, when the US Patent Office was frustrated by how long its beleaguered staff was taking to research patent applications, it started a pilot project that enlists “citizen-experts” to find prior instances of the claimed inventions, across disciplinary and professional lines.

Its massiveness alone gives rise to new possibilities for expertise—that is, for groups of unrelated people to collectively figure something out, or to be a knowledge resource about a topic far too big for any individual expert. The simplest forms are what Jeff Howe called “crowdsourcing” in a 2006 article in Wired.13 He intended it as a play on “outsourcing,” and his examples mainly were of “plugged-in enthusiasts” who will work for much less than traditional employees. But the term was so good that it quickly escaped its creator’s tether and now applies to just about any instance in which the mass of the Net lets us do things for little or no cost that otherwise would have been prohibitively expensive. The examples of crowdsourcing are familiar at this point. When Members of Parliament were found to be routinely taking frivolous deductions, the British newspaper The Guardian set up a site where 20,000 people pored through 700,000 expense claims.

Harris, In the Shadow of Slavery: African Americans in New York City, 1626–1863 (University of Chicago Press: Chicago, 2004). An excerpt of the chapter titled “The New York City Draft Riots of 1863” can be found at http://www.press.uchicago.edu/Misc/Chicago/317749.html. 11 Howard Rheingold, Smart Mobs: The Next Social Revolution (Basic Books, 2003). 12 James Surowiecki, The Wisdom of Crowds (Random House, 2004). 13 Jeff Howe, “The Rise of Crowdsourcing,” Wired 14, no. 6 (June 2006), http://www.wired.com/wired/archive/14.06/crowds.html. See also Howe’s Crowdsourcing (Crown Business, 2008). 14 “Darpa Network Challenge: We Have a Winner,” https://network-challenge.darpa.mil/Default.aspx. 15 “How It Works” (MIT), 2009, http://balloon.mit.edu/mit/payoff/. 16 Darren Murph, “MIT-Based Team Wins DARPA’s Red Balloon Challenge, Demonstrates Power of Social Networks (and Cold Hard Cash),” December 6, 2009, http://www.engadget.com/2009/12/06/mit-based-team-wins-darpas-red-balloon-challenge-demonstrates/. 17 See Jonathan Zittrain’s “Minds for Sale” video at http://www.youtube.com/watch?

The Open Organization: Igniting Passion and Performance by Jim Whitehurst

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crowdsourcing, Google Hangouts, Network effects, Silicon Valley, Skype, Snapchat

This book reveals the secrets of how an open organization really works by taking an insider’s in-depth look into one of the premier 2 Chapter_01.indd 2 3/7/15 9:59 AM Why Opening Up Your Organization Matters open organizations in the world, Red Hat (a software company with a value of more than $10 billion where I am the CEO), along with illustrative examples of other companies operating this way too, such as Whole Foods, Pixar, Zappos, Starbucks, W. L. Gore, and others. This book will show leaders and aspiring leaders—in companies large and small, and in established companies as well as startups struggling to grow—how to develop a new, open organizational model that uniquely matches the speed and complexity that businesses must master today. From Crowdsourcing to Open Sourcing Much has been written recently about a new way of working called “crowdsourcing,” which is the power of mass participation to generate phenomenal ideas, solve complex problems, and organize broad movements. We’ve seen examples, such as Wikipedia or the Linux operating system (which played a key role in Red Hat’s start), where communities of people spontaneously self-organize around a problem or activity. Work is distributed in a network-like fashion and people are held accountable, all without a formal hierarchy.

There’s even a company called InnoCentive that firms can hire to help them use the power of the crowd. There are also competitions like the Ansari XPRIZE, which awarded $10 million to the first nongovernment organization to launch a reusable manned spacecraft into space twice within two weeks, or Kaggle, which crowdsources solutions to big data–type analytical challenges, that get a multitude of participants to deliver a bunch of ideas or solutions, where the single best of the bunch wins and receives an award. The Limitations of Crowdsourcing As effective as these “tapping the wisdom of the crowd” approaches are at providing companies with new ideas and solutions to problems, they are often limited in that they are either timebound, say, for the duration of a competition, or are narrowly focused on a single, specific goal, such as generating an idea for a new product.

So, while many companies have 4 Chapter_01.indd 4 3/7/15 9:59 AM Why Opening Up Your Organization Matters tapped the power of participation in targeted ways, few have leveraged its power more broadly within their own organizations. What if you could make this kind of engagement standard, not just one-and-done, for how work gets done in your organization, so that you’re engaging at this level every single day? Another problem with crowdsourcing is that it’s a one-way transaction. Crowdsourcing approaches typically depend on the contributions of volunteers—people who contribute to the product primarily for the reputational advantage, not necessarily for a monetary one. And, too often, it seems that companies approach these volunteers with the goal of extracting value, with what has been called a “Tom Sawyer” model of collaboration.1 As you might recall from your childhood reading, Tom was a bit of a manipulator, someone who was always trying to get out of doing chores.


pages: 677 words: 206,548

Future Crimes: Everything Is Connected, Everyone Is Vulnerable and What We Can Do About It by Marc Goodman

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23andMe, 3D printing, additive manufacturing, Affordable Care Act / Obamacare, Airbnb, airport security, Albert Einstein, algorithmic trading, artificial general intelligence, augmented reality, autonomous vehicles, Baxter: Rethink Robotics, Bill Joy: nanobots, bitcoin, Black Swan, blockchain, borderless world, Brian Krebs, business process, butterfly effect, call centre, Chelsea Manning, cloud computing, cognitive dissonance, computer vision, connected car, corporate governance, crowdsourcing, cryptocurrency, data acquisition, data is the new oil, Dean Kamen, disintermediation, don't be evil, double helix, Downton Abbey, Edward Snowden, Elon Musk, Erik Brynjolfsson, Filter Bubble, Firefox, Flash crash, future of work, game design, Google Chrome, Google Earth, Google Glasses, Gordon Gekko, high net worth, High speed trading, hive mind, Howard Rheingold, hypertext link, illegal immigration, impulse control, industrial robot, Internet of things, Jaron Lanier, Jeff Bezos, job automation, John Harrison: Longitude, Jony Ive, Julian Assange, Kevin Kelly, Khan Academy, Kickstarter, knowledge worker, Kuwabatake Sanjuro: assassination market, Law of Accelerating Returns, Lean Startup, license plate recognition, litecoin, M-Pesa, Mark Zuckerberg, Marshall McLuhan, Menlo Park, mobile money, more computing power than Apollo, move fast and break things, Nate Silver, national security letter, natural language processing, obamacare, Occupy movement, Oculus Rift, offshore financial centre, optical character recognition, pattern recognition, personalized medicine, Peter H. Diamandis: Planetary Resources, Peter Thiel, pre–internet, RAND corporation, ransomware, Ray Kurzweil, refrigerator car, RFID, ride hailing / ride sharing, Rodney Brooks, Satoshi Nakamoto, Second Machine Age, security theater, self-driving car, shareholder value, Silicon Valley, Silicon Valley startup, Skype, smart cities, smart grid, smart meter, Snapchat, social graph, software as a service, speech recognition, stealth mode startup, Stephen Hawking, Steve Jobs, Steve Wozniak, strong AI, Stuxnet, supply-chain management, technological singularity, telepresence, telepresence robot, Tesla Model S, The Wisdom of Crowds, Tim Cook: Apple, trade route, uranium enrichment, Wall-E, Watson beat the top human players on Jeopardy!, Wave and Pay, We are Anonymous. We are Legion, web application, WikiLeaks, Y Combinator, zero day

The boss’s gamification strategy paid off and received widespread attention among his workers, with the Ferrari reserved for the chosen “employee of the month.” From Crowdsourcing to Crime Sourcing Of all the business innovation techniques utilized by Crime, Inc., perhaps none has been as widely adopted as crowdsourcing. Crowdsourcing began as a legitimate tool to leverage the wisdom of crowds to solve complex business and scientific challenges. The concept of crowdsourcing first gained widespread attention in an article written in 2006 by Jeff Howe for Wired. Howe defined crowdsourcing as the act of “outsourcing a task to a large, undefined group of people through an open call.” While hundreds of examples of crowdsourcing have been documented with great results, these very same techniques can be harnessed for criminal purposes as well. YouTube is replete with great examples of apparent strangers suddenly breaking out into song, whether at Heathrow Airport or Times Square.

Open-source warfare and crowdsourced crime must be met with open-source security and crowdsourced public safety. Fortunately, there are a few bright spots where this new paradigm of public safety is beginning to shine. Organizations such as Crisis Commons and Ushahidi are reinventing disaster relief and saving lives by coordinating citizen response to public emergencies, including during the Haiti earthquake and the terrorist attack at the Westgate Mall in Nairobi. Citizens in Mexico, a country racked by fifty thousand narcotics-related murders from 2006 to 2012, are using tools such as Google Maps to crowdsource reporting on the cartels, their activities, and their whereabouts. In eastern Europe, the Organized Crime and Corruption Reporting Project, comprising journalists and citizens, crowdsources sophisticated multinational investigations to reveal which dictators, crooked officials, terrorists, and organized crime groups are moving and laundering their massive ill-gotten gains around the globe.

If any of the participants involved are arrested, they are unlikely to be able to “rat” on their co-conspirators, whom they met for the first time at the scene of the crime. Similar incidents have taken place in Chicago, Philadelphia, and Los Angeles. Some crowdsourcing techniques are meant to give potential lawbreakers a leg up on the police. In the United States, mobile apps such as DUI Dodger, Buzzed, and Checkpoint Wingman allow those who have had too much to drink to crowdsource the location of DUI checkpoints, view them on an interactive map on the iPhone or Android device, and receive alerts when checkpoints are moved or newly established. When the 2011 London riots against government spending cuts turned violent, protesters created an app called Sukey, which allowed them to photograph police and upload their geo-tagged images to a crowdsourced interactive map. When other protest participants launched Sukey on their mobiles, they knew which areas contained riot police and were shown interactive compasses advising them how to avoid the cops (green pointed to safe areas, red to police danger zones).


pages: 502 words: 107,510

Natural Language Annotation for Machine Learning by James Pustejovsky, Amber Stubbs

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Amazon Mechanical Turk, bioinformatics, cloud computing, computer vision, crowdsourcing, easy for humans, difficult for computers, finite state, game design, information retrieval, iterative process, natural language processing, pattern recognition, performance metric, sentiment analysis, social web, speech recognition, statistical model, text mining

Language Resources and Evaluation 39(2–3):165–210. References for Using Amazon’s Mechanical Turk/Crowdsourcing Aker, Ahmet, Mahmoud El-Haj, M-Dyaa Albakour, and Udo Kruschwitz. 2012. “Assessing Crowdsourcing Quality through Objective Tasks.” In Proceedings of the 8th International Conference on Language Resources and Evaluation (LREC’12), Istanbul, Turkey. Filatova, Elena. 2012. “Irony and Sarcasm: Corpus Generation and Analysis Using Crowdsourcing.” In Proceedings of the 8th International Conference on Language Resources and Evaluation (LREC’12), Istanbul, Turkey. Fort, Karën, Gilles Adda, and K. Bretonnel Cohen. 2011. “Amazon Mechanical Turk: Gold Mine or Coal Mine?” Computational Linguistics 37(2):413–420. Kittur, E.H. Chi, and B. Suh. 2008. “Crowdsourcing user studies with Mechanical Turk.” In Proceedings of CHI ’08: The 26th Annual SIGCHI Conference on Human Factors in Computing Systems.

This is why it is important to have well-defined guidelines and good IAA scores; if a task is clear, then it can be reproduced later by other groups of people. In Chapter 4 we discussed interoperability and reproducibility as it applies to data formats, but the concept applies to the annotation task as well. Crowdsourcing Crowdsourcing is another approach that is being used more frequently in the annotation community. Essentially, instead of asking a small number of annotators to tag a large number of extents, the task is broken down into a large number of smaller tasks, and a large number of annotators are asked to tag only a few examples each. One popular crowdsourcing platform is Amazon’s Mechanical Turk (MTurk), a resource where people who have tasks that require human intelligence to perform can place requests that are then fulfilled by people across the country and around the world.

In this chapter we look toward the future of annotation projects and ML algorithms, and show you some ways that the field of Natural Language Processing (NLP) is changing, as well as how those changes can help (or hurt) your own annotation and ML projects. Crowdsourcing Annotation As you have learned from working your way through the MATTER cycle, annotation is an expensive and time-consuming task. Therefore, you want to maximize the utility of your corpus to make the most of the time and energy you put into your task. One way that people have tried to ameliorate the cost of large annotation projects is to use crowdsourcing—by making the task available to a large group of (usually untrained) people, it becomes both cheaper and faster to obtain annotated data, because the annotation is no longer being done by a handful of selected annotators, but rather by large groups of people. If the concept of crowdsourcing seems strange, think about asking your friends on Facebook to recommend a restaurant, or consider what happens when a famous person uses Twitter to ask her followers for a piece of information, or their preferences for an upcoming event.


pages: 270 words: 79,992

The End of Big: How the Internet Makes David the New Goliath by Nicco Mele

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3D printing, 4chan, A Declaration of the Independence of Cyberspace, Airbnb, Amazon Web Services, Any sufficiently advanced technology is indistinguishable from magic, Apple's 1984 Super Bowl advert, barriers to entry, Berlin Wall, big-box store, bitcoin, business climate, call centre, Cass Sunstein, centralized clearinghouse, Chelsea Manning, citizen journalism, cloud computing, collaborative consumption, collaborative editing, crony capitalism, cross-subsidies, crowdsourcing, David Brooks, death of newspapers, Donald Trump, Douglas Engelbart, en.wikipedia.org, Exxon Valdez, Fall of the Berlin Wall, Filter Bubble, Firefox, Galaxy Zoo, global supply chain, Google Chrome, Gordon Gekko, Hacker Ethic, Jaron Lanier, Jeff Bezos, jimmy wales, Julian Assange, Kevin Kelly, Khan Academy, Kickstarter, Lean Startup, Mark Zuckerberg, minimum viable product, Mohammed Bouazizi, Mother of all demos, Narrative Science, new economy, Occupy movement, Peter Thiel, pirate software, Ronald Reagan, Ronald Reagan: Tear down this wall, sharing economy, Silicon Valley, Skype, social web, Steve Jobs, Steve Wozniak, Stewart Brand, Stuxnet, Ted Nelson, Telecommunications Act of 1996, telemarketer, The Wisdom of Crowds, transaction costs, uranium enrichment, Whole Earth Catalog, WikiLeaks, Zipcar

It makes me feel better; I know I’m safe because of an interconnecting web of institutions that operate to encourage the best and make sure my interests are protected. In a crowd-sourced, maker world, we’re missing some of the institutions that have helped to provide accountability and reliability. Just as the end of Big News has meant a demonstrable loss of accountability journalism, we might worry that the end of Big Companies could mean a demonstrable loss of accountability, especially in industries where technical expertise or competency is required. While I tend to sympathize with the views of Ben Kaufman of Quirky and others who believe that anything—literally anything—can be crowd-sourced, I’m not sure everything should be crowd-sourced. Would you want to fly on a small airline that uses a craft- or maker-produced airplane whose engines come from a craft- or maker-produced engine company?

In another study, “just 4 percent of consumers would be willing to stick with a brand if its competitors offered better value for the same price.24 It turns out that the more technology you use, the more likely you are to have a lot less brand loyalty.25 From Groupon to iPad shopping apps to Amazon, consumers respond overwhelmingly to price and to the recommendations of trusted peers in their social networks—not to brands. Crowdsourcing works well for designing large, complex, expensive products purchased by organizations, not just small consumer items. The U.S. military has begun designing its vehicles using crowdsourcing—with some initial promise. In four months, a team designed, built, and deployed an “experimental crowd-derived combat support vehicle” or XC2V for short. The site used to design it is called LocalMotors, which “harnesses the creativity of the world’s underemployed car designers.”26 Thousands of people on the site participate in the design of vehicles, some of which actually find their way into production.

It’s part of the “free agent” world, where radical connectivity and cloud computing allow individuals to operate outside the bounds of a normal nine-to-five job at a big company—with all the uncertainty and opportunity that comes with freelancing. How far can we take crowdsourcing? “Giffgaff” is a Scottish English word that means “mutual giving,” which is a pretty good way to describe the British mobile phone company giffgaff. Its customers are its sales team. Its customers are its technical support team. In fact, giffgaff uses customers to do as much as possible, compensating them with a virtual currency, “payback,” that can be redeemed for mobile phone minutes, cash, and other rewards. By distributing key expenses out to the “crowd”—in this case, the customers—this mobile phone network in the U.K. keeps costs down and establishes itself as a competitive choice. Open Source Takes on the Big Guys Crowdsourcing has its roots in open-source programming, which first took hold during the 1960s.


pages: 464 words: 127,283

Smart Cities: Big Data, Civic Hackers, and the Quest for a New Utopia by Anthony M. Townsend

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1960s counterculture, 4chan, A Pattern Language, Airbnb, Amazon Web Services, anti-communist, Apple II, Bay Area Rapid Transit, Burning Man, business process, call centre, carbon footprint, charter city, chief data officer, clean water, cleantech, cloud computing, computer age, congestion charging, connected car, crack epidemic, crowdsourcing, DARPA: Urban Challenge, data acquisition, Deng Xiaoping, East Village, Edward Glaeser, game design, garden city movement, Geoffrey West, Santa Fe Institute, George Gilder, ghettoisation, global supply chain, Grace Hopper, Haight Ashbury, Hedy Lamarr / George Antheil, hive mind, Howard Rheingold, interchangeable parts, Internet Archive, Internet of things, Jacquard loom, Jacquard loom, Jane Jacobs, jitney, John Snow's cholera map, Khan Academy, Kibera, knowledge worker, load shedding, M-Pesa, Mark Zuckerberg, megacity, mobile money, mutually assured destruction, new economy, New Urbanism, Norbert Wiener, Occupy movement, openstreetmap, packet switching, patent troll, place-making, planetary scale, popular electronics, RFC: Request For Comment, RFID, ride hailing / ride sharing, Robert Gordon, self-driving car, sharing economy, Silicon Valley, Skype, smart cities, Smart Cities: Big Data, Civic Hackers, and the Quest for a New Utopia, smart grid, smart meter, social graph, social software, social web, special economic zone, Steve Jobs, Steve Wozniak, Stuxnet, supply-chain management, technoutopianism, Ted Kaczynski, telepresence, The Death and Life of Great American Cities, too big to fail, trade route, Tyler Cowen: Great Stagnation, Upton Sinclair, uranium enrichment, urban decay, urban planning, urban renewal, Vannevar Bush, working poor, working-age population, X Prize, Y2K, zero day, Zipcar

But as powerful as this approach can be, we need to be cautious. While seemingly progressive, crowdsourcing can also open the door for those who would cut the legs out from under government. Where crowdsourced efforts fill gaps left behind by shrinking budgets, the appearance of an inefficient and ineffective public sector will be difficult to avoid. In cities in the developing world, where crowdsourcing offers services governments have never adequately provided, they may allow for a permanent offloading of obligations. Poor communities may not have the luxury of this level of engagement—the day-to-day realities of survival often leave few resources for volunteerism. Taken to its extreme, crowdsourcing is tantamount to the privatization of public services—the rich will provide for themselves and deny services to those outside their enclaves.

As Heeks argues, “In a globalized world, the problems of the poor today can, tomorrow—through migration, terrorism, and disease epidemics—become the problems of those at the pyramid’s top.”50 This brings us to the final dilemma: crowdsourcing and the future role of government in delivering basic services. In smart cities, there will be many new crowdsourcing tools that, like OpenStreetMap, create opportunities for people to pool efforts and resources outside of government. Will governments respond by casting off their responsibilities? In rich countries, governments facing tough spending choices may simply withdraw services as citizen-driven alternatives expand, creating huge gaps in support for the poor. In the slums of the developing world’s megacities, where those responsibilities were hardly acknowledged to begin with, crowdsourced alternatives may allow governments to free themselves from the obligation to equalize services in the future.

Taken to its extreme, crowdsourcing is tantamount to the privatization of public services—the rich will provide for themselves and deny services to those outside their enclaves. Unless we are ready to embrace anarchy and institutionalize unequal access to public services, there will be limits to what crowdsourcing can accomplish. Crowdsourcing with care means limiting its use to areas where government needs to mobilize citizens around efforts where it lacks capacity, and there is broad consensus over desired outcomes. In a sense, it is the architecture of total civic participation in urban regeneration that Patrick Geddes could only dream of. But as much as crowdsourcing can augment capacity, government needs to ensure that critical public services are delivered to everyone and on time. What happens when helping one part of a crowd hurts another, for instance in traffic avoidance? Do you reward one set of users by revealing secret but limited-capacity, clog-free routes around jams?


pages: 292 words: 85,151

Exponential Organizations: Why New Organizations Are Ten Times Better, Faster, and Cheaper Than Yours (And What to Do About It) by Salim Ismail, Yuri van Geest

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23andMe, 3D printing, Airbnb, Amazon Mechanical Turk, Amazon Web Services, augmented reality, autonomous vehicles, Baxter: Rethink Robotics, bioinformatics, bitcoin, Black Swan, blockchain, Burning Man, business intelligence, business process, call centre, chief data officer, Clayton Christensen, clean water, cloud computing, cognitive bias, collaborative consumption, collaborative economy, corporate social responsibility, cross-subsidies, crowdsourcing, cryptocurrency, dark matter, Dean Kamen, dematerialisation, discounted cash flows, distributed ledger, Edward Snowden, Elon Musk, en.wikipedia.org, ethereum blockchain, Galaxy Zoo, game design, Google Glasses, Google Hangouts, Google X / Alphabet X, gravity well, hiring and firing, Hyperloop, industrial robot, Innovator's Dilemma, Internet of things, Iridium satellite, Isaac Newton, Jeff Bezos, Kevin Kelly, Kickstarter, knowledge worker, Kodak vs Instagram, Law of Accelerating Returns, Lean Startup, life extension, loose coupling, loss aversion, Lyft, Mark Zuckerberg, market design, means of production, minimum viable product, natural language processing, Netflix Prize, Network effects, new economy, Oculus Rift, offshore financial centre, p-value, PageRank, pattern recognition, Paul Graham, Peter H. Diamandis: Planetary Resources, Peter Thiel, prediction markets, profit motive, publish or perish, Ray Kurzweil, recommendation engine, RFID, ride hailing / ride sharing, risk tolerance, Ronald Coase, Second Machine Age, self-driving car, sharing economy, Silicon Valley, skunkworks, Skype, smart contracts, Snapchat, social software, software is eating the world, speech recognition, stealth mode startup, Stephen Hawking, Steve Jobs, subscription business, supply-chain management, TaskRabbit, telepresence, telepresence robot, Tony Hsieh, transaction costs, Tyler Cowen: Great Stagnation, urban planning, WikiLeaks, winner-take-all economy, X Prize, Y Combinator

This strategy failed, largely due to legal issues about ownership and licensing costs, although another problem was that the students lacked a sense of purpose and commitment insofar as the company was concerned, which resulted in almost no contribution to the platform [Experimentation]. Undaunted, Jones and Rogers took another shot at attracting community, this time via crowdsourcing. They were successful this time around, and in March 2008, Local Motors debuted as the first community to completely crowdsource a car. (The company currently has eighty-three employees and three micro-factories for manufacturing.) The Local Motors staff then turned its attention to evangelizing, sharing its passion for the product on numerous designer sites, which acted as magnets for a like-minded community [Community & Crowd]. Next, implementing Engagement, Local Motors undertook its first competition for a car design.

Here are some of the paper’s initiatives: In 2007, the Guardian offered a free blogging platform for thought leaders and created online forums and discussion groups [Community and Crowd]. Developers offered an open API to the paper’s website so they could leverage content on the site [Algorithms]. Investigative reporting for the millions of WikiLeaks cables fully crowdsourced [Community & Crowd]. The Guardian has institutionalized the crowdsourcing of investigative reporting and has successfully used that approach on several occasions, including after obtaining public documents from Sarah Palin’s tenure as governor of Alaska. Similarly, in 2009, when the UK government bowed to public pressure and released two million pages of parliamentary expense reports, the Guardian asked its readership to find any newsworthy needles in that vast haystack of words.

We have referenced Quirky several times throughout this book and will now focus on its MTP, which is “Make Invention Accessible.” General Electric early on saw the huge potential of the new crowdsourced model of product development. It subsequently partnered with Quirky in 2012 on incentive competition [Engagement], whereby the Quirky community was tasked with dreaming up innovative everyday products. The submissions would then be put to a community vote, with the winning invention manufactured by GE. Out of a total of 1,500 submissions, the Quirky community selected the Milkmaid, a smart container that alerts users when milk begins to spoil or run low, as the top product. Each subsequent phase of the Milkmaid’s production, including product design, name, tagline and even price, was crowdsourced as well [Crowd], resulting in a total of 2,530 contributions from the Quirky community for a single product.

The Data Revolution: Big Data, Open Data, Data Infrastructures and Their Consequences by Rob Kitchin

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business intelligence, business process, cellular automata, Celtic Tiger, cloud computing, collateralized debt obligation, conceptual framework, congestion charging, corporate governance, correlation does not imply causation, crowdsourcing, discrete time, George Gilder, Google Earth, Infrastructure as a Service, Internet Archive, Internet of things, invisible hand, knowledge economy, late capitalism, linked data, Masdar, means of production, Nate Silver, natural language processing, openstreetmap, pattern recognition, platform as a service, recommendation engine, RFID, semantic web, sentiment analysis, slashdot, smart cities, Smart Cities: Big Data, Civic Hackers, and the Quest for a New Utopia, smart grid, smart meter, software as a service, statistical model, supply-chain management, the scientific method, The Signal and the Noise by Nate Silver, transaction costs

Clearly the production of such life-logs raise a number of questions concerning privacy, the ownership of the data produced, and how such data are used (Dodge and Kitchin 2007b). Crowdsourcing Crowdsourcing is the collective generation of media, ideas and data undertaken voluntarily by many people to solve a particular task. While social media content can be said to be crowdsourced in the sense that it is sourced from a large number of people, its purpose is diffuse and lacking in focus. Instead, crowdsourcing focuses on the collective production of information and on creating solutions to particular issues by drawing on the energy, knowledge, skills and consensual and collective action of a crowd of people (Howe 2008). Howe (2008) argues that there are four developments that support the growth of crowdsourcing: a renaissance of amateurism (often at professional standards), the emergence of the open source software movement, the increasing availability of the tools of production outside of firms, and the rise of vibrant online communities organised according to people’s interests.

Moreover, there are concerns about the quality and consistency of content and metadata created across diversely skilled/motivated individuals, and how to provide documented degrees of reliability and generate a sense of trustworthiness (Dodge and Kitchin 2013). This has led some to posit that ‘amateur’, crowdsourced labour is best expended on data verification and correction, not creation (Carr 2007). The example Carr highlights is Wikipedia, which although popular and extensive, has grown in a haphazard way that matches the selective interests of participants, and has incomplete, sometimes poorly written, trivial and highly contested articles which undermine its authority and usability. Carr contends that ‘if Wikipedia weren’t free, it is unlikely its readers would be so forgiving of its failings’ (2007: 4). OpenStreetMap can suffer from a lack of coverage in some areas where there are few volunteers. There are also concerns as to the sustainability of volunteered crowdsourced labour, with Carr (2007) arguing that the connections that bind a virtual crowd together are often superficial, lacking depth and obligatory commitment, are liable to dispersion, and are reliant on a small core group to keep the project going and provide the bulk of the labour.

Table 2.4 lists over thirty such reasons divided into three dimensions – direct/indirect, near-term/long-term, public/private – as defined by Beagrie et al. (2010). These translate approximately into scientific and financial gains, the cumulative effect of benefits, and who gains from such infrastructures. The scientific arguments for the storing, sharing and scaling of data within data infrastructures centre on the promises of new discoveries and innovations through the combination of datasets and the crowdsourcing of minds. Individual datasets are valuable in their own right, but when combined with other datasets or examined in new ways fresh insights can be potentially discerned and new questions answered (Borgman 2007). By combining datasets, it is contended that the cumulative nature and pace of knowledge building is accelerated (Lauriault et al. 2007). Moreover, by preserving data over time it becomes possible to track trends and patterns, and the longer the record, the greater the ability to build models and simulations and have confidence in the conclusions drawn (Lauriault et al. 2007).


pages: 742 words: 137,937

The Future of the Professions: How Technology Will Transform the Work of Human Experts by Richard Susskind, Daniel Susskind

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23andMe, 3D printing, additive manufacturing, AI winter, Albert Einstein, Amazon Mechanical Turk, Amazon Web Services, Andrew Keen, Atul Gawande, Automated Insights, autonomous vehicles, Big bang: deregulation of the City of London, big data - Walmart - Pop Tarts, Bill Joy: nanobots, business process, business process outsourcing, Cass Sunstein, Checklist Manifesto, Clapham omnibus, Clayton Christensen, clean water, cloud computing, computer age, computer vision, conceptual framework, corporate governance, crowdsourcing, Daniel Kahneman / Amos Tversky, death of newspapers, disintermediation, Douglas Hofstadter, en.wikipedia.org, Erik Brynjolfsson, Filter Bubble, Frank Levy and Richard Murnane: The New Division of Labor, full employment, future of work, Google Glasses, Google X / Alphabet X, Hacker Ethic, industrial robot, informal economy, information retrieval, interchangeable parts, Internet of things, Isaac Newton, James Hargreaves, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, Joseph Schumpeter, Khan Academy, knowledge economy, lump of labour, Marshall McLuhan, Narrative Science, natural language processing, Network effects, optical character recognition, personalized medicine, pre–internet, Ray Kurzweil, Richard Feynman, Richard Feynman, Second Machine Age, self-driving car, semantic web, Skype, social web, speech recognition, spinning jenny, strong AI, supply-chain management, telepresence, the market place, The Wealth of Nations by Adam Smith, The Wisdom of Crowds, transaction costs, Turing test, Watson beat the top human players on Jeopardy!, young professional

At PatientsLikeMe, 300,000 people connect with other people who share their conditions (at the moment, around 2,300 conditions), and swap experiences and treatments.37 It is reported that Facebook is planning to develop online ‘support communities’ in this spirit.38 One-third of doctors in the United States use the network known as Sermo to distribute research, post clinical cases, and talk amongst each other.39 The same proportion use a network known as QuantiaMD, with similar functionality.40 More than half of the doctors in the United States are members of Doximity, another doctor-specific networking tool.41 Medicine is also making use of crowdsourcing, where large numbers of individuals are drawn upon for their collective ideas and support. At CrowdMed, people post their symptoms and crowdsource diagnoses from an online community of 2,000 doctors—so-called ‘Medical Detectives’.42 At InnoCentive, medical institutions crowdsource ideas by offering large online rewards for those who solve their medical ‘challenges’.43 At Watsi, people in need of medical care, but unable to afford it themselves, can use their online crowdfunding platform to raise finance from donors.44 3-D printing techniques enable many medical objects, from casts to prosthetics to dentist’s caps and crowns, to be personalized and then printed on demand.

In Chapter 2 we observed cases where experts and lay people collaborate with each other, with the former, for example, reviewing, editing, or supplementing the user-generated content. A third type of online collaboration is crowdsourcing. Here large numbers of people—experts or non-specialists—are invited to contribute to a well-defined project or problem that is so large that it requires many hands, or is so difficult that it might benefit from the ‘wisdom of crowds’,24 or so obscure that an answer is most likely to be found if the net of inquiry is spread widely enough. WikiHouse and Arcbazar in architecture, and Open Ideo and WikiStrat in consulting, have run crowdsourcing projects in this manner. Realization of latent demand One of the attractions of the new approaches to professional work and, in particular, of various online services, is that practical expertise is steadily becoming more affordable and accessible.

Today this kind of shared online platform can be set up in minutes, using inexpensive off-the-shelf software. In this way, for example, it is easy jointly to co-author complex documents, even if the contributors are in different countries. A related form of production occurs when online humans crowdsource (as is discussed briefly in section 3.7). Ordinarily, this involves large numbers of people being called upon to co-operate on discrete projects whose completion would be beyond the scope of individuals or conventional organizations. A common approach adopted here is to break some large task down into a manageable number of sub-tasks and invite a community of users each to undertake some of them. Crowdsourcing draws on networks of human beings to solve particular problems, to carry out pieces of work, or even to raise finance for given initiatives. Again, this is highly collaborative. A load is shared: a problem, or a piece of work, or a sum of money is subdivided and the burden is distributed across a community.


pages: 322 words: 84,752

Pax Technica: How the Internet of Things May Set Us Free or Lock Us Up by Philip N. Howard

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Affordable Care Act / Obamacare, Berlin Wall, bitcoin, blood diamonds, Bretton Woods, Brian Krebs, British Empire, call centre, Chelsea Manning, citizen journalism, clean water, cloud computing, corporate social responsibility, crowdsourcing, Edward Snowden, en.wikipedia.org, failed state, Fall of the Berlin Wall, feminist movement, Filter Bubble, Firefox, Francis Fukuyama: the end of history, Google Earth, Howard Rheingold, income inequality, informal economy, Internet of things, Julian Assange, Kibera, Kickstarter, land reform, M-Pesa, Marshall McLuhan, megacity, Mikhail Gorbachev, mobile money, Mohammed Bouazizi, national security letter, Network effects, obamacare, Occupy movement, packet switching, pension reform, prediction markets, sentiment analysis, Silicon Valley, Skype, spectrum auction, statistical model, Stuxnet, trade route, uranium enrichment, WikiLeaks, zero day

Such initiatives are rarely able to cover an entire country in a systematic way, and they often need the backing of funding and skills from neutral outsiders like the National Democratic Institute.32 But even the most humble projects to map voting irregularities, film the voting process, or crowd-source polling results help expose and document electoral fraud. Such projects allow citizens to surveil government behavior at a local level, though democracy at the national level isn’t necessarily an outcome. Still, the highlight reels of voter fraud can end up online, wearing down bad government.33 Ushahidi is a user-friendly, open-source platform for mapping and crowd-sourcing information. These days, there are well over thirty-five thousand Ushahidi maps in thirty languages.34 In complex humanitarian disasters, most governments and United Nations agencies now know they need to take public crisis mapping seriously. Ushahidi isn’t the only platform, though it is one of the most popular because of its crowd-sourced content and community of volunteers.

Modern political life is rife with examples of how people have used social media to catch dictators off guard and engage their neighbors with political questions. Ushahidi, the mapping platform for crowd-sourced knowledge, has a good record of problem solving. It may be one of the largest and most high profile of such providers of connective action, but it’s not the only one. Uchaguzi is a platform built specifically for monitoring the Kenyan election in 2013.27 In neighboring Nigeria, researchers find that the number and location of electoral fraud reports is highly correlated with voter turnout.28 This means that social media are starting to generate statistically valid snapshots of what’s happening on the ground—even in countries as chaotic as Nigeria. Still, connective action doesn’t just happen through crowd-sourced maps. Indian Kanoon, an online, searchable database on Indian law, has opened up a whole swath of data to the average person.29 Many Indians are proud of living in the largest democracy in the world, but it is difficult for average citizens to understand Indian law.

Research on China’s feeble attempts at open government demonstrates that crowd sourcing doesn’t work well, and in China’s context is better thought of as “cadre sourcing.”18 This is because the kinds of information sought by the government have already been distorted by the government, enthusiastic cadre participants are more likely to report favorable information than accurate information, and news about independent crowd-sourcing initiatives don’t circulate far. Only during complex humanitarian disasters do people decide to take on the risks of contributing quality information. As device networks spread, civic initiatives will always have more positive impacts in open societies. Authoritarian societies are structurally prevented from making use of people’s goodwill and altruism. In the bounded device networks of an authoritarian regime, crowd-sourcing initiatives are likely to create negative feedback loops and big data efforts are likely to generate misinformation about the actual conditions of public life. With this pernicious structural flaw, how much faith should we have that China’s rival information infrastructure will stay rivalrous?


pages: 230 words: 61,702

The Internet of Us: Knowing More and Understanding Less in the Age of Big Data by Michael P. Lynch

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Affordable Care Act / Obamacare, Amazon Mechanical Turk, big data - Walmart - Pop Tarts, bitcoin, Cass Sunstein, Claude Shannon: information theory, crowdsourcing, Edward Snowden, Firefox, Google Glasses, hive mind, income inequality, Internet of things, John von Neumann, meta analysis, meta-analysis, Nate Silver, new economy, patient HM, prediction markets, RFID, sharing economy, Steve Jobs, Steven Levy, the scientific method, The Wisdom of Crowds, Thomas Kuhn: the structure of scientific revolutions, WikiLeaks

Inclusivity of a different sort can come about by what Wired’s Jeff Howe dubbed “crowdsourcing” in 2006. Crowdsourcing is not simply any activity that uses the World Wide Web as a platform for people to network about problems—like Intrade or rankings on Amazon. As computer scientist Daren Brabham defines it, crowdsourcing is an online problem-solving and production model that “leverages the collective intelligence of online communities to serve specific organizational goals.”2 In other words, it is the top-down organized use of the Internet hive-mind. An organization throws out a problem, and those who want (or those granted access to the relevant site or network) contribute solutions, and see what sticks. The popular incentive-based innovation platform InnoCentive is often cited as an example of the inclusivity of crowdsourcing. (InnoCentive is ancient in Web 2.0 terms: it was founded in 2002.)

“The traditional dream of rags to riches is being supplanted by a new dream of sustainable quality of life”—a life where we can spend more time engaged in pursuits that interest us, such as making music, cooking better food and thinking about philosophy.6 Rifkin thinks the same revolution is happening at the level of knowledge—perhaps especially there, since the wide availability of knowledge is the fuel powering the rest of our economy. But while Rifkin’s collaborative vision might be appealing, the death of capitalism—and exploitative versions of it—is hardly near. Take crowdsourcing as an example. Instead of an economy of skilled laborers that require resources to train, equip and compensate, crowdsourcing makes it possible for companies to distribute and generate knowledge without the expense of hiring those experts. This isn’t necessarily more “democratic.” But it is more capitalistic. Even some of the most active workers for Amazon’s Mechanical Turk can make very little, two to five dollars an hour. This may seem reasonable if you think of such laborers as amateurs—doing such work in their “spare time.”

Weinberger, Too Big to Know, 23. 15. Sosa, Reflective Knowledge, chs. 7 and 8.. 16. Pritchard, Epistemic Luck, 225. Chapter 7: Who Gets to Know 1. Lawrence M. Sanger, “Who Says We Know: On the New Politics of Knowledge,” Edge 208 (April 25, 2007): http://edge.org/3rd_culture/sanger07/sanger07_index.html%3E. Accessed August 25, 2015. 2. Brabham, Crowdsourcing, xix. 3. Jeppesen and Lakhani, “Marginality and Problem-Solving Effectiveness.” 4. Brabham, Crowdsourcing, 21. 5. Rifkin, The Zero Marginal Cost Society, 18. 6. Ibid., 19. See also 179–80. 7. Fricker rightly distinguishes epistemic inequality from what she calls epistemic injustice: Epistemic Injustice, 1–2. But the two are related, as noted below. 8. Frank LaRue, Special Rapporteur on the promotion and protection of the right to freedom of opinion and expression, Report to the Human Rights Council of the United Nations General Assembly, May 16, 2011.


pages: 327 words: 103,336

Everything Is Obvious: *Once You Know the Answer by Duncan J. Watts

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affirmative action, Albert Einstein, Amazon Mechanical Turk, Black Swan, butterfly effect, Carmen Reinhart, Cass Sunstein, clockwork universe, cognitive dissonance, collapse of Lehman Brothers, complexity theory, correlation does not imply causation, crowdsourcing, death of newspapers, discovery of DNA, East Village, easy for humans, difficult for computers, edge city, en.wikipedia.org, Erik Brynjolfsson, framing effect, Geoffrey West, Santa Fe Institute, happiness index / gross national happiness, high batting average, hindsight bias, illegal immigration, interest rate swap, invention of the printing press, invention of the telescope, invisible hand, Isaac Newton, Jane Jacobs, Jeff Bezos, Joseph Schumpeter, Kenneth Rogoff, lake wobegon effect, Long Term Capital Management, loss aversion, medical malpractice, meta analysis, meta-analysis, Milgram experiment, natural language processing, Netflix Prize, Network effects, oil shock, packet switching, pattern recognition, performance metric, phenotype, planetary scale, prediction markets, pre–internet, RAND corporation, random walk, RFID, school choice, Silicon Valley, statistical model, Steve Ballmer, Steve Jobs, Steve Wozniak, supply-chain management, The Death and Life of Great American Cities, the scientific method, The Wisdom of Crowds, too big to fail, Toyota Production System, ultimatum game, urban planning, Vincenzo Peruggia: Mona Lisa, Watson beat the top human players on Jeopardy!, X Prize

The solution is the Mullet Strategy: In the back pages where few people will see any particular story, let a thousand flowers bloom (or a million of them); then selectively promote material from the back to the front page, with all its premium advertising space, and keep that under strict editorial control.6 The Mullet Strategy is also an example of “crowdsourcing,” a term coined in a 2006 Wired article by Jeff Howe to describe the outsourcing of small jobs to potentially very large numbers of individual workers. Online journalism, in fact, is increasingly moving toward a crowdsourced model—not just for generating community activity around a news story but also for creating the stories themselves, or even deciding what topics to cover in the first place. The Huffington Post, for example, relies on thousands of unpaid bloggers who contribute content either out of passion for the topic they write about or else to benefit from the visibility they receive from being published on a widely read news site.

And BuzzFeed—a platform for launching “contagious media”—keeps track of hundreds of potential hits and only promotes those that are already generating enthusiastic responses from users.8 As creative as they are, these examples of crowdsourcing work best for media sites that already attract millions of visitors, and so automatically generate real-time information about what people like or don’t like. So if you’re not Bravo or Cheezburger or BuzzFeed—if you’re just some boring company that makes widgets or greeting cards or whatnot—how can you tap into the power of the crowd? Fortunately, crowdsourcing services like Amazon’s Mechanical Turk (which Winter Mason and I used to run our experiments on pay and performance that I discussed in Chapter 2) can also be used to perform fast and inexpensive market research.

“Multitask Principal-Agent Analyses: Incentive Contracts, Asset Ownership, and Job Design.” Journal of Law, Economics & Organization 7:24–52. Hoorens, Vera. 1993. “Self-Enhancement and Superiority Biases in Social Comparison.” European Review of Social Psychology 4 (1):113–39. Howard, Philip K. 1997. The Death of Common Sense. New York: Warner Books. Howe, Jeff. 2006. “The Rise of Crowdsourcing.” Wired Magazine 14 (6):1–4. ———. 2008. Crowdsourcing: Why the Power of the Crowd Is Driving the Future of Business. New York: Crown Business. Hu, Ye, Leonard M. Lodish, and Abba M. Krieger. 2007. “An Analysis of Real World TV Advertising Tests: A 15-year Update.” Journal of Advertising Research 47 (3):341. Huckfeldt, Robert, Paul E. Johnson, and John Sprague. 2004. Political Disagreement: The Survival of Disagreement with Communication Networks.

Frugal Innovation: How to Do Better With Less by Jaideep Prabhu Navi Radjou

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3D printing, additive manufacturing, Affordable Care Act / Obamacare, Airbnb, Albert Einstein, barriers to entry, Baxter: Rethink Robotics, Bretton Woods, business climate, business process, call centre, Capital in the Twenty-First Century by Thomas Piketty, carbon footprint, cloud computing, collaborative consumption, collaborative economy, connected car, corporate social responsibility, crowdsourcing, Elon Musk, financial innovation, global supply chain, income inequality, industrial robot, Internet of things, job satisfaction, Khan Academy, Kickstarter, late fees, Lean Startup, low cost carrier, M-Pesa, Mahatma Gandhi, megacity, minimum viable product, more computing power than Apollo, new economy, payday loans, peer-to-peer lending, Peter H. Diamandis: Planetary Resources, precision agriculture, race to the bottom, reshoring, ride hailing / ride sharing, risk tolerance, Ronald Coase, self-driving car, shareholder value, sharing economy, Silicon Valley, Silicon Valley startup, six sigma, smart grid, smart meter, software as a service, Steve Jobs, supply-chain management, TaskRabbit, The Fortune at the Bottom of the Pyramid, The Nature of the Firm, transaction costs, unbanked and underbanked, underbanked, women in the workforce, X Prize, yield management, Zipcar

Yet the Booz study estimates that only 8% of large R&D budgets are spent on digital tools that, among other things, track changing customer needs and help firms work with customers to create solutions.8 It is an obvious way to improve front-end innovation performance and, thanks to plummeting technology costs, affordable digital tools and techniques now exist to improve the depth and breadth of customer engagement. Deploy crowdsourcing and social media Crowdsourcing is a cost-effective technique for collecting customers’ ideas and ascertaining specific, explicit needs. For instance, SoapBox, a Toronto-based online crowdsourcing site, provides companies with a platform for individuals to talk about their ideas and gauge initial public reactions through its thumbs-up or thumbs-down voting system. Ideas that garner sufficient support are packaged with supporting data and sent to the relevant managers, who in turn signal their view of its potential to executives responsible for taking such ideas forward.

Co-create value with prosumers. Chapter 6 looks at ways consumers – especially the tech-savvy millennial generation (those born between 1982 and 2004) – are evolving from passive individual users into communities of empowered “prosumers”, who collectively design, create and share the products and services they want. As a result, R&D and marketing leaders at firms like Auchan are working with do-it-yourself (DIY) and crowdsourcing pioneers, such as TechShop and Quirky, to bolster and harness the collective ingenuity and skills of consumer communities. Additionally, big brands such as IKEA are linking up with start-ups such as Airbnb to develop a “sharing economy” in which consumers share goods and services. The chapter also outlines how sales and marketing managers can build greater brand affinity and deepen their engagement with customers by co-creating greater value for all.

An important aspect of the company’s business model is that the inventors themselves stand to make money from the process. Quirky claims that 10% of its direct revenues are shared with its online community; in 2013, inventors and online influencers shared a pot of $3.8 million. According to Ben Kaufman, the company’s CEO, two consumer products are developed every week. Quirky has launched several products based on crowdsourced ideas, including a flexible power strip, an egg separator and a smartphone-controlled air conditioner. Kaufman uses this as evidence to explain to corporate leaders he meets that the most innovative ideas do not necessarily come from the boardroom or from within the company, but from consumers and the general public. Increasingly, inventors do not even need access to companies like Quirky. Armed with a laptop, high-speed broadband and design software, individuals can manufacture one-off products and make a profit.


pages: 291 words: 90,200

Networks of Outrage and Hope: Social Movements in the Internet Age by Manuel Castells

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access to a mobile phone, banking crisis, call centre, centre right, citizen journalism, cognitive dissonance, collective bargaining, conceptual framework, crowdsourcing, currency manipulation / currency intervention, disintermediation, en.wikipedia.org, housing crisis, income inequality, microcredit, Mohammed Bouazizi, Occupy movement, offshore financial centre, Port of Oakland, social software, statistical model, We are the 99%, web application, WikiLeaks, World Values Survey, young professional

[Online] Available at: <http://www.VoxEU.org/index.php?q=node/7077> [Accessed on January 9, 2012]. Landamore, H. (2014) We, All the People. Five lessons from Iceland’s failed experiment in creating a crowdsourced constitution. Future Tense, [Online] July 31. Available at: <http://www.slate.com/articles/technology/future_tense/2014/07/five_lessons_from_iceland_s_failed_crowdsourced_constitution_experiment.html> [Accessed on November 17, 2014]. Siddique, H. (2011) Mob rule: Iceland crowdsources its next constitution. The Guardian, [Online] June 9. Available at: <http://www.guardian.co.uk/world/2011/jun/09/iceland-crowdsourcing-constitution-facebook/print> [Accessed on January 9, 2012]. On Iceland’s financial crisis Journal articles Wade, R. and Sigurgeirsdottir, S. (2010) Lessons from Iceland. New Left Review, 65: 5–29.

Available at: <http://ijoc.org/ojs/index.php/ijoc/article/view/1174/606>. On the Icelandic revolution Web resources Bennett, N. (2011) Iceland’s crowdsourced constitution – a lesson in open source marketing. [Online] Available at: <http://socialmediatoday.com/nick-bennett/305690/icelands-crowdsourced-constitution-lesson-opensource-marketing> [Accessed on January 9, 2012]. Boyes, R. (2009) Age of Testosterone comes to end in Iceland. The Times, [Online] February 7. Available at: <http://www.timesonline.co.uk/tol/news/world/europe/article5679378.ece> [Accessed on January 9, 2012]. Brown, M. (2011) Icelanders turn in first draft of crowdsourced constitution. Wired News, [Online] August 1. Available at: <http://www.wired.co.uk/news/archive/2011-08/01/iceland-constitution> [Accessed on January 9, 2012].

That the Constitution of a country could explicitly reflect principles that, in the context of global capitalism, are revolutionary shows the direct link between a process of genuinely popular crowdsourcing and the content resulting from such a participatory process. It should be remembered that the consultation and elaboration took place in four months as requested by the parliament, belying the notion of the ineffectiveness of participatory democracy. Granted, Iceland has only 320,000 citizens. But the defenders of the experience argue that with the Internet and with full Internet literacy and unrestricted access, this model of political participation and crowdsourcing of the legislative process is scalable. The reference that the Icelandic revolution came to be for European social movements battling the consequences of a devastating financial crisis is explained by its direct connection to the main issues that induced the protests.


pages: 382 words: 120,064

Bank 3.0: Why Banking Is No Longer Somewhere You Go but Something You Do by Brett King

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3D printing, additive manufacturing, Albert Einstein, Amazon Web Services, Any sufficiently advanced technology is indistinguishable from magic, asset-backed security, augmented reality, barriers to entry, bitcoin, bounce rate, business intelligence, business process, business process outsourcing, call centre, capital controls, citizen journalism, Clayton Christensen, cloud computing, credit crunch, crowdsourcing, disintermediation, en.wikipedia.org, George Gilder, Google Glasses, high net worth, I think there is a world market for maybe five computers, Infrastructure as a Service, invention of the printing press, Jeff Bezos, jimmy wales, London Interbank Offered Rate, M-Pesa, Mark Zuckerberg, mass affluent, microcredit, mobile money, more computing power than Apollo, Northern Rock, Occupy movement, optical character recognition, performance metric, platform as a service, QWERTY keyboard, Ray Kurzweil, recommendation engine, RFID, risk tolerance, self-driving car, Skype, speech recognition, stem cell, telepresence, Tim Cook: Apple, transaction costs, underbanked, web application

Figure 8.6: Use the power of the crowd for good, not evil (Credit: Washington Post) The concept of an idea lab or crowdsource engagement platform is hardly new. In fact, CommBank’s IdeaBank appears to be a close facsimile of First Direct’s “lab” launched five months earlier. First Direct was the UK’s first financial provider to exploit the power of crowdsourcing. First Direct Lab is, according to the official press release, a social platform “that will be populated with content every month such as product designs, service innovations and website concepts. Users will have the chance to critique the content through a comment facility and forum, with the feedback collated and inputted into the product or service teams before release”. Figure 8.7: First Direct was the first to launch a crowdsourcing platform for regular interaction with the crowd (Credit: First Direct UK) Finding out how customers interact with financial services can be tricky and expensive.

Figure 8.8: DBS Remix branch, a result of crowdsourced input (Credit: DBS) Not to be outdone in the supercompetitive market of Singapore, OCBC then launched its own initiative to crowdsource not just a new branch design, but a whole new Y-Gen-focused brand initiative. The result was FRANK by OCBC. Frank (or #frankbyocbc) has been phenomenally successful in building a “cult”’ brand following within their intended Y-Gen segment. Figure 8.9 and 8.10: FRANK (Credit: OCBC) If you want to engage customers, why not let them choose the direction for a selection of new products, branch design or engagement approaches. What have you got to lose? A good best practice for this is, not surprisingly, from outside of financial services. A great crowdsourcing platform is also one of the hottest conferences on innovation on the planet—known as SXSW—but more formally as South-by-South-West.

Regardless of where social media is taking us, credibility is built only through dialogue and open communication with the crowd. If you aren’t in the game already, it’s getting harder and harder to get a proper seat at the table. There’s no technological fix to being able to tell whether or not people like you. There’s only the ability to change the way you talk to your audience. Crowdsourcing—use the power of the crowd The “occupy” movement we talked about earlier is an example of how communities work in the social, hyperconnected landscape of today. However, there is a mechanism for using crowdsourcing as a mechanism for designing new products and services that are immediately advocated by customers because they were designed by the crowd, for the crowd. Commonwealth Bank in Australia has invited the crowd to submit, discuss and vote on ideas that improve the Australian banking experience.


pages: 339 words: 88,732

The Second Machine Age: Work, Progress, and Prosperity in a Time of Brilliant Technologies by Erik Brynjolfsson, Andrew McAfee

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2013 Report for America's Infrastructure - American Society of Civil Engineers - 19 March 2013, 3D printing, access to a mobile phone, additive manufacturing, Airbnb, Albert Einstein, Amazon Mechanical Turk, Amazon Web Services, American Society of Civil Engineers: Report Card, Any sufficiently advanced technology is indistinguishable from magic, autonomous vehicles, barriers to entry, Baxter: Rethink Robotics, British Empire, business intelligence, business process, call centre, clean water, combinatorial explosion, computer age, computer vision, congestion charging, corporate governance, crowdsourcing, David Ricardo: comparative advantage, employer provided health coverage, en.wikipedia.org, Erik Brynjolfsson, factory automation, falling living standards, Filter Bubble, first square of the chessboard / second half of the chessboard, Frank Levy and Richard Murnane: The New Division of Labor, Freestyle chess, full employment, game design, global village, happiness index / gross national happiness, illegal immigration, immigration reform, income inequality, income per capita, indoor plumbing, industrial robot, informal economy, inventory management, James Watt: steam engine, Jeff Bezos, jimmy wales, job automation, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, Joseph Schumpeter, Kevin Kelly, Khan Academy, knowledge worker, Kodak vs Instagram, law of one price, low skilled workers, Lyft, Mahatma Gandhi, manufacturing employment, Mark Zuckerberg, Mars Rover, means of production, Narrative Science, Nate Silver, natural language processing, Network effects, new economy, New Urbanism, Nicholas Carr, Occupy movement, oil shale / tar sands, oil shock, pattern recognition, payday loans, price stability, Productivity paradox, profit maximization, Ralph Nader, Ray Kurzweil, recommendation engine, Report Card for America’s Infrastructure, Robert Gordon, Rodney Brooks, Ronald Reagan, Second Machine Age, self-driving car, sharing economy, Silicon Valley, Simon Kuznets, six sigma, Skype, software patent, sovereign wealth fund, speech recognition, statistical model, Steve Jobs, Steven Pinker, Stuxnet, supply-chain management, TaskRabbit, technological singularity, telepresence, The Bell Curve by Richard Herrnstein and Charles Murray, The Signal and the Noise by Nate Silver, The Wealth of Nations by Adam Smith, total factor productivity, transaction costs, Tyler Cowen: Great Stagnation, Vernor Vinge, Watson beat the top human players on Jeopardy!, winner-take-all economy, Y2K

It was an example of what Amazon CEO Jeff Bezos called “artificial artificial intelligence,” and another way for people to race with machines, although not one with particularly high wages.26 Mechanical Turk, which quickly became popular, was an early instance of what came to be called crowdsourcing, defined by communications scholar Daren Brabham as “an online, distributed problem-solving and production model.”27 This model is interesting because instead of using technology to automate a process, crowdsourcing makes it deliberately labor intensive. The labor is provided not by a preidentified group of employees, as is the case with most industrial processes, but instead by one or more people (often many more), not identified in advance, who choose to participate. In less than a decade, crowdsourced production has become an important phenomenon. In fact, it’s given rise to a large new crop of companies, often grouped together as the ‘peer economy.’ Peer economy companies satisfy their customers’ requests by crowdsourcing them. Some of the graphs you see in this book, for example, were generated or improved by people we’d never met before.

Cragin said that, “Though I hadn’t worked in the area of solar physics as such, I had thought a lot about the theory of magnetic reconnection.”22 This was evidently the right theory for the job, because Cragin’s approach enabled prediction of SPEs eight hours in advance with 85 percent accuracy, and twenty-four hours in advance with 75 percent accuracy. His recombination of theory and data earned him a thirty-thousand-dollar reward from the space agency. In recent years, many organizations have adopted NASA’s strategy of using technology to open up their innovation challenges and opportunities to more eyeballs. This phenomenon goes by several names, including ‘open innovation’ and ‘crowdsourcing,’ and it can be remarkably effective. The innovation scholars Lars Bo Jeppesen and Karim Lakhani studied 166 scientific problems posted to Innocentive, all of which had stumped their home organizations. They found that the crowd assembled around Innocentive was able to solve forty-nine of them, for a success rate of nearly 30 percent. They also found that people whose expertise was far away from the apparent domain of the problem were more likely to submit winning solutions.

One of its most successful products, a flexible electrical power strip called Pivot Power, sold more than 373 thousand units in less than two years and earned the crowd responsible for its development over $400,000. Affinnova, yet another young company supporting recombinant innovation, helps its customers with the second of Weitzman’s two phases: sorting through the possible combinations of building blocks to find the most valuable ones. It does this by combining crowdsourcing with Nobel Prize–worthy algorithms. When Carlsberg breweries wanted to update the bottle and label for Belgium’s Grimbergen, the world’s oldest continually produced abbey beer, it knew it had to proceed carefully. The company wanted to update the brand without sacrificing its strong reputation or downplaying its nine hundred years of history. It knew that the redesign would mean generating many candidates for each of several attributes—bottle shape, embossments, label color, label placement, cap design, and so on—then settling on the right combination of all of these.


pages: 259 words: 73,193

The End of Absence: Reclaiming What We've Lost in a World of Constant Connection by Michael Harris

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4chan, Albert Einstein, AltaVista, Andrew Keen, augmented reality, Burning Man, cognitive dissonance, crowdsourcing, dematerialisation, en.wikipedia.org, Filter Bubble, Firefox, Google Glasses, informal economy, information retrieval, invention of movable type, invention of the printing press, invisible hand, James Watt: steam engine, Jaron Lanier, jimmy wales, Kevin Kelly, Loebner Prize, Marshall McLuhan, McMansion, Nicholas Carr, pattern recognition, pre–internet, Republic of Letters, Silicon Valley, Skype, Snapchat, social web, Steve Jobs, the medium is the message, The Wisdom of Crowds, Turing test

The process of intellectual exploration, once highly idiosyncratic, becomes an opportunity to promote whatever material has the highest view count. “Until now,” Ng told me, “education has been a largely anecdotal science, and we can now make it data-driven.” This reminded me, of course, of Karthik Dinakar, eager to “harden” the soft sciences of psychology and psychiatry with reams of crowdsourced data. The crowdsourcing of education is further highlighted by Ng’s interest in Wiki lecture notes. “At Stanford,” he explained to me, “I taught a class for a decade, and writing the lecture notes would take forever. And then, every year, students would find more bugs, more errors, in my notes. But for online classes, I put up a Wiki and invite students to write their own lecture notes; students watch my lectures and create the notes themselves.

And that everybody in the world is going to respond to it like the mean-spirited person that created it.” Dinakar watched the program, figuring there must be a way to stem such cruelty, to monitor and manage unacceptable online behavior. Most social Web sites leave it to the public. Facebook, Twitter, and the like incorporate a button that allows users to “flag this as inappropriate” when they see something they disapprove of. In the age of crowdsourced knowledge like Wikipedia’s, such user-driven moderation sounds like common sense, and perhaps it is.8 “But what happens,” Dinakar explains, “is that all flagging goes into a stream where a moderation team has to look at it. Nobody gets banned automatically, so the problem becomes how do you deal with eight hundred million users throwing up content and flagging each other?” (Indeed, Facebook has well over one billion users whose actions it must manage.)

Unfortunately, Feldman (though she may well be a real person) did not invent the hair iron, and on September 15, 2009, Wikipedia was forced to consign the Feldman affair to their growing list of hoaxes. Not a particularly scandalous or even interesting hoax, but such is the banality of error. Four years later, I asked Wiki.Answers.com (the largest Q&A site online) who Erica Feldman is and was redirected to a set of crowdsourced “Relevant Answers” that claimed she is both alive and that she invented the hair straightener in 1872 (making her more than 140 years old). I was also informed of the Feldman hairdo, which involves “slicked-back long hair with one strand hanging over the forehead.” These results were displayed alongside a number of hair-focused advertisements. Even the algorithms that choose which companies should hawk things at me when I search for “Erica Feldman” are in on the mass delusion.


pages: 588 words: 131,025

The Patient Will See You Now: The Future of Medicine Is in Your Hands by Eric Topol

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23andMe, 3D printing, Affordable Care Act / Obamacare, Anne Wojcicki, Atul Gawande, augmented reality, bioinformatics, call centre, Clayton Christensen, clean water, cloud computing, computer vision, conceptual framework, connected car, correlation does not imply causation, crowdsourcing, dark matter, data acquisition, disintermediation, don't be evil, Edward Snowden, Elon Musk, en.wikipedia.org, Erik Brynjolfsson, Firefox, global village, Google Glasses, Google X / Alphabet X, Ignaz Semmelweis: hand washing, interchangeable parts, Internet of things, Isaac Newton, job automation, Joseph Schumpeter, Julian Assange, Kevin Kelly, license plate recognition, Lyft, Mark Zuckerberg, Marshall McLuhan, meta analysis, meta-analysis, microbiome, Nate Silver, natural language processing, Network effects, Nicholas Carr, obamacare, pattern recognition, personalized medicine, phenotype, placebo effect, RAND corporation, randomized controlled trial, Second Machine Age, self-driving car, Silicon Valley, Skype, smart cities, Smart Cities: Big Data, Civic Hackers, and the Quest for a New Utopia, Snapchat, social graph, speech recognition, stealth mode startup, Steve Jobs, the scientific method, The Signal and the Noise by Nate Silver, The Wealth of Nations by Adam Smith, Turing test, Uber for X, Watson beat the top human players on Jeopardy!, X Prize

K. Murphy, “Crowdfunding Tips for Turning Inspiration into Reality,” New York Times, January 23, 2014, http://www.nytimes.com/2014/01/23/technology/personaltech/crowdfunding-tips-for-turning-inspiration-into-reality.html. 125. B. L. Ranard et al., “Crowdsourcing—Harnessing the Masses to Advance Health and Medicine, a Systematic Review,” Journal of General Internal Medicine 29, no. 1 (2013): 187–203. 126. S. Novella, “CureCrowd—Crowdsourcing Science,” Science Based Medicine, May 7, 2014, http://www.sciencebasedmedicine.org/curecrowd-crowdsourcing-science/. 127. “Open-Source Medical Devices: When Code Can Kill or Cure,” The Economist, May 31, 2012, http://www.economist.com/node/21556098. Chapter 12 1. L. Fox, “Snowden and His Accomplices,” Wall Street Journal, April 14, 2014, http://online.wsj.com/news/articles/SB10001424052702303603904579495391321958008. 2.

Collectively, via the social online health network PatientsLikeMe, a rapid crowdsourced clinical trial took form, albeit without controls (patients not receiving sodium chlorite) but showing no sign of efficacy. In fact, taking sodium chlorite was associated with an adverse effect.102,103 Using clever algorithms, PatientsLikeMe can simulate a randomized trial within their database and had already demonstrated that another candidate drug for ALS, lithium bicarbonate, was ineffective using this method. That finding was subsequently validated by a traditional, expensive, and time-consuming randomized trial. Although open is not a guarantee of good outcomes, social online networks of “ePatients” with like conditions do have real advantages over classic clinical trials. A major one is that they provide unique, real-world, relevant crowdsourcing information.

., “Detection of a Recurrent DNAJB1-PRKACA Chimeric Transcript in Fibrolamellar Hepatocellular Carcinoma,” Science 343, no. 6174 (2014): 1010–1014. 102. A. D. Marcus, “Frustrated ALS Patients Concoct Their Own Drug,” Wall Street Journal, April 15, 2012, http://online.wsj.com/news/articles/SB10001424052702304818404577345953943484054?mg=reno64-wsj. 103. D. L. Scher, “Crowdsourced Clinical Studies: A New Paradigm in Health Care?,” Digital Health Corner, March 30, 2012, http://davidleescher.com/2012/03/30/crowdsourced-clinical-studies-a-new-paradigm-in-health-care/. 104. A. Hamilton, “Could ePatient Networks Become the Superdoctors of the Future?,” Fast Coexist, September 28, 2012, http://www.fastcoexist.com/1680617/could-epatient-networks-become-the-superdoctors-of-the-future. 105. L. Scanlon, “Genentech and PatientsLikeMe Enter Patient-Centric Research Collaboration,” PatientsLikeMe, April 7, 2014, http://news.patientslikeme.com/print/node/470. 106.


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To Save Everything, Click Here: The Folly of Technological Solutionism by Evgeny Morozov

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3D printing, algorithmic trading, Amazon Mechanical Turk, Andrew Keen, augmented reality, Automated Insights, Berlin Wall, big data - Walmart - Pop Tarts, Buckminster Fuller, call centre, carbon footprint, Cass Sunstein, choice architecture, citizen journalism, cloud computing, cognitive bias, crowdsourcing, data acquisition, Dava Sobel, disintermediation, East Village, en.wikipedia.org, Fall of the Berlin Wall, Filter Bubble, Firefox, Francis Fukuyama: the end of history, frictionless, future of journalism, game design, Gary Taubes, Google Glasses, illegal immigration, income inequality, invention of the printing press, Jane Jacobs, Jean Tirole, Jeff Bezos, jimmy wales, Julian Assange, Kevin Kelly, Kickstarter, license plate recognition, lone genius, Louis Pasteur, Mark Zuckerberg, market fundamentalism, Marshall McLuhan, Narrative Science, Nicholas Carr, packet switching, PageRank, Paul Graham, Peter Singer: altruism, Peter Thiel, pets.com, placebo effect, pre–internet, Ray Kurzweil, recommendation engine, Richard Thaler, Ronald Coase, Rosa Parks, self-driving car, Silicon Valley, Silicon Valley ideology, Silicon Valley startup, Skype, Slavoj Žižek, smart meter, social graph, social web, stakhanovite, Steve Jobs, Steven Levy, Stuxnet, technoutopianism, the built environment, The Chicago School, The Death and Life of Great American Cities, the medium is the message, The Nature of the Firm, the scientific method, The Wisdom of Crowds, Thomas Kuhn: the structure of scientific revolutions, Thomas L Friedman, transaction costs, urban decay, urban planning, urban sprawl, Vannevar Bush, WikiLeaks

Sol Schwimmer is suing me”: Woody Allen, The Complete Prose of Woody Allen (New York: Wings Books, 1991), 105. 35 “when we think of information technology”: David Edgerton, Shock of the Old: Technology and Global History Since 1900 (London: Profile Books, 2011), xvi. 36 “the most wrenching cultural transformation since the Industrial Revolution”: “‘Antichrist of Silicon Valley,’ Andrew Keen Wary of Online Content Sharing,” Economic Times, May 29, 2012. 37 they don’t always capture the historical complexity: on the longitude problem, see Dava Sobel’s accessible history Longitude: The True Story of a Lone Genius Who Solved the Greatest Scientific Problem of His Time, reprint ed. (New York: Walker & Company, 2007). On early crowdsourcing efforts by the Smithsonian, see “Smithsonian Crowd-sourcing since 1849!,” Smithsonian Institution Archives, April 14, 2011, http://siarchives.si.edu/blog/smithsonian-crowdsourcing-1849. I learned of Toyota’s efforts via this blog post on pre-Internet crowd-sourcing efforts: “Crowdsourcing Is Not New—the History of Crowdsourcing (1714 to 2010),” DesignCrowd, October 28, 2010, http://blog.designcrowd.com/article/202/crowdsourcing. 37 “Knowledge is taking on the shape of the Net”: David Weinberger, Too Big to Know: Rethinking Knowledge Now that the Facts Aren’t the Facts, Experts Are Everywhere, and the Smartest Person in the Room Is the Room (New York: Basic Books, 2012), 17.

Such circularity—whereby “the Internet” is seen as revolutionary because of Factor X, but Factor X is seen as revolutionary because of “the Internet”—is silly, but in an era of profound and revolutionary change, this passes for deep insight. Take the fake novelty of a term like “crowdsourcing”—supposedly, one of the chief attributes of the Internet era, an idea that gave us that great source of didactic knowledge, Wikipedia. “Crowdsourcing” is certainly a very effective term; calling some of the practices it enables as “digitally distributed sweatshop labor”—for this seems like a much better description of what’s happening on crowdsource-for-money platforms like Amazon’s Mechanical Turk—wouldn’t accomplish half as much. But effective euphemisms come with trade-offs; they don’t always capture the historical complexity of the processes they purport to describe. Didn’t the British government turn to “crowdsourcing”—in 1714!—to solve the “longitude problem” and solicit proposals for how to better navigate at sea?

Didn’t the Smithsonian Institution—in 1849!—turn to a network of over six hundred volunteer observers (in Canada, Mexico, Latin America, and the Caribbean) to submit monthly weather reports (published in 1861 as the first of a two-volume compilation of climactic data)? Didn’t Toyota hold a contest—in 1936!—to redesign its logo, only to receive 27,000 entries in return? Didn’t Zagat turn to a form of “crowdsourcing” to generate its restaurant reviews long before Yelp made online reviews fashionable? Granted, today it’s much easier and cheaper to do such things, but a revolution in knowledge gathering it isn’t—not if we want the word “revolution” to retain any meaning at all. This message, however, is lost on our Internet pundits, who think that “the Internet” has fundamentally altered how knowledge is produced—nay, it has even altered what counts as knowledge.


pages: 188 words: 9,226

Collaborative Futures by Mike Linksvayer, Michael Mandiberg, Mushon Zer-Aviv

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4chan, Benjamin Mako Hill, British Empire, citizen journalism, cloud computing, collaborative economy, corporate governance, crowdsourcing, Debian, en.wikipedia.org, Firefox, informal economy, jimmy wales, Kickstarter, late capitalism, loose coupling, Marshall McLuhan, means of production, Naomi Klein, Network effects, optical character recognition, packet switching, postnationalism / post nation state, prediction markets, Richard Stallman, semantic web, Silicon Valley, slashdot, Slavoj Žižek, stealth mode startup, technoutopianism, the medium is the message, The Wisdom of Crowds, web application

Glossary: Architecture 100 From Splicing Code to Assembling Social Solidarities We can already see early examples of these approaches outside of Free So ware. One of them is the Twi er Vote Report used in the 2008 US presidential elections <twi ervotereport.com> and its later incarnation as Swi River, a tool for crowdsourcing situational awareness: “Swi hopes to expand [Twi er Vote Report’s] approach into a general purpose toolkit for crowdsourcing the semantic structuring of data so that it can be reused in other applications and visualizations. The developers of Swi are particularly interested in crisis reporting (Ushahidi) and international media criticism (Meedan), but by providing a general purpose crowdsourcing tool we hope to create a tool reusable in many contexts. Swi engages self-interested teams of “citizen editors” who curate publicly available information about a crisis or any event or region as it happens” —Swi Project, 2010 <h p://github.com/unthinkingly/swi river_rails> These activist hacker initiatives are realizing the potential of loosely coordinated distributed action.

Process Fetishism There's a risk of making a fetish of process over product, of the act of collaboration over the artifact that results from it. How important is it that a product was produced through an open, distributed network if, in the end, it serves the interests of the status quo? If it's just another widget, another distraction, an added value that some giant conglomerate can take advantage of, as in some cases of crowdsourcing? Does open collaboration serve a purpose or is it more like a drum circle, way more fun and interesting for the participants than for those who are forced to listen to it? Collaboration is fundamental to human experience. It should be no surprise that collaboration also occurs online. The important question is what goals these new opportunities for cooperation and creation across space and time are put in service of.

Glossary: Tyranny Among us. 105 29. Free vs. Gratis Labor What makes a collaboration “open”? Open appears to be an assertion of —though it is more accurately an aspiration towards—egalitarianism, inclusion, non-coerciveness, freedom. But what kind of freedom? Free as in unscripted and improvisatory, free as in freely chosen, free as in unpaid, or free as in it won't tie you down? As books like Jeff Howe’s Crowdsourcing: Why The Power of the Crowd is Driving the Future of Business show, corporate America is ready to collaborate. They want to have an open relationship with their workforce, because who can beat free? And by turning their consumers into collaborators, the bond between the company and their customers is made even stronger. Meanwhile, everyday people are happy to help. Why? Howe says people do it for fun and for the “cred”, otherwise known as the “emerging reputation economy.”


pages: 538 words: 141,822

The Net Delusion: The Dark Side of Internet Freedom by Evgeny Morozov

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A Declaration of the Independence of Cyberspace, Ayatollah Khomeini, Berlin Wall, borderless world, Buckminster Fuller, Cass Sunstein, citizen journalism, cloud computing, cognitive dissonance, Columbine, computer age, conceptual framework, crowdsourcing, Dissolution of the Soviet Union, don't be evil, failed state, Fall of the Berlin Wall, Francis Fukuyama: the end of history, global village, Google Earth, illegal immigration, invention of radio, invention of the printing press, invisible hand, John von Neumann, Marshall McLuhan, Naomi Klein, Network effects, new economy, New Urbanism, pirate software, pre–internet, Productivity paradox, RAND corporation, Ronald Reagan, Ronald Reagan: Tear down this wall, Silicon Valley, Silicon Valley startup, Sinatra Doctrine, Skype, Slavoj Žižek, social graph, Steve Jobs, technoutopianism, The Wisdom of Crowds, urban planning, Washington Consensus, WikiLeaks, women in the workforce

In the Saudi case, banned porn websites carry a message that explains in detail the reasons for the ban, referencing a Duke Law Journal article on pornography written by the American legal scholar Cass Sunstein and a 1,960-page study conducted by the U.S. attorney general’s Commission on Pornography in 1986. (At least for most nonlawyers, those are probably far less satisfying than the porn pages they were seeking to visit.) The practice of “crowdsourcing” censorship is becoming popular in democracies as well. Both the British and the French authorities have similar schemes for their citizens to report child pornography and several other kinds of illegal content. As there are more and more websites and blogs to check for illegal material, it’s quite likely that such crowdsourcing schemes will become more common. The Thai, Saudi, and British authorities rely on citizens’ goodwill, but a new scheme in China actually offers monetary awards to anyone submitting links to online pornography. Found a porn site?

One such tool, Ushahidi, was first designed to report on violence during the postelection crisis in Kenya and since then has been successfully deployed all over the world, including in the devastating earthquakes in Haiti and Chile in early 2010. But the reason why many projects that rely on crowdsourcing produce trustworthy data in natural disasters is because those are usually apolitical events. There are no warring sides, and those who report data do not have any incentives to manipulate it. The problem with using such crowdsourced tools for other purposes—for example, documenting human rights abuses or monitoring elections, some of the other uses to which Ushahidi has been put—is that the accuracy of such reports is impossible to verify and easy to manipulate. After all, anyone can text in deliberately erroneous reports to accuse their opponents of wrongdoing or, even worse, to sow panic in their ranks (remember the Nigerian SMS that said that all food was poisoned?).

Craig, G. A. “The Professional Diplomat and His Problems, 1919-1939.” World Politics: A Quarterly Journal of International Relations 4, no. 2 (1952): 145-158. Currion, Paul. “Better the Devil We Know: Obstacles and Opportunities in Humanitarian GIS.” Humanitarian.info, January 25, 2006. www.humanitarian.info/humanitarian-gis/. ———. “Correcting Crowdsourcing in a Crisis.” Humanitarian.info, March 30, 2009. www.humanitarian.info/2009/03/30/correcting-crowdsourcing-in-a-crisis/. “Cyber-Nationalism: The Brave New World of E-hatred.” Economist, July 24, 2008. Dahlberg, L. “Rethinking the Fragmentation of the Cyberpublic: From Consensus to Contestation.” New Media & Society 9, no. 5 (2007): 827. Dewan, Shaila. “Chinese Student in U.S. Is Caught in Confrontation.” New York Times, April 17, 2008. Doppelt, G.


pages: 330 words: 91,805

Peers Inc: How People and Platforms Are Inventing the Collaborative Economy and Reinventing Capitalism by Robin Chase

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3D printing, Airbnb, Amazon Web Services, Andy Kessler, banking crisis, barriers to entry, bitcoin, blockchain, Burning Man, business climate, call centre, car-free, cloud computing, collaborative consumption, collaborative economy, collective bargaining, congestion charging, crowdsourcing, cryptocurrency, decarbonisation, don't be evil, Elon Musk, en.wikipedia.org, ethereum blockchain, Ferguson, Missouri, Firefox, frictionless, Gini coefficient, hive mind, income inequality, index fund, informal economy, Internet of things, Jane Jacobs, Jeff Bezos, jimmy wales, job satisfaction, Kickstarter, Lean Startup, Lyft, means of production, megacity, Minecraft, minimum viable product, Network effects, new economy, Oculus Rift, openstreetmap, optical character recognition, pattern recognition, peer-to-peer lending, Richard Stallman, ride hailing / ride sharing, Ronald Coase, Ronald Reagan, Satoshi Nakamoto, Search for Extraterrestrial Intelligence, self-driving car, shareholder value, sharing economy, Silicon Valley, six sigma, Skype, smart cities, smart grid, Snapchat, sovereign wealth fund, Steve Crocker, Steve Jobs, Steven Levy, TaskRabbit, The Death and Life of Great American Cities, The Nature of the Firm, transaction costs, Turing test, Uber and Lyft, Zipcar

I understood clearly that we were on a path that was going to break a hundred-year-old industry. What I failed to appreciate back then was the much larger movement made possible by the Internet. Zipcar was a trailblazer. When you can connect and share assets, people, and ideas, everything changes, not just how you rent a car. Google, eBay, Facebook, OKCupid, YouTube, Waze, Airbnb, WhatsApp, Duolingo—all are part of this transformation of capitalism. Web 2.0, the sharing economy, crowdsourcing, collaborative production, collaborative consumption, and network effects are simply terms we’ve created along the way in an effort to capture what is going on. Attributing all this to “the Internet” misses the building blocks and therefore the ability to replicate this type of activity in a more controlled way. There is one structure that underlies all these—excess capacity + a platform for participation + diverse peers—and it is fundamentally changing the way we work, build businesses, and shape economies.

Packaged products are shipped off to five global warehouses and distribution centers, which in turn send those boxes on to 35,000 retail locations.26 As the company has grown, Quirky has been able to partner with both physical and online retailers to sell its products. A $69 million financing in November 2013, including $30 million from GE, allowed Quirky to spin off Wink, a wholly owned subsidiary.27 Wink provides a technology ecosystem (a platform) that makes it simple to bring together connected-home devices with smartphones, giving GE a way to participate in both the Internet of Things and crowd-sourced innovation. (Chapter 8 will delve into the ways in which large mainstream companies are adapting to the new organizational paradigm.) The first GE + Quirky–branded product was the Aros air conditioner, which lets you change the room temperature setting from a distance when you are away, and which automatically instructs your Aros to begin cooling the room to a predetermined temperature when your smartphone is within a certain proximity of home.

We could have averted the thousands of horrific deaths, decimated families, countless hours of suffering and worrying, and billions of dollars in medical aid if we had listened to the right person at the right time. The U.S. Agency for International Development’s Ebola Grand Challenge is the late-breaking but now deep-within-the-crisis Peers Inc approach, using the OpenIdeo platform to collect insight into the situation on the ground and integrate learning from hospitals and universities.13 Today, we connected peers have access to crowdsourced best practices plus supercomputing power plus the insight of people who are right there on the ground and just a step ahead of us. Institutions tasked with responsibilities as enormous as fighting diseases such as Ebola are catching up as fast as they can. Even the U.S. Department of Defense has a disaster relief expert coordination team, STAR-TIDES, striving to provide the deft touch, the fluid access to expertise required to assist teams in the field with a connection to the right people at the right time.


pages: 685 words: 203,949

The Organized Mind: Thinking Straight in the Age of Information Overload by Daniel J. Levitin

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airport security, Albert Einstein, Amazon Mechanical Turk, Anton Chekhov, big-box store, business process, call centre, Claude Shannon: information theory, cloud computing, cognitive bias, complexity theory, computer vision, conceptual framework, correlation does not imply causation, crowdsourcing, cuban missile crisis, Daniel Kahneman / Amos Tversky, delayed gratification, Donald Trump, en.wikipedia.org, epigenetics, Eratosthenes, Exxon Valdez, framing effect, friendly fire, fundamental attribution error, Golden Gate Park, Google Glasses, haute cuisine, impulse control, index card, indoor plumbing, information retrieval, invention of writing, iterative process, jimmy wales, job satisfaction, Kickstarter, life extension, meta analysis, meta-analysis, more computing power than Apollo, Network effects, new economy, Nicholas Carr, optical character recognition, pattern recognition, phenotype, placebo effect, pre–internet, profit motive, randomized controlled trial, Skype, Snapchat, statistical model, Steve Jobs, supply-chain management, the scientific method, The Wealth of Nations by Adam Smith, The Wisdom of Crowds, theory of mind, Turing test, ultimatum game

This feeling appears to be culturally universal and innate. The Amber Alert is an example of crowdsourcing—outsourcing to a crowd—the technique by which thousands or even millions of people help to solve problems that would be difficult or impossible to solve any other way. Crowdsourcing has been used for all kinds of things, including wildlife and bird counts, providing usage examples and quotes to the editors of the Oxford English Dictionary, and helping to decipher ambiguous text. The U.S. military and law enforcement have taken an interest in it because it potentially increases the amount of data they get by turning a large number of civilians into team members in information gathering. Crowdsourcing is just one example of organizing our social world—our social networks—to harness the energy, expertise, and physical presence of many individuals for the benefit of all.

A large number of people—the public—can often help to solve big problems outside of traditional institutions such as public agencies. Wikipedia is an example of crowdsourcing: Anyone with information is encouraged to contribute, and through this, it has become the largest reference work in the world. What Wikipedia did for encyclopedias, Kickstarter did for venture capital: More than 4.5 million people have contributed over $750 million to fund roughly 50,000 creative projects by filmmakers, musicians, painters, designers, and other artists. Kiva applied the concept to banking, using crowdsourcing to kick-start economic independence by sponsoring microloans that help start small businesses in developing countries. In its first nine years, Kiva has given out loans totaling $500 million to one million people in seventy different countries, with crowdsourced contributions from nearly one million lenders. The people who make up the crowd in crowdsourcing are typically amateurs and enthusiastic hobbyists, although this doesn’t necessarily have to be the case.

In its first nine years, Kiva has given out loans totaling $500 million to one million people in seventy different countries, with crowdsourced contributions from nearly one million lenders. The people who make up the crowd in crowdsourcing are typically amateurs and enthusiastic hobbyists, although this doesn’t necessarily have to be the case. Crowdsourcing is perhaps most visible as a form of consumer ratings via Yelp, Zagat, and product ratings on sites such as Amazon.com. In the old, pre-Internet days, a class of workers existed who were expert reviewers and they would share their impressions of products and services in newspaper articles or magazines such as Consumer Reports. Now, with TripAdvisor, Yelp, Angie’s List, and others of their ilk, ordinary people are empowered to write reviews about their own experiences. This cuts both ways. In the best cases, we are able to learn from the experiences of hundreds of people about whether this motel is clean and quiet, or that restaurant is greasy and has small portions.


pages: 515 words: 126,820

Blockchain Revolution: How the Technology Behind Bitcoin Is Changing Money, Business, and the World by Don Tapscott, Alex Tapscott

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Airbnb, altcoin, asset-backed security, autonomous vehicles, barriers to entry, bitcoin, blockchain, Bretton Woods, business process, Capital in the Twenty-First Century by Thomas Piketty, carbon footprint, clean water, cloud computing, cognitive dissonance, corporate governance, corporate social responsibility, Credit Default Swap, crowdsourcing, cryptocurrency, disintermediation, distributed ledger, Donald Trump, double entry bookkeeping, Edward Snowden, Elon Musk, Erik Brynjolfsson, ethereum blockchain, failed state, fiat currency, financial innovation, Firefox, first square of the chessboard, first square of the chessboard / second half of the chessboard, future of work, Galaxy Zoo, George Gilder, glass ceiling, Google bus, Hernando de Soto, income inequality, informal economy, interest rate swap, Internet of things, Jeff Bezos, jimmy wales, Kickstarter, knowledge worker, Kodak vs Instagram, Lean Startup, litecoin, Lyft, M-Pesa, Mark Zuckerberg, Marshall McLuhan, means of production, microcredit, mobile money, Network effects, new economy, Oculus Rift, pattern recognition, peer-to-peer lending, performance metric, Peter Thiel, planetary scale, Ponzi scheme, prediction markets, price mechanism, Productivity paradox, quantitative easing, ransomware, Ray Kurzweil, renewable energy credits, rent-seeking, ride hailing / ride sharing, Ronald Coase, Ronald Reagan, Satoshi Nakamoto, Second Machine Age, seigniorage, self-driving car, sharing economy, Silicon Valley, Skype, smart contracts, smart grid, social graph, social software, Stephen Hawking, Steve Jobs, Steve Wozniak, Stewart Brand, supply-chain management, TaskRabbit, The Fortune at the Bottom of the Pyramid, The Nature of the Firm, The Wisdom of Crowds, transaction costs, Turing complete, Turing test, Uber and Lyft, unbanked and underbanked, underbanked, unorthodox policies, X Prize, Y2K, Zipcar

Augur’s style of prediction making could engage citizens in making small choices that contribute to national discussions of policy, eventually shaping the future of their own democracy. Blockchain Judiciary The blockchain can also transform our judiciary. Combining the concepts of transparency, crowdsourcing, and online citizen participation—over a blockchain—we can envision reintroducing concepts of ancient Athenian democracy into the twenty-first century.55 CrowdJury56 looks to transform the justice system by putting several judicial processes online, using both crowdsourcing and the blockchain, including filing a charge or complaint, gathering and vetting of evidence, engaging citizens in open trials online and as online jurors, and issuing a verdict. Think transparent processes with crowdsourced discovery, crowdsourced analysis, and crowdsourced decision making and presto—you get an accurate outcome in a much shorter time frame and at vastly reduced cost. The process57 starts with the reporting online of a suspected civil or criminal wrongdoing (e.g., a public official suspected of receiving bribes) and inviting potential witnesses to provide evidence, and combining information from multiple sources.

“A wallet could be controlled by a piece of software that has no ownership and so you have the possibility of completely autonomous software agents that control their own money.”15 An autonomous agent could pay for its own Web hosting and use evolutionary algorithms to spread copies of itself by making small changes and then allowing those copies to survive. Each copy could contain new content that it discovers or even crowdsources somewhere on the Internet. As some of these copies become very successful, the agent could sell ads back to users, ad revenue could go into a bank account or posted on a secure place on the blockchain, and the agent could use this growing revenue to crowdsource more ad content and proliferate itself. The agent would repeat the cycle so that appealing content propagates and hosts itself successfully, and unsuccessful content basically dies because it runs out of money to host itself. DISTRIBUTED AUTONOMOUS ENTERPRISES We now suggest you buckle up in your Star Trek captain’s seat for a moment.

Interview with Eduardo Robles Elvira, September 10, 2015. 52. http://cointelegraph.com/news/111599/blockchain_technology_smart_contracts_and_p2p_law. 53. Patent Application of David Chaum, “Random Sample Elections,” June 19, 2014; http://patents.justia.com/patent/20140172517. 54. https://blog.ethereum.org/2014/08/21/introduction-futarchy/. 55. Federico Ast (@federicoast) and Alejandro Sewrjugin (@asewrjugin), “The CrowdJury, a Crowdsourced Justice System for the Collaboration Era,” https://medium.com/@federicoast/the-crowdjury-a-crowdsourced-court-system-for-the-collaboration-era-66da002750d8#.e8yynqipo. 56. http://crowdjury.org/en/. 57. The entire process is described in Ast and Sewrjugin, “The CrowdJury.” 58. A brief description of the jury selection process in early Athens is described at www.agathe.gr/democracy/the_jury.html. 59. See full report and recommendations here, including a description of models worldwide: www.judiciary.gov.uk/reviews/online-dispute-resolution/. 60. http://blog.counter-strike.net/index.php/overwatch/. 61.


pages: 344 words: 96,690

Groundswell: Winning in a World Transformed by Social Technologies by Charlene Li, Josh Bernoff

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business process, call centre, centre right, citizen journalism, crowdsourcing, demand response, Donald Trump, estate planning, Firefox, knowledge worker, Silicon Valley, skunkworks, Tony Hsieh

All the brand equity the bank had built up would ebb away, and worse, it would cease to tap into its customers’ innovations and go back to business as usual. a few words about crowdsourcing The Crédit Mutuel story is an example of crowdsourcing—asking the groundswell to provide you with ideas. Crowdsourcing is all the rage right now. It’s especially popular with advertising agencies, which are increasingly asking people to create television ads as part of some sort of contest.8 Frito-Lay’s Doritos ad in the 2007 Super Bowl was crowdsourced.9 It was pretty good, too. Crowdsourcing by itself is not the same as embracing your customers. Crowdsource an ad campaign, and you might save a few bucks on ad production—but you won’t have to do the hard work of changing the way you interact with customers. Salesforce.com has permanently changed how it innovates.

Salesforce.com has permanently changed how it innovates. Del Monte thinks very differently about creating new products now. And Crédit Mutuel, if it keeps going in the same direction, will be a very responsive bank in the future. On the other hand, Frito-Lay probably learned very little from crowdsourcing its Super Bowl Doritos commercial. It’s unlikely to turn over significant parts of its ad creation process to consumers on a regular basis. Its customers are not changing the company’s product development pipeline, supporting each other, or energizing each other in any sustainable way. Crowdsourced ads are a flash in the pan—they tap the groundswell for a moment, rather than move the company in a positive direction. CASE STUDY loblaw: reviews that drive continuous improvement Jim Osborne helped turn a grocery store and its store brand into a hotbed of innovation.

It received 148,000 “points,” which puts it at the top of the list of suggestions. 8. It’s especially popular with advertising agencies, which are increasingly asking people to create television ads as part of some sort of contest: The New York Times examined this phenomenon and noted that not only is crowdsourcing commercials sometimes an expensive proposition, but it also leads to expressions of the brand that the company might find less than ideal. See “The High Price of Creating Free Ads” by Louise Story, New York Times, May 26, 2007, visible at http://forr.com/gsw9-8. 9. Frito-Lay’s Doritos ad in the 2007 Super Bowl was crowdsourced: The Frito-Lay’s 2007 Super Bowl ad site is no longer visible. chapter 10 1. Fadra blogs and tweets about her experiences, especially as a mom. The blog “all.things.fadra” by Fadra Nally is visible at http://allthingsfadra.com.


pages: 286 words: 82,065

Curation Nation by Rosenbaum, Steven

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Amazon Mechanical Turk, Andrew Keen, barriers to entry, citizen journalism, cognitive dissonance, crowdsourcing, disintermediation, en.wikipedia.org, future of journalism, Jason Scott: textfiles.com, means of production, PageRank, pattern recognition, postindustrial economy, pre–internet, Sand Hill Road, Silicon Valley, Skype, social graph, social web, Steve Jobs, Tony Hsieh, Yogi Berra

No longer is the owner of the distribution system the king of the castle. Today, curation is king. CONTENT STRATEGISTS While the emerging curation ecosystem may leave the highbrow and pedigreed museum curation crowd with a furrowed brow, there’s another group who are equally troubled by the rise of human-powered finding and filtering—and that’s the code-centric solutions crowd that has been searching for the holy grail of machine-powered (or crowd-sourced) finding and filtering. This is the aggregation camp. And they too are anxious to see the emerging but noisy curation community replaced by elegant code. Blogger Clinton Forry has the most cogent distinction I’ve read so far: Aggregation is automated Aggregation collects content based on criteria in the form of metadata or keywords Criteria can be adjusted, but remain static otherwise Follows a preset frequency of publishing [as available, weekly, etc.]

Pepsi has taken seriously the change that Garfield is shouting from the rooftops. Bonin Bough, the director of digital and social media at PepsiCo explains, “If you listen to what people have to say and give voice to their perspectives, you can inspire people and empower their ideas.” This may not seem like the words of a soda and snack food company, but Pepsi is putting its brand and its money where its mouth is by pledging more than 20 million dollars to a crowd-sourced grant program, with public voting determining who gets the grants. Each month, Pepsi will award up to $1.3 million to the winning ideas across six categories: Health, Arts and Culture, Food and Shelter, The Planet, Neighborhoods, and Education. It’s a listening campaign that is meant to send a message to a new generation of connected consumers. Frank Cooper, Pepsi’s chief consumer engagement officer, explains the company’s social media initiatives this way: “We want to become a catalyst in the culture rather than act like a big brand announcing something.”

And we believe social media and digital engagement can fuel, extend, and inform these efforts.” And it appears that some of the companies that first were exposed to the power of consumer voice online and didn’t pay attention are drinking the Kool-Aid. Jarvis says Dell got the message, and years later Dell CEO Michael Dell told Jarvis, “No company can exist anymore on the idea that it’s just three people.” The era of the all-powerful CEO, CMO, and COO has been replaced by a crowd-sourced aggregation of suggestions, feedback, and complaints. TAKING CONTROL OF THE BRAND So what are the action items that this change from mass media to consumer-controlled conversations can offer? Well, there is a shift in how the buyers engage companies: no longer do they need to accept the “take it or leave it” attitude of many companies they do business with. Instead, they can say, “No, I think I’ll change it and take control of the brand.”


pages: 294 words: 80,084

Tomorrowland: Our Journey From Science Fiction to Science Fact by Steven Kotler

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Albert Einstein, autonomous vehicles, barriers to entry, Burning Man, carbon footprint, Colonization of Mars, crowdsourcing, Dean Kamen, epigenetics, gravity well, haute couture, interchangeable parts, Kevin Kelly, life extension, Louis Pasteur, North Sea oil, Oculus Rift, oil shale / tar sands, peak oil, personalized medicine, Peter H. Diamandis: Planetary Resources, RAND corporation, Ray Kurzweil, Richard Feynman, Richard Feynman, Ronald Reagan, self-driving car, stem cell, Stephen Hawking, Stewart Brand, theory of mind, Watson beat the top human players on Jeopardy!, Whole Earth Catalog, WikiLeaks

In the early 2000s, businesses started to realize that highly skilled jobs formerly performed in-house, by a single employee, could more efficiently be crowdsourced to a larger group via the Internet. Initially, offerings were simple. We crowdsourced the design of T-shirts (Threadless.com) and the writing of encyclopedias (Wikipedia.com), but it didn’t take long for the trend to start making inroads into the harder sciences. Pretty soon, the hunt for extraterrestrial life, the development of self-driving cars, and the folding of enzymes into new and novel proteins were being done this way. With the fundamental tools of genetic manipulation — tools that cost millions of dollars not ten years ago — dropping precipitously in price, the crowdsourced design of biological agents was just the next logical step. In 2008, casual DNA design competitions with small prizes arose; then, in 2011, with the launch of GE’s $100 million cancer challenge, the field moved onto serious contests.

A year later, before the invasion by Russian military, the state of Georgia saw a massive cyberattack paralyze their banking system and disrupt cell-phone networks. Iraqi insurgents subsequently repurposed Skygrabber — Russian software developed to steal satellite television and available for $29.95 — to intercept the video feeds of US predator drones, giving them the information needed to monitor and evade American military operations. Lately, organized crime has even taken up crowdsourcing, outsourcing areas of their illegal operations — printing up fake credit cards, money laundering, even murder — to those with greater expertise. With the anonymous nature of the online crowd, this development makes it all but impossible for law-enforcement to track these efforts. Added together, the historical data is clear: Whenever novel technologies enter the market, illegitimate uses quickly follow legitimate ones.

We are entering a world where imagination is the only brake on biology, where dedicated individuals can create new life from scratch. Today, when a difficult problem is mentioned, a commonly heard refrain is, “There’s an app for that.” Sooner than you might believe, “applications” will be replaced by synthetically created “organisms” — as in, “There’s an org for that” — when we think about the solutions to many of our problems. Crowdsourcing the protection of the presidential genome, in light of this coming revolution, may prove to be the only way to protect the president. And in the process, the rest of us. The God of Sperm THE CONTROVERSIAL FUTURE OF BIRTH Most of the innovators we’ve covered in these pages emerged from beyond the mainstream. Whether it’s Dezso Molnar and his flying motorcycle or William Dobelle and his artificial vision implant or Craig Venter and his synthetic genome — all three are much more maverick outsider than cozy insider.


pages: 525 words: 116,295

The New Digital Age: Transforming Nations, Businesses, and Our Lives by Eric Schmidt, Jared Cohen

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3D printing, access to a mobile phone, additive manufacturing, airport security, Amazon Mechanical Turk, Amazon Web Services, anti-communist, augmented reality, Ayatollah Khomeini, barriers to entry, bitcoin, borderless world, call centre, Chelsea Manning, citizen journalism, clean water, cloud computing, crowdsourcing, data acquisition, Dean Kamen, Elon Musk, failed state, fear of failure, Filter Bubble, Google Earth, Google Glasses, hive mind, income inequality, information trail, invention of the printing press, job automation, Julian Assange, Khan Academy, Kickstarter, knowledge economy, Law of Accelerating Returns, market fundamentalism, means of production, mobile money, mutually assured destruction, Naomi Klein, offshore financial centre, peer-to-peer lending, personalized medicine, Peter Singer: altruism, Ray Kurzweil, RFID, self-driving car, sentiment analysis, Silicon Valley, Skype, Snapchat, social graph, speech recognition, Steve Jobs, Steven Pinker, Stewart Brand, Stuxnet, The Wisdom of Crowds, upwardly mobile, Whole Earth Catalog, WikiLeaks, young professional, zero day

Through diligent crowd-sourced detective work, the perpetrator was soon tracked to a small town in northeastern China, and after her name, phone number and employer were made public, she fled, as did her cameraman. It’s not just computers that can find needles in haystacks, apparently; locating this woman among more than one billion Chinese—through only the clues in the video—took just six days. This kind of mob behavior can veer into unpredictable chaos, but that does not mean attempts to harness its collective power for good should be abandoned. Imagine if the end goal of the Chinese users was not to harass the kitten-stomper but to bring her to justice through official channels. In a conflict scenario, where institutions have broken down or are not trusted by the population, crowd-sourced energy will help to produce more comprehensive and accurate information, help track down wanted criminals and create demand for accountability even in the most difficult circumstances.

The introduction of mobile phones is far more transformative than most people in modern countries realize. As people come online, they will quite suddenly have access to almost all the world’s information in one place in their own language. This will even be true for an illiterate Maasai cattle herder in the Serengeti, whose native tongue, Maa, is not written—he’ll be able to verbally inquire about the day’s market prices and crowd-source the whereabouts of any nearby predators, receiving a spoken answer from his device in reply. Mobile phones will allow formerly isolated people to connect with others very far away and very different from themselves. On the economic front, they’ll find ways to use the new tools at their disposal to enlarge their businesses, make them more efficient and maximize their profits, as the fisherwomen did much more locally with their basic phones.

The more welcomed whistle-blowers of the future will be the ones who follow the example of people like Alexei Navalny, a Russian blogger and anticorruption activist, who enjoys much sympathy from many in the West. Disillusioned with Russia’s liberal opposition parties, Navalny, a real-estate lawyer, started his own blog dedicated to exposing corruption in major Russian companies, initially supplying the disclosures himself by taking small stakes in the businesses and invoking shareholder rights to force them to share information. He later crowd-sourced his approach, instructing supporters to try to do the same, with some success. Eventually, his blog grew into a full-blown secret-spilling platform, where visitors were encouraged to donate toward its operating costs via PayPal. Navalny’s profile grew as his collection of scoops swelled, most notably with a set of leaked documents that revealed the misuse of $4 billion at the state-owned oil pipeline company Transneft in 2010.


pages: 88 words: 22,980

One Way Forward: The Outsider's Guide to Fixing the Republic by Lawrence Lessig

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collapse of Lehman Brothers, crony capitalism, crowdsourcing, en.wikipedia.org, Filter Bubble, jimmy wales, Occupy movement, Ronald Reagan

Iceland had failed to insulate its government from cronyism and corruption. Both fueled irresponsible monetary and banking policy and, eventually, economic collapse. So the citizens of Iceland launched the most ambitious crowdsourced-sovereignty project in modern history. As a first step, a network of private grassroots organizations called the Anthill gathered a statistically significant portion of the nation to brainstorm a vision for the country. This “National Assembly” of more than fifteen hundred Icelandic citizens used open-source principles to “energize the wisdom of the population,” as it was promoted, and “to crowdsource a socio-economic political manifesto.”45 The idea, according to the assembly’s architect, was to “focus on the process. With a process it is something that can scale. It’s like how Linux competed with Windows. … The process … can scale so clever people all over the world can participate.”

As Wes Boyd recounted in an interview for this book, We got blank stares for years and years and years from most of the professional political people. They had no idea what this was about. … The pros, when we made the mistake of consulting them, would warn very very strongly, “Do not just send volunteers out to do this work.” But, of course, volunteers became the lifeblood of this new genre of political movement. They constituted the energy in “crowdsourced” politics, and they defined its power. MoveOn’s wave has repeated itself again and again in the decade or so since. Not just on the tech-enabled Left but also on the traditional Left (Obama) and then on the Right (the Tea Party), then on the Gen X/millennial Left (Occupy Wall Street), and now in the unaligned Internet (the Wikipedia-driven anti-SOPA/PIPA campaign). Each time, the pattern has been the same: A surprising and unpredicted “open-source” energy, enabled by cheap and ubiquitous technology, shows us a part of us, We, the People, that conventional politics had forgotten or thought lost.

. … The process … can scale so clever people all over the world can participate.” The National Assembly set the stage for the next extraordinary step of popular sovereignty. In June 2010, the Icelandic parliament passed the Act on a Constitutional Assembly, delegating the “intensely legalistic task” of writing a constitution to a group of citizens acting in a constitutional council. That council then convened a National Forum in November 2010, which “crowdsourced the norms and values of the population of 21st century Iceland,” through a series of questions and interviews. Then, building on the results from that survey and the work of the 2009 assembly, the forum divided citizens into groups focused upon particular themes. At the same time, the council initiated elections to a twenty-five-seat drafting commission, which would have ultimate responsibility for drafting a constitution.


pages: 465 words: 109,653

Free Ride by Robert Levine

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A Declaration of the Independence of Cyberspace, Anne Wojcicki, book scanning, borderless world, Buckminster Fuller, citizen journalism, correlation does not imply causation, crowdsourcing, death of newspapers, Edward Lloyd's coffeehouse, Firefox, future of journalism, Googley, Hacker Ethic, informal economy, Jaron Lanier, Julian Assange, Kevin Kelly, linear programming, offshore financial centre, pets.com, publish or perish, race to the bottom, Saturday Night Live, Silicon Valley, Silicon Valley startup, Skype, spectrum auction, Steve Jobs, Steven Levy, Stewart Brand, subscription business, Telecommunications Act of 1996, Whole Earth Catalog, WikiLeaks

The main idea behind much of this thinking is that there are other ways to create the kind of artistic work we enjoy now without laws to protect it, either by funding it in ways that don’t involve the media business or by using the reach of the Internet to harness volunteerism. Could art be “crowdsourced,” created by scattered people working together online, much as Wikipedia is? While online collaboration has intriguing possibilities, it seems to work better as a way of creating tools—like software or encyclopedias—rather than art. As ambitious as it is, Wikipedia depends on facts that can be sourced from other expensively produced publications, and experiments with crowdsourced original reporting have been underwhelming compared with professional work. A system based on these arrangements would also create a new generation of media gatekeepers. In the meantime, free culture advocates take any chance they get to argue that the media business can adjust to a world in which laws against illegal copying are not enforced.

Due to bad decisions that had nothing to do with technology, many newspaper chains were saddled with enormous debt run up by parent companies that overspent to buy publications and gain market share. And they faced a post-boomer generation of readers who have not picked up the habits of paying for news or reading it on a printed page. Conventional wisdom says that newspaper journalism must be reinvented for a changing world—blogged, Twittered, or somehow crowdsourced. It’s a tempting prescription—innovative, optimistic, and forward-looking—but it doesn’t get to the heart of the problem. Despite complaints about the media, newspaper journalism now reaches a larger audience than ever before, both directly and on various sites that summarize it. How dissatisfied can readers really be? The product isn’t the problem. Online publications that Twitter on a 24-7 schedule face the same difficulties, and even the inventive start-up Politico has said it makes most of its revenue on the print edition it distributes in Washington, D.C.14 At most online start-ups, any interest in journalistic innovation seems to come from the desire to cut costs, which is why more of them are experimenting with “citizen journalism” than, say, professionally shot video.

As the media executive and news business blogger Alan Mutter pointed out, U.S. newspapers now spend $4.4 billion a year on reporting, while nonprofit journalism institutions raised only $144 million over the last four.42 “The finding about that in general is that the content is great and the funding model is very unstable,” says Nicholas Lemann, dean of the Columbia University Graduate School of Journalism. “Then there are these experiments in crowdsourcing and other forms of social production, and my view is that they haven’t really delivered the goods.” Although nonprofit groups like the Knight Foundation have become enamored with citizen journalism projects, their track record has been uneven at best. A 2010 study by the Pew Research Center’s Project for Excellence in Journalism that examined the news “ecosystem” of Baltimore over the course of a week found that traditional media produced 95 percent of the stories with new information and that newspapers were responsible for most of them.43 (It also found that 80 percent of all stories contained no new information at all, which is damning for old and new media alike.)


pages: 371 words: 108,317

The Inevitable: Understanding the 12 Technological Forces That Will Shape Our Future by Kevin Kelly

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3D printing, A Declaration of the Independence of Cyberspace, AI winter, Airbnb, Albert Einstein, Amazon Web Services, augmented reality, bank run, barriers to entry, Baxter: Rethink Robotics, bitcoin, blockchain, book scanning, Brewster Kahle, Burning Man, cloud computing, computer age, connected car, crowdsourcing, dark matter, dematerialisation, Downton Abbey, Edward Snowden, Elon Musk, Filter Bubble, Freestyle chess, game design, Google Glasses, hive mind, Howard Rheingold, index card, indoor plumbing, industrial robot, Internet Archive, Internet of things, invention of movable type, invisible hand, Jaron Lanier, Jeff Bezos, job automation, Kevin Kelly, Kickstarter, linked data, Lyft, M-Pesa, Marshall McLuhan, means of production, megacity, Minecraft, multi-sided market, natural language processing, Netflix Prize, Network effects, new economy, Nicholas Carr, peer-to-peer lending, personalized medicine, placebo effect, planetary scale, postindustrial economy, recommendation engine, RFID, ride hailing / ride sharing, Rodney Brooks, self-driving car, sharing economy, Silicon Valley, slashdot, Snapchat, social graph, social web, software is eating the world, speech recognition, Stephen Hawking, Steven Levy, Ted Nelson, the scientific method, transport as a service, two-sided market, Uber for X, Watson beat the top human players on Jeopardy!, Whole Earth Review

As of 2015, these two largest peer-to-peer lending companies have facilitated more than 200,000 loans worth more than $10 billion. Innovation itself can be crowdsourced. The Fortune 500 company General Electric was concerned that its own engineers could not keep up with the rapid pace of invention around them, so it launched the platform Quirky. Anyone could submit online an idea for a great new GE product. Once a week, the GE staff voted on the best idea that week and would set to work making it real. If an idea became a product, it would earn money for the idea maker. To date GE has launched over 400 new products from this crowdsourced method. One example is the Egg Minder, an egg holder in your refrigerator that sends you a text when it’s time to reorder your eggs. Another popular version of crowdsourcing appears, at first, to be less about collaboration and more about competition.

A couple platforms (Flattr, Unglue) use fans to fund work that has already been released. But by far the most potent future role for crowdsharing is in fan base equity. Rather than invest into a product, supporters invest into a company. The idea is to allow fans of a company to purchase shares in the company. This is exactly what you do when you buy shares of stock on the stock market. You are part of a crowdsourced ownership. Each of your shares is some tiny fraction of the whole enterprise, and the collected money raised by public shares is used to grow the business. Ideally, the company is raising money from its own customers, although in reality big pension and hedge funds are the bulk buyers. Heavy regulation and intense government oversight of public companies offer some guarantee to the average stock buyer, making it so anyone with a bank account can buy stock.

No matter how many times the picture may be recopied, the credit comes back to me. Compared with last century, it’s really easy to make, say, an instructional video now because you can assemble the available parts (images, scenes, even layouts) from other excellent creators, and the micropayments for their work automatically flow back to them as a default. The electric car we are making will be crowdsourced, but unlike decades earlier, every engineer who contributes to the car, no matter how small her contribution, gets paid proportionally. I have a choice of 10,000 different co-ops I can contribute to. (Not many of my generation want to work for a corporation.) They offer different rates, varying benefits, but, most important, different sets of coworkers. I try to give my favorite co-ops a lot of time not because they pay more, but because I really enjoy working with the best folks—even though we’ve never met in real life.


pages: 167 words: 50,652

Alternatives to Capitalism by Robin Hahnel, Erik Olin Wright

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3D printing, affirmative action, crowdsourcing, inventory management, iterative process, Kickstarter, loose coupling, means of production, profit maximization, race to the bottom, transaction costs

But there is also a practical problem with Erik’s suggestions about risk and innovation when applied in the context of a participatory economy. Even if those who received start-up funds from crowd-sourcing agreed that the enterprise would be run according to participatory economic principles, and even if investors received no return on their investment, the new enterprise would have to obtain the inputs it needs to operate through the participatory planning procedure. And it can’t do this without being certified as “credible.” A worker council can’t buy its inputs with funds raised through crowd-sourcing in a participatory economy. I think, instead, what is needed are multiple ways for groups who want to start up new enterprises to demonstrate their credibility so they can participate in the planning procedure. If a group comes with an impressive display of crowdsourcing support, this can demonstrate credibility. If members of the group have relevant educational credentials, this can demonstrate credibility.

Is there good reason to believe that the optimal system would allow no investments outside of the decision-making processes of councils and federations? Consider the following example: Suppose a group of people have an idea for some new product but they cannot convince the relevant council or federation to provide them the needed capital equipment and raw materials to produce it. There is just too much skepticism about the viability of the project. An alternative way of funding the project could be through a form of crowdsourcing finance along the lines of Kickstarter. The workers involved would post a description of the project online and explain their specific needs for material inputs. They appeal to people (in their role of consumers) to allocate part of their annual consumption allowances to the project. Consumers might decide, for example, to put in extra hours at work in order to acquire the extra funds needed for their contribution, or they might just decide to consume less of some discretionary part of their consumption bundle.

This would, in effect, be simply a long-term pre-order of the product, although operating outside of the mechanism of the IFB. But potential contributors to the project might also only be interested in contributing if they got a positive return on their “investment”. This would look much closer to market investment. The question, then, is should such practices be prohibited in a participatory economy? Especially if a positive return on crowd-sourced investments is allowed, these projects would constitute a kind of quasi-market niche in the participatory economy. Robin argues that new worker councils should be prohibited from raising capital outside of the planning process. Here is what he says about new startup worker councils: In a participatory economy new worker councils bid for the resources they need to get started in the participatory planning process.


pages: 186 words: 49,595

Revolution in the Age of Social Media: The Egyptian Popular Insurrection and the Internet by Linda Herrera

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citizen journalism, crowdsourcing, Google Earth, informal economy, Julian Assange, knowledge economy, minimum wage unemployment, Mohammed Bouazizi, Occupy movement, RAND corporation, Rosa Parks, Silicon Valley, Skype, Slavoj Žižek, WikiLeaks

Unlike the homegrown skits that went viral as people voluntarily passed them from phone to phone, the pro-US messages generally traveled unidirectionally from the embassy to the targeted phone. There were also attempts to penetrate the most popular online chat rooms of young Arabs, but this proved far more difficult due to the atomized and interactive nature of chat rooms. Chat rooms, like social media after it, do not lend themselves to packaged, top-down messaging in the style of traditional media, but rely on people-to-people crowdsourcing. Christopher Ross, Special Coordinator for Public Diplomacy at the State Department, describes the difficulty of working in chat rooms: There are many, many chat rooms in which the Middle East, and U.S. policy towards the Middle East, are openly discussed. Many of their participants are from the Middle East. We are not present. And the difficulty is that to be present is very labor-intensive.

Step 4 of the AYM manual urges: Use the press: Figure out your outreach strategy: The more people hear your message, the more influential you’ll be. Contact the media—print, radio, television, online—whenever possible to tell your story. If a sympathetic foreign dignitary or organization happens to visit, try to meet with them, or organize a protest to coincide with their arrival, which can get you some international press attention. Through crowdsourcing, the page started formulating its media plan as early as June 14, four days into the launch. The admin wrote: Hey everyone, tonight our plan is for all of us to call the talk shows. Please, can people send us the telephone numbers so we can use these in our [media] plan? We want you to find the numbers of all the talk shows in Egypt. He would soon mobilize members to help him build a more comprehensive database of bloggers, journalists, and television personalities with reach in Egypt, the region, and internationally.

The goal was to create an “internet government” by the people to monitor security forces and police at three main sites: checkpoints in the streets, police stations, and public universities. The plan was to create a Twitter hashtag that any citizen with an internet connection could use to tweet and report their encounter with the police, whether good or bad. The admins of the site would use a crowdsourcing mapping application to monitor where high numbers of violations were taking place. Police stations that respected people and the law would be rewarded with good ratings, whereas the abusers would be publicized and subject to citizen action. As plans were underway for Police Watch, the Khaled Said incident took place and diverted his energies. Mansour recalls: I was very affected by Khaled Said.


pages: 239 words: 56,531

The Secret War Between Downloading and Uploading: Tales of the Computer as Culture Machine by Peter Lunenfeld

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Albert Einstein, Andrew Keen, Apple II, Berlin Wall, British Empire, Brownian motion, Buckminster Fuller, Burning Man, butterfly effect, computer age, crowdsourcing, cuban missile crisis, Dissolution of the Soviet Union, don't be evil, Douglas Engelbart, Dynabook, East Village, Edward Lorenz: Chaos theory, Fall of the Berlin Wall, Francis Fukuyama: the end of history, Frank Gehry, Grace Hopper, gravity well, Guggenheim Bilbao, Honoré de Balzac, Howard Rheingold, invention of movable type, Isaac Newton, Jacquard loom, Jacquard loom, Jane Jacobs, Jeff Bezos, John von Neumann, Mark Zuckerberg, Marshall McLuhan, Mercator projection, Mother of all demos, mutually assured destruction, Network effects, new economy, Norbert Wiener, PageRank, pattern recognition, planetary scale, Plutocrats, plutocrats, Post-materialism, post-materialism, Potemkin village, RFID, Richard Feynman, Richard Feynman, Richard Stallman, Robert X Cringely, Schrödinger's Cat, Search for Extraterrestrial Intelligence, SETI@home, Silicon Valley, Skype, social software, spaced repetition, Steve Ballmer, Steve Jobs, Steve Wozniak, Ted Nelson, the built environment, The Death and Life of Great American Cities, the medium is the message, Thomas L Friedman, Turing machine, Turing test, urban planning, urban renewal, Vannevar Bush, walkable city, Watson beat the top human players on Jeopardy!, William Shockley: the traitorous eight

I am indebted to Lessig’s work of over a decade defining, defending, and promoting Creative Commons, open-source culture, and the remix economy: Remix: Making Art and Commerce Thrive in the Hybrid Economy (New York: Penguin Press, 2008); Code v2 and Other Laws of Cyberspace (New York: Basic Books, 2007); Free Culture: How Big Media Uses Technology and the Law to Lock Down Creativity (New York: Penguin Press, 2004); The Future of Ideas: The Fate of the Commons in a Connected World (New York: Random House, 2001); Code and Other Laws of Cyberspace (New York: Basic Books, 1999). 13 . Formerly at <http://www.jennyeverywhere.com>; now available at <http://theshifterarchive.com>. 14 . This neologism is credited to journalist Jeff Howe in his article “The Rise of Crowdsourcing” Wired 14.06 (June 2006): 176–183. <http://www.wired.com/ wired/archive/14.06/crowds.html>. See his book, Crowdsourcing: Why the Power of the Crowd Is Driving the Future of Business (New York: Crown Business, 2008) and blog, http://crowdsourcing.typepad.com/. His “white paper” version of the definition of crowdsourcing specifically foregrounds the economic relationships: “Crowdsourcing is the act of taking a job traditionally performed by a designated agent (usually an employee) and outsourcing it to an undefined, generally large group of people in the form of an open call.” 15 . James Joyce, Ulysses (1922; repr., Oxford: Oxford University Press, 1998), 182. 16 .

According to the Web site where she was born and lives her (many) lives: “The character of Jenny Everywhere is available for use by anyone, with only one condition. This paragraph must be included in any publication involving Jenny Everywhere, in order that others may use this property as they wish. All rights reversed.”13 The openendedness, the unfinish of Jenny Everywhere, distinguishes it from the similar neologism “crowdsourcing.” Crowdsourcing is also about the deployment of multiple, online “eyeballs,” but the concept’s link to the “outsourcing” of globalization ties it tightly to the economic realm.14 Imagination, on the other hand, encompasses but is not limited to those projects that can be monetized, so it is less “problem solving” than “situation enabling” that is needed. The Creative Commons movement is trying to ensure that those who want to “write” with the culture machine—by this, I mean make and distribute motion pieces, new music, filmic fictions, digitally modeled fabrications, ubiquitous information environments, photo blogs, and the list goes on—will be able to have access to the contemporary raw materials of creativity.


pages: 411 words: 80,925

What's Mine Is Yours: How Collaborative Consumption Is Changing the Way We Live by Rachel Botsman, Roo Rogers

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Airbnb, barriers to entry, Bernie Madoff, bike sharing scheme, Buckminster Fuller, carbon footprint, Cass Sunstein, collaborative consumption, collaborative economy, Community Supported Agriculture, credit crunch, crowdsourcing, dematerialisation, disintermediation, en.wikipedia.org, experimental economics, George Akerlof, global village, Hugh Fearnley-Whittingstall, information retrieval, iterative process, Kevin Kelly, Kickstarter, late fees, Mark Zuckerberg, market design, Menlo Park, Network effects, new economy, new new economy, out of africa, Parkinson's law, peer-to-peer lending, Ponzi scheme, pre–internet, recommendation engine, RFID, Richard Stallman, ride hailing / ride sharing, Robert Shiller, Robert Shiller, Ronald Coase, Search for Extraterrestrial Intelligence, SETI@home, Simon Kuznets, Skype, slashdot, smart grid, South of Market, San Francisco, Stewart Brand, The Nature of the Firm, The Spirit Level, The Wealth of Nations by Adam Smith, The Wisdom of Crowds, Thorstein Veblen, Torches of Freedom, transaction costs, traveling salesman, ultimatum game, Victor Gruen, web of trust, women in the workforce, Zipcar

The collective power of physically dispersed yet virtually connected individuals only became stronger and more apparent through the 2000s. Crowdsourcing, a concept coined by Jeff Howe as the “act of taking a job traditionally performed by a designated agent (usually an employee) and outsourcing it to an undefined, generally large group of people in the form of an open call,” became an important business idea. It is now a well-documented phenomenon applied to the creation of collective repositories of content (Wikipedia), products (the T-shirt company Threadless, where all the designs are created by the user community), new business ideas (Procter & Gamble’s Connect & Develop), and even problems such as climate change (MIT’s Climate Collaboratorium). What the success of crowdsourcing has shown is that as people move from hyper-individualistic consumer behaviors, a “me mind-set,” to a “we mind-set,” an empowering dynamic emerges.

More than 2.5 million people around the world respond to some kind of Meetup invitation every month and more than two thousand local groups, from stay-at-home moms to small business owners to walking clubs, get together face-to-face each day.42 “We are using the Internet to get off the Internet and form a twenty-first-century civil society,” Heiferman commented.43 In 2006, a couple of years after leaving BBH, Gallop found herself thinking, “How could I take all the good intentions most of us have on a daily basis, our single biggest pool of untapped natural resource, and transform them into shared actions?” Like Chris Hughes on Obama’s campaign, Gallop also knew she had to make her initiative fun and avoid the “yawn factor” by adding a healthy dose of what she refers to as “competitive collaboration.” She launched IfWeRanTheWorld.com early in 2010. It’s essentially a crowdsourcing project based on the similar principles of microfunding sites such as Kiva or Kickstarter. People are motivated to do big things by taking all easy steps, microactions that in Gallop’s words “can bring about great leaps.” When you arrive at the site, you are asked to complete the statement, “If I ran the world, I would___.” Gallop illustrates how it works with a simple example. “The blank would be filled with something like ‘plant a garden to feed the local homeless.’ ” On the IfWeRanTheWorld platform, the user and the community all help break down the goal into microactions that friends, family, neighbors, businesses, celebrities, or total strangers can all help complete.

There will be an explosion in services that enable you to repair, upgrade, and customize owned or secondhand products. Instead of automatically paying with cash for many products and services, we will offer to barter talents, skills, and ideas, and virtual social currencies will have become a normal way to exchange. The consumer preference for handmade or locally produced goods will become the norm. Neighborhood networks such as EveryBlock or NeighborGoods will explode and enable local crowdsourcing between residents on creative and social projects. There will be a whole ecosystem of apps and software for our phones and computers that will enable us to share any kind of product or service. A collaborative and sharing culture will be the culture. We believe we will look back and see this epoch as a time when we took a leap and re-created a sustainable system built to serve basic human needs—in particular, the needs for community, individual identity, recognition, and meaningful activity—rooted in age-old market principles and collaborative behaviors.


pages: 366 words: 94,209

Throwing Rocks at the Google Bus: How Growth Became the Enemy of Prosperity by Douglas Rushkoff

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3D printing, Airbnb, algorithmic trading, Amazon Mechanical Turk, Andrew Keen, bank run, banking crisis, barriers to entry, bitcoin, blockchain, Burning Man, business process, buy low sell high, California gold rush, Capital in the Twenty-First Century by Thomas Piketty, carbon footprint, centralized clearinghouse, citizen journalism, clean water, cloud computing, collaborative economy, collective bargaining, colonial exploitation, Community Supported Agriculture, corporate personhood, crowdsourcing, cryptocurrency, disintermediation, diversified portfolio, Elon Musk, Erik Brynjolfsson, ethereum blockchain, fiat currency, Firefox, Flash crash, full employment, future of work, gig economy, Gini coefficient, global supply chain, global village, Google bus, Howard Rheingold, IBM and the Holocaust, impulse control, income inequality, index fund, iterative process, Jaron Lanier, Jeff Bezos, jimmy wales, job automation, Joseph Schumpeter, Kickstarter, loss aversion, Lyft, Mark Zuckerberg, market bubble, market fundamentalism, Marshall McLuhan, means of production, medical bankruptcy, minimum viable product, Naomi Klein, Network effects, new economy, Norbert Wiener, Oculus Rift, passive investing, payday loans, peer-to-peer lending, Peter Thiel, post-industrial society, profit motive, quantitative easing, race to the bottom, recommendation engine, reserve currency, RFID, Richard Stallman, ride hailing / ride sharing, Ronald Reagan, Satoshi Nakamoto, Second Machine Age, shareholder value, sharing economy, Silicon Valley, Snapchat, social graph, software patent, Steve Jobs, TaskRabbit, trade route, transportation-network company, Turing test, Uber and Lyft, Uber for X, unpaid internship, Y Combinator, young professional, Zipcar

.* Just as Wikipedia marshaled the talents of thousands of individual people working online to create an encyclopedia, corporations are beginning to use what are called crowdsourcing platforms to engage online workers in a multitude of freelance tasks. Again, such opportunities are touted by their proponents as part of the digital revolution. The CEO of the CrowdFlower crowdsourcing platform, Lukas Biewald, explains that these platforms are “bringing opportunities to people who never would have had them before, and we operate in a truly egalitarian fashion, where anyone who wants to can do microtasks, no matter their gender, nationality, or socio-economic status, and can do so in a way that is entirely of their choosing and unique to them.”40 Crowdsourcing platforms, such as Amazon Mechanical Turk, pay people to perform tiny, repetitive tasks that computers just can’t handle yet.

The worker is not eliminated; he’s just invisible. For employers, it’s a perfect realization of the industrial ideal: anyone can request work, do so anonymously, never meet the employee, and reject the results without ever paying. The labor force isn’t simply replaceable; it’s in constant flux, perpetually changing and responsible for its own training and care. As digital labor scholar and activist Trebor Scholz has pointed out,41 in crowdsourcing there’s no minimum wage, no labor regulation, no governmental jurisdiction. Although 18 percent of workers on Amazon Mechanical Turks are full-time laborers, most of them make less than two dollars an hour. Amazon argues that the platform is all about choice and empowerment, that workers can “vote with their feet” against bad labor practices. But when even minimum-wage jobs aren’t available to many workers today, they are empowered to make only one choice or none at all.

No cash is risked, because the backers don’t pay until the total amount sought has been raised. The only risk is that the project is never completed, but the open market seems pretty good at evaluating competence: 98 percent of projects that meet just 60 percent of their funding goals are fully completed. Startups funded by venture capital do about the reverse, with more than 90 percent of fully funded enterprises failing.59 The same crowdsourcing dynamics that Upwork or 99designs* use to shift risk onto freelancers can also shift risk off the table altogether. The less risk, the less money is owed to the risk taker. So, used appropriately, the net disintermediates the funder, eliminates the need to abandon ongoing productivity in favor of a quick exit, spares the marketplace from having to pay back investors, keeps cash in circulation instead of being extracted, and gives regular people the opportunity to put their money toward what they want to see happen.


pages: 527 words: 147,690

Terms of Service: Social Media and the Price of Constant Connection by Jacob Silverman

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23andMe, 4chan, A Declaration of the Independence of Cyberspace, Airbnb, airport security, Amazon Mechanical Turk, augmented reality, Brian Krebs, California gold rush, call centre, cloud computing, cognitive dissonance, correlation does not imply causation, Credit Default Swap, crowdsourcing, don't be evil, Edward Snowden, feminist movement, Filter Bubble, Firefox, Flash crash, game design, global village, Google Chrome, Google Glasses, hive mind, income inequality, informal economy, information retrieval, Internet of things, Jaron Lanier, jimmy wales, Kevin Kelly, Kickstarter, knowledge economy, knowledge worker, late capitalism, license plate recognition, life extension, Lyft, Mark Zuckerberg, Mars Rover, Marshall McLuhan, meta analysis, meta-analysis, Minecraft, move fast and break things, national security letter, Network effects, new economy, Nicholas Carr, Occupy movement, optical character recognition, payday loans, Peter Thiel, postindustrial economy, prediction markets, pre–internet, price discrimination, price stability, profit motive, quantitative hedge fund, race to the bottom, Ray Kurzweil, recommendation engine, rent control, RFID, ride hailing / ride sharing, self-driving car, sentiment analysis, shareholder value, sharing economy, Silicon Valley, Silicon Valley ideology, Snapchat, social graph, social web, sorting algorithm, Steve Ballmer, Steve Jobs, Steven Levy, TaskRabbit, technoutopianism, telemarketer, transportation-network company, Turing test, Uber and Lyft, Uber for X, universal basic income, unpaid internship, women in the workforce, Y Combinator, Zipcar

June 19, 2012. peasantmuse.com/2012/06/from-data-self-to-data-serf.html. 260 “This digital labor”: Scholz, “Why Does Digital Labor Matter Now?,”2. 260 “the micro-division of labor”: Andrew Ross. “In Search of the Lost Paycheck.” In Digital Labor: The Internet as Playground and Factory. Trebor Scholz, ed. New York: Routledge, 2013, 20. 260 Apps similar to Twitch: Rachel Metz. “The Next Frontier in Crowdsourcing: Your Smartphone.” MIT Technology Review. March 12, 2014. technologyreview.com/news/525481/thenext-frontier-in-crowdsourcing-your-smartphone. 262 Wall Street Journal praise for BuzzFeed: Farhad Manjoo. “BuzzFeed’s Brazen, Nutty, Growth Plan.” Wall Street Journal. Oct. 14, 2013. wsj.com/article/SB10001424052702304500404579129590411867328.html. 262 “digital volunteers”: Curt Hopkins. “The Smithsonian Is Outsourcing Transcription . . . to You.” Daily Dot.

(Sometimes rival networks fight back, as when Facebook bought Instagram—which was immensely popular with Twitter users—and later disabled the ability for Instagram photos to appear in the Twitter timeline and some Twitter apps.) Facebook has achieved a similar effect by encouraging third-party sites, from online magazines to Spotify, to use its Facebook Connect tool for user log-ins and, in the case of crowdsourced service sites such as Airbnb, as a kind of ersatz background check. Your Facebook identity becomes the proof of who you are and your reliability. This may make it more difficult for non-Facebook users to access these services, but it also means that instead of having to sign up for an account to read Foreign Policy or use the Tinder dating app, a Facebook member can just join through his or her Facebook account.

Even so, companies remain extraordinarily reliant on these reviews. A 2011 Harvard Business School study found that, on Yelp, “an extra star is worth an extra 5 to 9 percent in revenue.” The result of all this reviewing has been the atrophying of the critical culture, with professional critics seen as dispensable, nothing more than recommendation engines who can be replaced with algorithms and free, crowdsourced reviews. (Even so, some prominent cultural critics remain, though with less influence than they used to hold, and a smattering of publications, from the actuarially precise Consumer Reports to the liberal humanist New York Review of Books, continue to thrive.) It’s also expanded the idea of what should be reviewed, with everything now potentially susceptible to, if not a star rating, then the kind of up-or-down judgment we perform all the time when we choose to like things.


pages: 212 words: 49,544

WikiLeaks and the Age of Transparency by Micah L. Sifry

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1960s counterculture, Amazon Web Services, banking crisis, barriers to entry, Bernie Sanders, Buckminster Fuller, Chelsea Manning, citizen journalism, Climategate, crowdsourcing, Google Earth, Howard Rheingold, Internet Archive, Jacob Appelbaum, Julian Assange, Network effects, RAND corporation, school vouchers, Skype, social web, Stewart Brand, web application, WikiLeaks

Chapter 6 1 President Barack Obama, “Transparency and Open Government,” January 21, 2009, www.whitehouse.gov/the_press_office/Transparency andOpenGovernment. 2 President Barack Obama, “Freedom of Information Act,” January 21, 2009, www.whitehouse.gov/the_press_office/FreedomofInformationAct. 3 William Branigin, “Democrats Take Majority in House; Pelosi Poised to Become Speaker,” The Washington Post, November 8, 2006, www.washingtonpost.com/wp-dyn/content/article/2006/11/07/ AR2006110700473.html. 4 A full list of participants in the Open House Project can be found here: www.theopenhouseproject.com/press/launch. 5 John Wonderlich, “Open House Project Retrospective,” The Open House Project, October 14, 2008, www.theopenhouseproject.com/2008/10/14/ open-house-project-retrospective. It’s also worth noting that press credentialing for citizen journalists and bulk access to congressional floor and committee video were two recommendations that the project made the least progress on. 6 Micah L. Sifry, “Obama as Crowdsourcer; Organizing the Country for Change and Accountability,” techPresident.com, February 8, 2009, http://techpresident.com/blog-entry/obama-crowdsourcer-organizingcountry-change-and-accountability. 7 Clint Hendler, “Obama on Recovery.gov,” Columbia Journalism Review, February 9, 2009, www.cjr.org/the_kicker/obama_on_recoverygov.php. 8 Edward Luce and Tom Braithwaite, “US stimulus tsar to unleash 1m inspector-generals,” The Financial Times, August 20, 2009, www.ft.com/ cms/s/0/e731fd52-8db0-11de-93df-00144feabdc0.html#axzz1 AZfFLMQT. 9 Earl Devaney, “Chairman’s Corner,” Recovery.gov, March 22, 2010, www. recovery.gov/News/chairman/Pages/march222010.aspx. 10 Clay Johnson, “Recovery.gov: Stop with the Data Defense, Start with the Conversation,” March 30, 2010, http://sunlightlabs.com/blog/2010/ recoverygov-stop-data-defense-start-conversation. 11 Earl Devaney, “Chairman’s Corner,” Recovery.gov, October 27, 2010, www.recovery.gov/News/chairman/Pages/2010Oct27.aspx 197 WIKILEAKS AND THE AGE OF TRANSPARENCY 12 13 14 15 16 17 18 19 20 21 22 23 198 Becky Hogge, “Open Data Study,” Open Society Foundations Information Program, May 2010, www.soros.org/initiatives/information/focus/ communication/ar ticles_publications/publications/open-datastudy-20100519.

Eric Raymond, one of the earliest evangelists for the open source software movement, famously wrote that the ethos of the first developer of Linux, Linus Torvalds, was “given enough eyeballs, all bugs are shallow.”11 In technical terms, this means that if you have enough early testers of your software, and you make the source code visible, the community as a whole can easily help spot problems and help solve them. The same notion has come to apply, again and again, to the transparency movement. If you make a problem visible, or put it out on the web in a form that lots of people can swarm around, often 75 WIKILEAKS AND THE AGE OF TRANSPARENCY a solution will be found. “Crowdsourcing” is the term often used to describe this process, though I think it’s somewhat of a misnomer. We aren’t outsourcing a job that used to belong to professionals (such as investigative journalists) and giving it to a crowd to do; we’re inviting lots of civic watchdogs to add their eyeballs and time to the process of making government more transparent and accountable. Call it crowd-scouring instead.

But we still won’t know what members of Congress are doing when they meet with lobbyists, nor will we know anything but the roughest range of their personal financial holdings in companies whose business they may oversee. Transparency and participatory politics has run through a similarly checkered path in the United Kingdom in recent years. For a time, it appeared that the U.K.’s Labour government was inching close to embracing a much more people-driven vision of open government, akin to Obama’s “eyes and ears” notion of crowd-sourcing. First, in early 2007, the prime minister’s office (then under Tony Blair) hired mySociety.org to build a tool enabling the public to create and sign petitions to his office directly from the 10 Downing Street website.23 Millions of citizens swarmed in, and some of the top petitions forced the government to make actual policy changes, like dropping plans for a new vehicle tax. Tom Steinberg of mySociety was then asked to coauthor a study along with Ed Mayo, the head of the National Consumer Council, on the “power of information” to foster new kinds of citizen-to-citizen information sharing and collaboration.


pages: 184 words: 53,625

Future Perfect: The Case for Progress in a Networked Age by Steven Johnson

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airport security, algorithmic trading, banking crisis, barriers to entry, Bernie Sanders, call centre, Captain Sullenberger Hudson, Cass Sunstein, cognitive dissonance, credit crunch, crowdsourcing, dark matter, Dava Sobel, David Brooks, future of journalism, hive mind, Howard Rheingold, HyperCard, Jane Jacobs, John Gruber, John Harrison: Longitude, Kevin Kelly, Kickstarter, lone genius, Mark Zuckerberg, meta analysis, meta-analysis, Naomi Klein, Nate Silver, Occupy movement, packet switching, Peter Thiel, planetary scale, pre–internet, RAND corporation, risk tolerance, shareholder value, Silicon Valley, Silicon Valley startup, social graph, Steve Jobs, Steven Pinker, Stewart Brand, The Death and Life of Great American Cities, Tim Cook: Apple, urban planning, WikiLeaks, working poor, X Prize

The figure of some $1.5 billion passing through crowdfunding sites in 2011 is from Forbes, http://www.forbes.com/sites/suwcharmananderson/2012/05/11/crowdfunding-raised-1-5bn-in-2011-set-to-double-in-2012/. II. PEER NETWORKS AT WORK Communities. The Maple Syrup Event For more on 311 and other urban technology platforms, see my essay “What a Hundred Million Calls to 311 Reveal About New York,” in the November 2010 issue of Wired, and Vanessa Quirk’s essay “Can You Crowdsource a City?” (http://www.archdaily.com/233194/can-you-crowdsource-a-city/). A number of sites and mobile apps are innovating in the area of peer-network urbanism; an overview of many of them is available at the DIY City website, http://diycity.org/. Chris Anderson’s “Vanishing Point theory of news” was originally published at http://www.longtail.com/the_long_tail/2007/01/the_vanishing_p.html. Journalism. The Pothole Paradox For more on the debate over the future of journalism, see my discussion with Paul Starr published in Prospect, “Are We on Track for a Golden Age of Serious Journalism?”

Systems based on pure information are clearly more amenable to the experimentation, decentralization, and diversity of peer networks than more material realms are. It’s harder to get those kinds of groups to gather in a barn or a city hall than it is to assemble them virtually. Moving bits around is far easier than doing the—sometimes literal—heavy lifting of civic life: building reservoirs or highways or jet engines that don’t explode when birds fly into them. A skeptic might plausibly say, Sure, if you want to conduct an online poll, or crowdsource a city slogan, the Internet is a great leap forward. But if you want to do the real work, you need the older tools. But every material advance in human history—from the Great Wall to the Hoover Dam to the polio vaccine to the iPad—was ultimately the by-product of information transfer and decision making. This is how progress happens: some problem or unmet need is identified, imaginative new solutions are proposed, and eventually society decides to implement one (or more) of those solutions.

A New York–based site called UncivilServants collects reports and photos of government workers abusing parking rules around the city and ranks the top offenders by department. (The worst abuser, by a wide margin, is the NYPD.) There’s even a new Australian urban reporting site called, memorably, It’s Buggered Mate. Taken together, all this adaptive, flexible urban reporting points the way toward a larger, and potentially revolutionary, development: the crowdsourced metropolis, the city of quants. — Systems such as 311 and its ilk are the peer-progressive response to the problem that all great cities invariably confront: the problem of figuring out where the problems are. In the language of Seeing Like a State, 311 makes the city legible from below. It doesn’t set its priorities from above; it doesn’t get bound up in official definitions or categories.


pages: 209 words: 63,649

The Purpose Economy: How Your Desire for Impact, Personal Growth and Community Is Changing the World by Aaron Hurst

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3D printing, Airbnb, Atul Gawande, barriers to entry, big-box store, business process, call centre, carbon footprint, citizen journalism, corporate social responsibility, crowdsourcing, disintermediation, Elon Musk, Firefox, glass ceiling, greed is good, housing crisis, informal economy, Jane Jacobs, jimmy wales, Khan Academy, Kickstarter, Lean Startup, means of production, new economy, pattern recognition, Peter Singer: altruism, Peter Thiel, Ray Oldenburg, remote working, Richard Feynman, Ronald Reagan, sharing economy, Silicon Valley, Silicon Valley startup, Steve Jobs, TaskRabbit, Tony Hsieh, too big to fail, underbanked, women in the workforce, young professional, Zipcar

Five Levers in Action: Nine Mini-Case Studies You can find these levers in action across industries and sectors. While Taproot used all five, different organizations moved markets by using different levers. 1. Mosaic: Solar Energy Mosaic, an online portal for solar energy investment and crowdsourced finance, utilized disruptive energy and financing sector technologies to address the public perception of solar’s high investment costs. Publicly subsidizing solar investments has been tricky from a policy perspective, but Mosaic’s decision to crowdsource its financing and “green” investment was not only a clever marketing tool, but another way to challenge perceptions of the business viability of solar energy. To date, $5.6 million has been invested through the Mosaic platform. 2. OMEGA: Biofuels The OMEGA (Offshore Membrane Enclosures for Growing Algae) Project used new research and data by scientists and engineers to create a disruptive technology in the form of algae.

While this worked as a controlled pilot project, the next step is to understand the commercial viability of offshore OMEGA systems for a variety of uses, including biofuels production, wastewater treatment, and carbon sequestration. 3. Kickstarter: Crowdsourced Investment Kickstarter, an online platform for crowdfunding independent creative projects, launched in 2009 using secure online fundraising platforms (itself a recent disruptive technology). The platform recognized and filled a gap for creative entrepreneurs, designers, and other freelancers wanting to maintain creative control over their projects. The founders like to highlight this process as being rooted in the time of Mozart or Mark Twain, who solicited money from their communities and gave that community one of their finished products. Even so, Kickstarter’s inventive use of technology to harness the power of the creative community has enabled a crowd-sourced $789 million for 53,672 different projects, and in the process, Kickstarter has become one of the most influential bright spots in and beyond the tech world. 4.

LinkedIn, then, was part of this second wave, as it evolved past sites like Monster.com to allow us to assess professionals through a network of relationships between users. Google, too, was built on this 2.0 Internet, moving beyond searching web pages to allow us to search the network of links between users. Letters became emails (online letters), and emails became tweets (networked letters). Meetings became online discussion forums and eventually crowdsourcing. Social media is at the heart of Internet 2.0. By helping move people from consumers to creators online, social media drove the web’s next generation to emerge. It sparked our collective imagination in thinking about how technology could be leveraged for self-expression, community building, and service. And as our lives become more public, we are increasingly conscious of “personal brands.” So many people now have windows into our activities, network, and points of view, and this new level of transparency has created new ways to display our aspirational selves.


pages: 413 words: 119,587

Machines of Loving Grace: The Quest for Common Ground Between Humans and Robots by John Markoff

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A Declaration of the Independence of Cyberspace, AI winter, airport security, Apple II, artificial general intelligence, augmented reality, autonomous vehicles, Baxter: Rethink Robotics, Bill Duvall, bioinformatics, Brewster Kahle, Burning Man, call centre, cellular automata, Chris Urmson, Claude Shannon: information theory, Clayton Christensen, clean water, cloud computing, collective bargaining, computer age, computer vision, crowdsourcing, Danny Hillis, DARPA: Urban Challenge, data acquisition, Dean Kamen, deskilling, don't be evil, Douglas Engelbart, Douglas Hofstadter, Dynabook, Edward Snowden, Elon Musk, Erik Brynjolfsson, factory automation, From Mathematics to the Technologies of Life and Death, future of work, Galaxy Zoo, Google Glasses, Google X / Alphabet X, Grace Hopper, Gödel, Escher, Bach, Hacker Ethic, haute couture, hive mind, hypertext link, indoor plumbing, industrial robot, information retrieval, Internet Archive, Internet of things, invention of the wheel, Jacques de Vaucanson, Jaron Lanier, Jeff Bezos, job automation, John Conway, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, John von Neumann, Kevin Kelly, knowledge worker, Kodak vs Instagram, labor-force participation, loose coupling, Mark Zuckerberg, Marshall McLuhan, medical residency, Menlo Park, Mother of all demos, natural language processing, new economy, Norbert Wiener, PageRank, pattern recognition, pre–internet, RAND corporation, Ray Kurzweil, Richard Stallman, Robert Gordon, Rodney Brooks, Sand Hill Road, Second Machine Age, self-driving car, semantic web, shareholder value, side project, Silicon Valley, Silicon Valley startup, Singularitarianism, skunkworks, Skype, social software, speech recognition, stealth mode startup, Stephen Hawking, Steve Ballmer, Steve Jobs, Steve Wozniak, Steven Levy, Stewart Brand, strong AI, superintelligent machines, technological singularity, Ted Nelson, telemarketer, telepresence, telepresence robot, Tenerife airport disaster, The Coming Technological Singularity, the medium is the message, Thorstein Veblen, Turing test, Vannevar Bush, Vernor Vinge, Watson beat the top human players on Jeopardy!, Whole Earth Catalog, William Shockley: the traitorous eight

As early as 2005, for example, two chess amateurs used a chess-playing software program to win a match against chess experts and individual chess-playing programs. Horvitz is continuing to deepen the human-machine interaction by researching ways to couple machine learning and computerized decision-making with human intelligence. For example, his researchers have worked closely with the designers of the crowd-sourced citizen science tool called Galaxy Zoo, harnessing armies of human Web surfers to categorize images of galaxies. Crowd-sourced labor is becoming a significant resource in scientific research: professional scientists can enlist amateurs, who often need to do little more than play elaborate games that exploit human perception, in order to help scientists map tricky problems like protein folding.19 In a number of documented cases teams of human experts have exceeded the capability of some of the most powerful supercomputers.

“The Lumiere project: The Origins and Science Behind Microsoft’s Office Assistant,” Robotics Zeitgeist, 2009, http://robotzeitgeist.com/2009/08/lumiere-project-origins-and-science.html. 18.Lexi Krock, “The Final Eight Minutes,” Nova, WGBH, October 17, 2006, http://www.pbs.org/wgbh/nova/space/final-eight-minutes.html. 19.Jessica Marshall, “Victory for Crowdsourced Biomolecule Design,” Nature, January 22, 2012, http://www.nature.com/news/victory-for-crowdsourced-biomolecule-design-1.9872. 20.Sherry Turkle, Alone Together: Why We Expect More from Technology and Less from Each Other (New York: Basic Books, 2011), 101. 21.Miriam Steffens, “Slaves That Are Reflections of Ourselves,” Sydney Morning Herald, November 19, 2012, http://www.smh.com.au/small-business/growing/slaves-that-are-reflections-of-ourselves-20121118-29k63.html. 22.Daniel Crevier, AI: The Tumultuous History of the Search for Artificial Intelligence (New York: Basic Books, 1993), 58. 23.Ken Jennings, “My Puny Human Brain,” Slate, February 16, 2011. 7|TO THE RESCUE 1.Stuart Nathan, “Marc Raibert of Boston Dynamics,” Engineer, February, 22, 2010, http://www.theengineer.co.uk/in-depth/interviews/marc-raibert-of-boston-dynamics/1001065.article#ixzz2pevPQoYI. 2.Public Information Office, “Fact Sheet on ‘Simon,’” Columbia University, May 18, 1950, http://www.blinkenlights.com/classiccmp/berkeley/simonfaq.html. 3.Ivan E.

In the last century the car became synonymous with the American ideal of freedom and independence. That era is now ending. What will replace it? It is significant that Google is instrumental in changing the metaphor. In one sense the company began as the quintessential intelligence augmentation, or IA, company. The PageRank algorithm Larry Page developed to improve Internet search results essentially mined human intelligence by using the crowd-sourced accumulation of human decisions about valuable information sources. Google initially began by collecting and organizing human knowledge and then making it available to humans as part of a glorified Memex, the original global information retrieval system first proposed by Vannevar Bush in the Atlantic Monthly in 1945.11 As the company has evolved, however, it has started to push heavily toward systems that replace rather than extend humans.


pages: 25 words: 5,789

Data for the Public Good by Alex Howard

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23andMe, Atul Gawande, Cass Sunstein, cloud computing, crowdsourcing, Hernando de Soto, Internet of things, Network effects, openstreetmap, Silicon Valley, slashdot, social software, social web, web application

There are a growing number of data journalism efforts around the world, from New York Times interactive features to the award-winning investigative work of ProPublica. Here are just a few promising examples: Spending Stories, from the Open Knowledge Foundation, is designed to add context to news stories based upon government data by connecting stories to the data used. Poderopedia is trying to bring more transparency to Chile, using data visualizations that draw upon a database of editorial and crowdsourced data. The State Decoded is working to make the law more user-friendly. Public Laboratory is a tool kit and online community for grassroots data gathering and research that builds upon the success of Grassroots Mapping. Internews and its local partner Nai Mediawatch launched a new website that shows incidents of violence against journalists in Afghanistan. Open Aid and Development The World Bank has been taking unprecedented steps to make its data more open and usable to everyone.

The challenge is for the men and women entrusted with coordinating response to identify signals in the noise. First responders and crisis managers are using a growing suite of tools for gathering information and sharing crucial messages internally and with the public. Structured social data and geospatial mapping suggest one direction where these tools are evolving in the field. A web application from ESRI deployed during historic floods in Australia demonstrated how crowdsourced social intelligence provided by Ushahidi can enable emergency social data to be integrated into crisis response in a meaningful way. The Australian flooding web app includes the ability to toggle layers from OpenStreetMap, satellite imagery, and topography, and then filter by time or report type. By adding structured social data, the web app provides geospatial information system (GIS) operators with valuable situational awareness that goes beyond standard reporting, including the locations of property damage, roads affected, hazards, evacuations and power outages.


pages: 299 words: 91,839

What Would Google Do? by Jeff Jarvis

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23andMe, Amazon Mechanical Turk, Amazon Web Services, Anne Wojcicki, barriers to entry, Berlin Wall, business process, call centre, cashless society, citizen journalism, clean water, connected car, credit crunch, crowdsourcing, death of newspapers, disintermediation, diversified portfolio, don't be evil, fear of failure, Firefox, future of journalism, Google Earth, Googley, Howard Rheingold, informal economy, inventory management, Jeff Bezos, jimmy wales, Kevin Kelly, Mark Zuckerberg, moral hazard, Network effects, new economy, Nicholas Carr, PageRank, peer-to-peer lending, post scarcity, prediction markets, pre–internet, Ronald Coase, search inside the book, Silicon Valley, Skype, social graph, social software, social web, spectrum auction, speech recognition, Steve Jobs, the medium is the message, The Nature of the Firm, the payments system, The Wisdom of Crowds, transaction costs, web of trust, Y Combinator, Zipcar

Instead, these tools enable any business to build a new relationship with customers. Not every customer will want a personal relationship; most will eat and run. Following Wikipedia’s 1 percent rule, it takes only a small proportion of customers to get involved and contribute great value. Restaurants are even being crowdsourced. Trend-tracker Springwise reported that a restaurant called Instructables, where customers will make all decisions, is launching in Amsterdam. The Washington Post reported on the creation of an eatery called Elements, whose owners claim it is America’s first crowdsourced restaurant. Its volunteers collaborate on concept, design, and logo. The crowd will share 10 percent of the restaurant’s profits based on the depth of their involvement. As a fan of sizzling burgers and steaming burritos, I am less than enthralled with Elements’ concept: a “sustainable vegetarian/raw foods restaurant” (in the online discussion, there was talk of adding kosher and gluten-free to the mission with round-the-clock breakfast featuring salads and green smoothies).

Why not just ask the question and give everyone the means to answer? Your worst diner could be your best friend. The more layers of data you have, the more you learn, the more useful your advice can be: People who like this also like that. Or here are the popular dishes among runners (a proxy for the health-minded) or people who order expensive wines (a proxy for good taste, perhaps). If you know about your crowd’s taste in wine, why not crowdsource the job of sommelier? Have customers rate and describe every bottle. Show which wines were ordered with which dishes and what made diners happy. If this collection of data were valuable in one restaurant, it would be exponentially more valuable across many. Thinking openly, why not compile and link information from many establishments so diners can learn which wines go best with many kinds of spicy dishes?

Fashion is top-down—or it was. Just as the internet democratizes news and entertainment, it is opening up style. A darling of the open fashion movement is Threadless, a T-shirt company that invites users to submit designs, which are voted on, Digg-like, by the community. Winning designers receive $2,000 plus a $500 credit and $500 every time a design is reprinted. They become the Versaces of the crowdsourced runway. Just as in entertainment, we are learning that the public wants to create and leave its mark. A smart response is to create a platform to make that possible. CafePress.com and Zazzle provide the means for anyone to make and sell designs on T-shirts, mugs, bumper stickers, even underwear, getting a cut of every on-demand order. Threadbanger, a weekly internet video show, teaches viewers how to make cool do-it-yourself fashion with young designers.


pages: 421 words: 110,406

Platform Revolution: How Networked Markets Are Transforming the Economy--And How to Make Them Work for You by Sangeet Paul Choudary, Marshall W. van Alstyne, Geoffrey G. Parker

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3D printing, Affordable Care Act / Obamacare, Airbnb, Amazon Mechanical Turk, Amazon Web Services, Andrei Shleifer, Apple's 1984 Super Bowl advert, autonomous vehicles, barriers to entry, big data - Walmart - Pop Tarts, bitcoin, blockchain, business process, buy low sell high, chief data officer, clean water, cloud computing, connected car, corporate governance, crowdsourcing, data acquisition, data is the new oil, discounted cash flows, disintermediation, Edward Glaeser, Elon Musk, en.wikipedia.org, Erik Brynjolfsson, financial innovation, Haber-Bosch Process, High speed trading, Internet of things, inventory management, invisible hand, Jean Tirole, Jeff Bezos, jimmy wales, Khan Academy, Kickstarter, Lean Startup, Lyft, market design, multi-sided market, Network effects, new economy, payday loans, peer-to-peer lending, Peter Thiel, pets.com, pre–internet, price mechanism, recommendation engine, RFID, Richard Stallman, ride hailing / ride sharing, Ronald Coase, Satoshi Nakamoto, self-driving car, shareholder value, sharing economy, side project, Silicon Valley, Skype, smart contracts, smart grid, Snapchat, software is eating the world, Steve Jobs, TaskRabbit, The Chicago School, the payments system, Tim Cook: Apple, transaction costs, two-sided market, Uber and Lyft, Uber for X, winner-take-all economy, Zipcar

And Airbnb, the world’s largest accommodation provider, owns no real estate.”3 The community provides these resources. Strategy has moved from controlling unique internal resources and erecting competitive barriers to orchestrating external resources and engaging vibrant communities. And innovation is no longer the province of in-house experts and research and development labs, but is produced through crowdsourcing and the contribution of ideas by independent participants in the platform. External resources don’t completely replace internal resources—more often they serve as a complement. But platform firms emphasize ecosystem governance more than product optimization, and persuasion of outside partners more than control of internal employees. THE PLATFORM REVOLUTION: HOW WILL YOU RESPOND? As you’ll see in this book, the rise of the platform is driving transformations in almost every corner of the economy and of society as a whole, from education, media, and the professions to health care, energy, and government.

The underlying principle: Give fast, open feedback when applying laws that define good behavior, but give slow, opaque feedback when applying laws that punish bad behavior. Norms. One of the greatest assets any platform—indeed, any business—can have is a dedicated community. This doesn’t happen by accident. Vibrant communities are nurtured by skilled platform managers in order to develop norms, cultures, and expectations that generate lasting sources of value. iStockphoto, today one of the world’s largest markets for crowdsourced photographs, was originally founded by Bruce Livingstone to sell CD-ROM collections of images by direct mail. As that business tanked, Bruce and his partners hated the thought that their work might go to waste. So they began giving away their images online.25 Within months, they were discovered by thousands of people who not only downloaded images but asked to share their own images as well.

Platform-based students for whom a conventional credential is important can often make special arrangements to receive one—for example, at Coursera, college credit is a “premium service” you pay extra for. The platform-based unbundling of educational activities is separating the teaching of specific skills from reliance on vast, multipurpose institutions like traditional universities. Duolingo uses a crowdsourcing platform to teach foreign languages. Its founder, Luis von Ahn, is a computer scientist who never studied language instruction. After reading the most respected books on the topic, he performed comparative tests of the leading theories using the crowds that visited his website and an evolving set of testing tools to measure the results. Today, more people are using Duolingo to learn a language than all the students in high school in the U.S. combined.2 Duolingo separates language teaching from traditional educational institutions.


pages: 271 words: 52,814

Blockchain: Blueprint for a New Economy by Melanie Swan

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23andMe, Airbnb, altcoin, Amazon Web Services, asset allocation, banking crisis, bioinformatics, bitcoin, blockchain, capital controls, cellular automata, central bank independence, clean water, cloud computing, collaborative editing, Conway's Game of Life, crowdsourcing, cryptocurrency, disintermediation, Edward Snowden, en.wikipedia.org, ethereum blockchain, fault tolerance, fiat currency, financial innovation, Firefox, friendly AI, Hernando de Soto, Internet Archive, Internet of things, Khan Academy, Kickstarter, litecoin, Lyft, M-Pesa, microbiome, Network effects, new economy, peer-to-peer lending, personalized medicine, post scarcity, prediction markets, ride hailing / ride sharing, Satoshi Nakamoto, Search for Extraterrestrial Intelligence, SETI@home, sharing economy, Skype, smart cities, smart contracts, smart grid, software as a service, technological singularity, Turing complete, unbanked and underbanked, underbanked, web application, WikiLeaks

“Hacker Dreams Up Crypto Passport Using the Tech Behind Bitcoin.” Wired, October 30, 2014. http://www.wired.com/2014/10/world_passport/; Ellis, C. “World Citizenship Project Features in Wired Magazine.” Blog post, November 1, 2014. http://chrisellis.me/world-citizenship-project-features-in-wired-magazine/. 113 De Soto, H. The Mystery of Capital: Why Capitalism Triumphs in the West and Fails Everywhere Else. New York: Basic Books, 2003. 114 Swan, M. “Crowdsourced Health Research Studies: An Important Emerging Complement to Clinical Trials in the Public Health Research Ecosystem.” J Med Internet Res 14, no. 2 (2012): e46. 115 Mishra, P. “Inside India’s Aadhar, the World’s Biggest Biometrics Database.” TechCrunch, December 6, 2013. http://techcrunch.com/2013/12/06/inside-indias-aadhar-the-worlds-biggest-biometrics-database/. 116 Deitz, J. “Decentralized Governance Whitepaper.”

Existing Customers Can Access Their Results Here Until January 1st 2015.” http://en.wikipedia.org/wiki/DeCODE_genetics. 143 Castillo, M. “23andMe to Only Provide Ancestry, Raw Genetics Data During FDA Review.” CBS News, December 6, 2013. http://www.cbsnews.com/news/23andme-to-still-provide-ancestry-raw-genetics-data-during-fda-review/. 144 Swan, M. “Health 2050: The Realization of Personalized Medicine Through Crowdsourcing, the Quantified Self, and the Participatory Biocitizen.” J Pers Med 2, no. 3 (2012): 93–118. 145 ———. “Multigenic Condition Risk Assessment in Direct-to-Consumer Genomic Services. Genet Med 12, no. 5 (2010): 279–88; Kido, T. et al. “Systematic Evaluation of Personal Genome Services for Japanese Individuals.” Nature: Journal of Human Genetics 58 (2013):734–41. 146 Tamblyn, T. “Backup Your DNA Using Bitcoins.”

“Nearly $2 Million Worth of Vericoin Stolen from MintPal, Hard Fork Implemented.” Digital Currency Magnates, July 15, 2014. http://dcmagnates.com/nearly-2-million-worth-of-vericoin-stolen-from-mintpal-hard-fork-considered/. 189 Greenberg, A. “Hacker Hijacks Storage Devices, Mines $620,000 in Dogecoin.” Wired, June 17, 2014. http://www.wired.com/2014/06/hacker-hijacks-storage-devices-mines-620000-in-dogecoin/. 190 Swan, M. “Scaling Crowdsourced Health Studies: The Emergence of a New Form of Contract Research Organization.” Pers Med. 9, no. 2 (2012): 223–34. 191 Reitman, R. “Beware the BitLicense: New York’s Virtual Currency Regulations Invade Privacy and Hamper Innovation.” Electronic Frontier Foundation, October 15, 2014. https://www.eff.org/deeplinks/2014/10/beware-bitlicense-new-yorks-virtual-currency-regulations-invade-privacy-and-hamper. 192 Santori, M.


pages: 216 words: 61,061

Without Their Permission: How the 21st Century Will Be Made, Not Managed by Alexis Ohanian

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Airbnb, barriers to entry, carbon-based life, cloud computing, crowdsourcing, en.wikipedia.org, Hans Rosling, hiring and firing, Internet Archive, Kickstarter, Mark Zuckerberg, means of production, Menlo Park, minimum viable product, Occupy movement, Paul Graham, Silicon Valley, Skype, slashdot, social web, software is eating the world, Startup school, Tony Hsieh, unpaid internship, Y Combinator

And they were doing it with the same bullish ambitions in spite of tremendous hardships, such as a thirty-year dictatorship that had been recently overthrown by a haphazard collective of revolutionaries with the hope of crowdsourcing a constitution and holding Egypt’s first free and fair election in decades. They had no hesitation. They were as fearless as any other entrepreneurs you’d meet, only they had legitimate fears in a country that was figuratively and literally rebuilding. Taking the agony out of travel also turns out to be the basis for a viable business in many contexts, including on the congested streets of Cairo. That’s what five cousins—Aly Rafea, Mohamed Rafea, Gamal Sadek, Mostafa Beltagy, and Yehia Ismail—are doing with Bey2ollak (it’s Egyptian slang, used when telling someone about something you’ve heard), a mobile application (iOS, Android, BlackBerry, Windows, and even Nokia!) that allows commuters to crowdsource more effective routes to avoid the city’s notoriously awful traffic.

Whether they were donating twenty dollars or twenty thousand dollars, they wanted to know that their contributions were making a concrete, measurable difference in the lives of students and teachers. Soon, Charles was hard at work developing a novel way to tap this potentially tremendous resource. Charles took a simple pencil sketch of his idea to a computer programmer who had recently emigrated from Poland. For two thousand dollars, the programmer built Charles a working version of DonorsChoose.org. This was in 2000, years before anyone was using phrases like “crowdsourcing” or “social media.” The first version of the website was markedly low-tech. Charles used a manual credit-card reader, like the ones you find in grocery stores, to process donations. It wasn’t pretty or fast, but it worked. The term “minimum viable product” hadn’t been coined yet, but that’s exactly what Charles put together. The first projects were posted on the site by Charles and a few of his fellow teachers whom he’d bribed with baked goods from his mother—roasted pears with spices, apricot glaze, and slices of orange rind (remember that part about treating your first customers like gold?).

Literally every single person we met—once we explained the half red and half blue bus that had INTERNET 2012 written on it—was excited about our campaign. Not only did we have a special bus, but the lead car that escorted us on this road trip was built by Local Motors. What’s remarkable about these guys isn’t just that the car was built entirely in the USA. It’s that the design of the car was crowdsourced entirely online. That’s right: people from all over the world contributed designs for a working car that eventually rolled off the assembly line. As a result, the production costs from idea to vroom12 were a fraction of what it’d cost a traditional auto manufacturer. Also, the entire process happened either in cyberspace or in the United States of America. The idea for Local Motors came to John “Jay” Rogers while he was a marine serving in Iraq.


pages: 743 words: 201,651

Free Speech: Ten Principles for a Connected World by Timothy Garton Ash

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A Declaration of the Independence of Cyberspace, Affordable Care Act / Obamacare, Andrew Keen, Apple II, Ayatollah Khomeini, battle of ideas, Berlin Wall, bitcoin, British Empire, Cass Sunstein, Chelsea Manning, citizen journalism, Clapham omnibus, colonial rule, crowdsourcing, David Attenborough, don't be evil, Edward Snowden, Etonian, European colonialism, eurozone crisis, failed state, Fall of the Berlin Wall, Ferguson, Missouri, Filter Bubble, financial independence, Firefox, Galaxy Zoo, global village, index card, Internet Archive, invention of movable type, invention of writing, Jaron Lanier, jimmy wales, Julian Assange, Mark Zuckerberg, Marshall McLuhan, megacity, mutually assured destruction, national security letter, Netflix Prize, Nicholas Carr, obamacare, Peace of Westphalia, Peter Thiel, pre–internet, profit motive, RAND corporation, Ray Kurzweil, Ronald Reagan, semantic web, Silicon Valley, Simon Singh, Snapchat, social graph, Stephen Hawking, Steve Jobs, Steve Wozniak, The Death and Life of Great American Cities, The Wisdom of Crowds, Turing test, We are Anonymous. We are Legion, WikiLeaks, World Values Survey, Yom Kippur War

In the best case, what in the online world are usually called ‘community standards’ are exactly that—the self-determined standards of a self-governing community. (Freespeechdebate.com raises an interesting question in this respect: how freely can we speak about free speech? Our community standards explain our approach and the reasoning behind it.184) A book by Jeff Howe, who seems to have coined the term ‘crowdsourcing’, concludes with ten pieces of advice, one of which is ‘pick the right crowd’.185 This is a plain but useful truth. Although the number of potential members is huge, the active membership of such crowds typically is not. Howe quotes an estimate that the optimal user base for crowdsourcing is around 5,000 people. Interestingly, that is roughly the size of the crowd you might have got together in person at a typical assembly in ancient Athens.186 As we shall see when we look more closely at free speech and knowledge, under principle 3, a few thousand very active editors have been the key to the success of Wikipedia.

Delete this Video other wise you will see that your Family Dead Bodies’ (contributed by one Anmad Sarwar) may have had something to do with that decision; see https://www.youtube.com/user/DarthF3TT/discussion 197. David Kirkpatrick, ‘A Deadly Mix in Benghazi’, New York Times, 28 December 2013, http://www.nytimes.com/projects/2013/benghazi/#/?chapt=0, 198. our map is based on the interactive map prepared by John Hudson of The Wire, embedded in http://perma.cc/QVL3-YES9 and accessible directly at http://perma.cc/ATR9-VJ8C. The daily evolving, crowdsourced Wikipedia pages documenting the affair once again demonstrated the online encyclopaedia’s value as a crowdsourced aggregator of useful information on recent events. That information was not always reliable, but with more than 200 footnotes, many of them containing links, the reader could check it out 199. Raza S. Hassan, ‘Two Cops Among 17 Killed in Karachi’, Dawn, 22 September 2012, http://perma.cc/D6VP-TUDW 200. quoted in Washington Post, 17 September 2012; watch online at http://www.youtube.com/watch?

‘Each of them by himself may not be of a good quality; but when they all come together it is possible that they may surpass—collectively and as a body, although not individually—the quality of the few best . . . For when there are many, each has his share of goodness and practical wisdom’.182 The legal philosopher Jeremy Waldron calls this the ‘doctrine of the wisdom of the many’.183 Twenty-five hundred years ago, that was the original ‘crowdsourcing’. The internet offers us opportunities to create our own self-governing online communities and draw on the ‘wisdom of crowds’ across frontiers. Within the technical, legal and political outer limits set by the big cats and dogs, we can establish communities where we say: ‘we wish to conduct this debate by certain rules. If you don’t want to live by those rules, go somewhere else’. In the best case, what in the online world are usually called ‘community standards’ are exactly that—the self-determined standards of a self-governing community.


pages: 565 words: 151,129

The Zero Marginal Cost Society: The Internet of Things, the Collaborative Commons, and the Eclipse of Capitalism by Jeremy Rifkin

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3D printing, additive manufacturing, Airbnb, autonomous vehicles, back-to-the-land, big-box store, bioinformatics, bitcoin, business process, Chris Urmson, clean water, cleantech, cloud computing, collaborative consumption, collaborative economy, Community Supported Agriculture, computer vision, crowdsourcing, demographic transition, distributed generation, en.wikipedia.org, Frederick Winslow Taylor, global supply chain, global village, Hacker Ethic, industrial robot, informal economy, intermodal, Internet of things, invisible hand, Isaac Newton, James Watt: steam engine, job automation, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, Julian Assange, Kickstarter, knowledge worker, labour mobility, Mahatma Gandhi, manufacturing employment, Mark Zuckerberg, market design, means of production, meta analysis, meta-analysis, natural language processing, new economy, New Urbanism, nuclear winter, Occupy movement, oil shale / tar sands, pattern recognition, peer-to-peer lending, personalized medicine, phenotype, planetary scale, price discrimination, profit motive, RAND corporation, randomized controlled trial, Ray Kurzweil, RFID, Richard Stallman, risk/return, Ronald Coase, search inside the book, self-driving car, shareholder value, sharing economy, Silicon Valley, Skype, smart cities, smart grid, smart meter, social web, software as a service, spectrum auction, Steve Jobs, Stewart Brand, the built environment, The Nature of the Firm, The Structural Transformation of the Public Sphere, The Wealth of Nations by Adam Smith, The Wisdom of Crowds, Thomas Kuhn: the structure of scientific revolutions, Thomas L Friedman, too big to fail, transaction costs, urban planning, Watson beat the top human players on Jeopardy!, web application, Whole Earth Catalog, Whole Earth Review, WikiLeaks, working poor, Zipcar

Interdisciplinary and multicultural studies prepare students to become comfortable entertaining different perspectives and more adept at searching out synergies between phenomena. The idea of learning as an autonomous private experience and the notion of knowledge as an acquisition to be treated as a form of exclusive property made sense in a capitalist environment that defined human behavior in similar terms. In the Collaborative Age, learning is regarded as a crowdsourcing process and knowledge is treated as a publically shared good, available to all, mirroring the emerging definition of human behavior as deeply social and interactive in nature. The shift from a more authoritarian style of learning to a more lateral learning environment better prepares today’s students to work, live, and flourish in tomorrow’s collaborative economy. The new collaborative pedagogy is being applied and practiced in schools and communities around the world.

Universities that participate in edX augment their study groups by asking their own alumni to volunteer as online mentors and discussion group leaders. Harvard professor Gregory Nagy recruited ten of his former teaching fellows to help serve as online study group facilitators in the MOOC based on his popular course, Concepts of the Ancient Greek Hero.12 Upon graduating the Coursera and edX courses, the students receive a certificate of completion. The crowdsourcing approach to learning online is designed to foster a distributed, collaborative, peer-to-peer learning experience on the Commons—the kind that prepares students for the coming era. By February 2013, Coursera had approximately 2.7 million students from 196 countries enrolled in hundreds of courses.13 EdX’s first course, in 2012, had an enrollment of 155,000 students. Anant Agarwal, edX’s president and formerly the director of MIT’s artificial-intelligence laboratory, noted that enrollment in the first virtual course nearly equaled the total number of MIT alumni in the university’s 150 years of existence.

A similar software program developed by Epagogix analyzes movie scripts to project box office hits for the film industry.36 Its success in identifying winners has made algorithm assessment standard fare in the industry. In the future, these kinds of forecasting tools will eliminate the need to hire pricey marketing agents to conduct expensive focus-group encounters and other marketing-research initiatives, the accuracy of which might pale against the crowdsourcing accuracy of Big Data filtered by algorithms. Big Data and algorithms are even being used to create copy for sports stories that are chatty, chock full of information, and engaging. The Big Ten Network uses algorithms to create original pieces posted just seconds after games, eliminating human copywriters.37 Artificial intelligence took a big leap into the future in 2011 when an IBM computer, Watson—named after IBM’s past chairman—took on Ken Jennings, who held the record of 74 wins on the popular TV show Jeopardy, and defeated him.


pages: 397 words: 110,130

Smarter Than You Think: How Technology Is Changing Our Minds for the Better by Clive Thompson

Amazon: amazon.comamazon.co.ukamazon.deamazon.fr

3D printing, 4chan, A Declaration of the Independence of Cyberspace, augmented reality, barriers to entry, Benjamin Mako Hill, butterfly effect, citizen journalism, Claude Shannon: information theory, conceptual framework, corporate governance, crowdsourcing, Deng Xiaoping, discovery of penicillin, Douglas Engelbart, Edward Glaeser, en.wikipedia.org, experimental subject, Filter Bubble, Freestyle chess, Galaxy Zoo, Google Earth, Google Glasses, Henri Poincaré, hindsight bias, hive mind, Howard Rheingold, information retrieval, iterative process, jimmy wales, Kevin Kelly, Khan Academy, knowledge worker, Mark Zuckerberg, Marshall McLuhan, Menlo Park, Netflix Prize, Nicholas Carr, patent troll, pattern recognition, pre–internet, Richard Feynman, Richard Feynman, Ronald Coase, Ronald Reagan, sentiment analysis, Silicon Valley, Skype, Snapchat, Socratic dialogue, spaced repetition, telepresence, telepresence robot, The Nature of the Firm, the scientific method, The Wisdom of Crowds, theory of mind, transaction costs, Vannevar Bush, Watson beat the top human players on Jeopardy!, WikiLeaks, X Prize, éminence grise

seeking justice for a black teenager: Kelly McBride, “Trayvon Martin Story Reveals New Tools of Media Power, Justice,” Poynter.org, March 23, 2012, accessed March 26, 2013, www.poynter.org/latest-news/making-sense-of-news/167660/trayvon-martin-story-a-study-in-the-new-tools-of-media-power-justice/; Miranda Leitsinger, “How One Man Helped Spark Online Protest in Trayvon Martin Case,” NBC News, March 29, 2012, accessed March 26, 2013, usnews.nbcnews.com/_news/2012/03/29/10907662-how-one-man-helped-spark-online-protest-in-trayvon-martin-case; An Xiao Mina, “A Tale of Two Memes: the Powerful Connection Between Trayvon Martin and Chen Guangcheng,” The Atlantic, July 12, 2012, accessed March 26, 2013, www.theatlantic.com/technology/archive/12/07/a-tale-of-two-memes-the-powerful-connection-between-trayvon-martin-and-chen-guangcheng/259604/. The Haitian earthquake of 2010: Jessica Heinzelman and Carol Waters, Crowdsourcing Crisis Information in Disaster-Affected Haiti (United States Institute of Peace, October 2010); Francesca Garrett, “We Are the Volunteers of Mission 4636,” Ushahidi blog, January 27, 2010, accessed March 26, 2013, blog.ushahidi.com/2010/01/27/mission-4636/. “When compared side by side”: Heinzelman and Waters, Crowdsourcing, 2. slower-moving civic issues: Silvia Vinas, “Colombia: #Yodigoaquiestoy, a Tool for Denouncing Child Labor,” trans. Thalia Rahme, Global Voices, July 22, 2013, accessed March 26, 2013, globalvoicesonline.org/2012/07/22/colombia-yodigoaquiestoy-a-tool-for-denouncing-child-labor/; Geoavalanche, accessed March 26, 2014, geoavalanche.org/incident/.

Soon there was a wiki with 15,789 pages, including dozens of walk-throughs—descriptions of quests—complete with maps and screenshots, and boards teeming with tips and strategies on managing your inventory. (“You can get an invincible companion dog to fight for you with another human companion at the same time by speaking to Lod at Falkreath to find his dog Barbas.”) To be sure, not all gamers use these collective documents. It’s fun to solve problems on your own, so research shows most players use crowdsourced documents sparingly, such as when they’re stuck or pressed for time. But when it comes to the biggest, most sprawling games—like World of Warcraft—the number of players who dip into crowd wisdom is huge: According to one estimate in 2008, about 50 percent of English-speaking World of Warcraft players were using the game’s wiki every month. Top players form “guilds” that play together, cooperating to tackle the most difficult monsters.

Though each microcontribution is a small grain of sand, when you get thousands or millions you quickly build a beach. Microcontributions also diversify the knowledge pool. If anyone who’s interested can briefly help out, almost everyone does, and soon the project is tapping into broad expertise: “The small contributions help the collaboration rapidly explore a much broader range of ideas than would otherwise be the case,” as the author Michael Nielsen notes in Reinventing Discovery, an investigation of crowdsourced science. Tahrir Supplies leveraged microcontributions brilliantly. Because Abulhassan made it so easy for activists to contribute news—all they needed to do was text, tweet at, or e-mail the central team—thousands did, and together they amassed a more complete picture of the situation than the central team could have achieved on its own. We see this pattern at Wikipedia, too. Because it’s so easy to add to a Wikipedia article—hit “edit” and boom, you’re a contributor—the scale of microcontributions is vast, well into the hundreds of millions.


pages: 56 words: 16,788

The New Kingmakers by Stephen O'Grady

Amazon: amazon.comamazon.co.ukamazon.deamazon.fr

Amazon Web Services, barriers to entry, cloud computing, correlation does not imply causation, crowdsourcing, DevOps, Jeff Bezos, Khan Academy, Kickstarter, Mark Zuckerberg, Netflix Prize, Paul Graham, Silicon Valley, Skype, software as a service, software is eating the world, Steve Ballmer, Steve Jobs, Tim Cook: Apple, Y Combinator

Unlike traditional venture capital, however, Kickstarter claims no ownership stake in funded projects—all rights are retained by the project owners. Though Kickstarter is by no means focused strictly on developers, they have been among the most impressive beneficiaries. Of the top projects by funds raised, the first three are video games. In March 2012, Double Fine Adventure set the record for Kickstarter projects, attracting $3.3 million in crowd-sourced financing. Number two on the list, Wasteland 2, raised just under $3 million, with third place Shadowrun Returns receiving $1.8 million. The Kickstarter model is less established than even seed-stage venture dollars, but it shows every sign of being a powerful funding option for developers moving forward. In little more than a decade, developers had gained access to free software, affordable hardware, powerful networking tools, and more entrepreneur-friendly financing options.

On October 2, 2006, Netflix announced the Netflix Prize: The first team of non-employees that could best their in-house algorithm by 10% would claim $1,000,000. This prize had two major implications. First, it implied that the benefits of an improved algorithm would exceed one million dollars for Netflix, presumably through customer acquisition and improvements in retention. Second, it implied that crowd-sourcing had the potential to deliver better results than the organization could produce on its own. In this latter assumption, Netflix was proven correct. On October 8—just six days after the prize was announced—an independent team bested the Netflix algorithm, albeit by substantially less than ten percent. The 10% threshold was finally reached in 2009. In September of that year, Netflix announced that the team “BellKor’s Pragmatic Chaos”—composed of researchers from AT&T Labs, Pragmatic Theory, and Yahoo!


pages: 377 words: 97,144

Singularity Rising: Surviving and Thriving in a Smarter, Richer, and More Dangerous World by James D. Miller

Amazon: amazon.comamazon.co.ukamazon.deamazon.fr

23andMe, affirmative action, Albert Einstein, artificial general intelligence, Asperger Syndrome, barriers to entry, brain emulation, cloud computing, cognitive bias, correlation does not imply causation, crowdsourcing, Daniel Kahneman / Amos Tversky, David Brooks, David Ricardo: comparative advantage, Deng Xiaoping, en.wikipedia.org, feminist movement, Flynn Effect, friendly AI, hive mind, impulse control, indoor plumbing, invention of agriculture, Isaac Newton, John von Neumann, knowledge worker, Long Term Capital Management, low skilled workers, Netflix Prize, neurotypical, pattern recognition, Peter Thiel, phenotype, placebo effect, prisoner's dilemma, profit maximization, Ray Kurzweil, recommendation engine, reversible computing, Richard Feynman, Richard Feynman, Rodney Brooks, Silicon Valley, Singularitarianism, Skype, statistical model, Stephen Hawking, Steve Jobs, supervolcano, technological singularity, The Coming Technological Singularity, the scientific method, Thomas Malthus, transaction costs, Turing test, Vernor Vinge, Von Neumann architecture

For example, if 90 percent of people who had some unusual allele or brain microstructure enjoyed a certain cat video, then the AI recommender would suggest the video to all other viewers who had that trait. 12.Amenable to Crowdsourcing—Netflix, the rent-by-mail and streaming video distributor, offered (and eventually paid) a $1 million prize to whichever group improved its recommendation system the most, so long as at least one group improved the system by at least 10 percent. This “crowdsourcing,” which occurs when a problem is thrown open to anyone, helps a company by allowing them to draw on the talents of strangers, while only paying the strangers if they help the firm. This kind of crowdsourcing works only if, as with a video recommendation system, there is an easy and objective way of measuring progress toward the crowdsourced goal. 13.Potential Improvement All the Way Up to Superhuman Artificial General Intelligence—A recommendation AI could slowly morph into a content creator.

See also amphetamines; amphetamines (“speed”); sleep deprivation Adderall (See under Adderall) author considers them safe and they significantly increase IQ, memory and mental staying power, 124, 211 author’s use of, 104–5, 112 benefits of, 155 as bio-enhancements for human self-improvement, 109 brain-power heightened by, 155 dangerous but effective, 124–25 doctors’ intelligence improved by, 158 drugs enhance excitement levels of different jobs, 159 drugs make life tolerable, 159 drugs reduce chronic unemployment, 159 drug studies, warnings about, 110–12 drugs would boost income of unskilled laborers, 159 economic inequality among nations, greatly reduces, 125 government-licensed occupations and, 158 hourly wages boosted by, 155 income increased by factor of 100, 125 investment banking and, 158–59 lawyers and, 158 militaries and, 109 modafinil, 104 opposition to, 109–10 parents concern that their children have, 211–12 pharmaceutical companies and, 108–9 Prisoners’ Dilemma of drug use and risks, 160–62 professors and, 158 regulated drugs, 123 Ritalin, xv, 104–5 safe and effective, 123–24 SAT tests and, 162–63 side-effects, 112 US ban on, 123–25 cognitive-enhancing technologies, 173 cognitive skills, human, 77 cognitive skills of hunter-gatherers, 76 cognitive training, 114 cognitive traits, farming-friendly, 76 Cohen, Gene, 113 cold-blooded killer, 93 Cold War, 127 community, short-term—oriented, 80 comparative advantage, 135–37 computational science, 185 computer(s) with brilliance of von Neumann, xiii chess, 132–33 Moore’s Law and computer chips, 5 nanotubes, 3-D molecular, 4 performance, 5 simulation, 45 simulation of chimpanzee’s brain, 177 Singularity-enabling of, 6 computing hardware, 7 construction workers, 179–80 consumer, hyper-rational, 42 consumer preference rankings, 42 consumption equality, 167–69 convergent evolution, 202 Coulson, Andrew, 172 crowdsourcing, 20 cruise missiles, hypersonic stealth, 127 cryocrastination, 219–20 cryonics, 213–21 Cryonics Institute, 214–15 cryonics patient, first, 220 crystallized intelligence, 115 culture software, 79 cystic fibrosis, 83–84 D Daily Princetonian, 86 DARPA. See Defense Department research agency (DARPA) Darwin, Charles, 91 dating market power of men, 194 debt-ridden countries, 177 Deep Blue (IBM’s supercomputer), 4, 132 Defense Department research agency (DARPA), 121 de Grey, Aubrey, 35 dementia, 108, 116, 149.


pages: 378 words: 94,468

Drugs 2.0: The Web Revolution That's Changing How the World Gets High by Mike Power

Amazon: amazon.comamazon.co.ukamazon.deamazon.fr

air freight, banking crisis, bitcoin, blockchain, Buckminster Fuller, Burning Man, cloud computing, credit crunch, crowdsourcing, death of newspapers, double helix, fiat currency, Firefox, Fractional reserve banking, frictionless, Haight Ashbury, Kevin Kelly, means of production, Menlo Park, Mother of all demos, Network effects, packet switching, pattern recognition, pre–internet, RAND corporation, Satoshi Nakamoto, Skype, Stephen Hawking, Steve Jobs, Stewart Brand, trade route, Whole Earth Catalog, Zimmermann PGP

The site, which was set up in 2000, offers a fascinating window into a hidden culture, and plots geographically and publicly the quality of drugs across Europe in real time, while most official reports lag by at least a year. The site’s servers are located in the Netherlands, thanks to the country’s lenient and liberal drug laws. It has 29,345 user-generated reports on pills sold as Ecstasy, and gets around 15,000 unique visitors each day. It is a self-managing community, with moderators keeping an eye on threads to ensure that dealers do not use the service to advertise their products. ‘Like any site that crowdsources user reviews there is always the danger of people gaming the system, but we find that good information always drives out bad,’ the site’s administrator told me by email. To those who argue that the site encourages drug use, he offers the baldly factual response: ‘Studies on the influence of drug information, and particularly pill testing, have shown that the more information people have about what is in pills the less likely they are to take them.’

The sample was tested by John Ramsey at St George’s, and he said it was indeed excellent quality. The story was broadcast and published on the BBC’s website. Andrew Lewman audibly facepalms as he relates the story over the telephone. ‘What better advert could they have given? Not only does this illegal site sell rare drugs, it sells very high-quality product.’ But you didn’t need to trust the BBC. The forums at the site offered crowdsourced proof of the best vendors and worst scammers. In June 2012, reviews for the best LSD vendor ran to eighty-one pages, with 50,000 views, heroin to twenty-two pages with 8,000 views. Cocaine vendors were reviewed in a 292-page behemoth with over 90,000 views, and MDMA ran in at 129 pages with over 60,000 views. One vendor said dealing drugs on the site wasn’t without its moral problems. ‘The prospect of a twelve-year-old loaded to the gills on my MDMA is not a pleasant one.

Torrents are shared downloads, so when a user fires up their bit-torrent client and downloads, say, a film using a torrent file from an illegal site such as the Pirate Bay, they actually download millions of chunks of the file from a swarm of users at once, rather than one file from one central server. The torrent software on the downloaders’ machines then assembles the pieces of data into a film or music file. Nakamoto’s elegant solution to the double-spend dilemma was to create what he called a ‘block chain’, a distributed, or shared ledger of all transfers of coins from one person to another. Crowdsourced, decentralized, massively distributed cryptographic cash had arrived. Users, known as miners, donate processor time to maintain and update the block chain, which records all transactions between users, and in the process also ‘dig’ for new coins. Miners’ computers send evidence of those transactions to the network, racing each other to solve these irreversible crypotographic puzzles that contain several transactions.


pages: 407 words: 103,501

The Digital Divide: Arguments for and Against Facebook, Google, Texting, and the Age of Social Netwo Rking by Mark Bauerlein

Amazon: amazon.comamazon.co.ukamazon.deamazon.fr

Amazon Mechanical Turk, Andrew Keen, centre right, citizen journalism, collaborative editing, computer age, computer vision, corporate governance, crowdsourcing, David Brooks, disintermediation, Frederick Winslow Taylor, Howard Rheingold, invention of movable type, invention of the steam engine, invention of the telephone, Jaron Lanier, Jeff Bezos, jimmy wales, Kevin Kelly, knowledge worker, late fees, Mark Zuckerberg, Marshall McLuhan, means of production, meta analysis, meta-analysis, Network effects, new economy, Nicholas Carr, PageRank, pets.com, Results Only Work Environment, Saturday Night Live, search engine result page, semantic web, Silicon Valley, slashdot, social graph, social web, software as a service, speech recognition, Steve Jobs, Stewart Brand, technology bubble, Ted Nelson, The Wisdom of Crowds, Thorstein Veblen, web application

. >>> redefining collective intelligence: new sensory input To understand where the Web is going, it helps to return to one of the fundamental ideas underlying Web 2.0, namely that successful network applications are systems for harnessing collective intelligence. Many people now understand this idea in the sense of “crowdsourcing”—namely, that a large group of people can create a collective work whose value far exceeds that provided by any of the individual participants. The Web as a whole is a marvel of crowdsourcing, as are marketplaces such as those on eBay and craigslist, mixed media collections such as YouTube and Flickr, and the vast personal lifestream collections on Twitter, MySpace, and Facebook. Many people also understand that applications can be constructed in such a way as to direct their users to perform specific tasks, like building an online encyclopedia (Wikipedia), annotating an online catalog (Amazon), adding data points onto a map (the many Web-mapping applications), or finding the most popular news stories (Digg, Twine).

All of a sudden, we’re not using search via a keyboard and a stilted search grammar, we’re talking to and with the Web. It’s getting smart enough to understand some things (such as where we are) without us having to tell it explicitly. And that’s just the beginning. And while some of the databases referenced by the application—such as the mapping of GPS coordinates to addresses—are “taught” to the application, others, such as the recognition of speech, are “learned” by processing large, crowdsourced data sets. Clearly, this is a “smarter” system than what we saw even a few years ago. Coordinating speech recognition and search, search results and location, is similar to the “hand-eye” coordination the baby gradually acquires. The Web is growing up, and we are all its collective parents. >>> cooperating data subsystems In our original Web 2.0 analysis, we posited that the future “Internet operating system” would consist of a series of interoperating data subsystems.

Lessig isn’t the only one singing 2.0’s praises who seems confused about fundamental terms. Jay Rosen, a professor of journalism at New York University, is maybe the most voluble booster of the “citizen journalism” that he believes fulfills the blogosphere’s social promise. Rosen has started a blog-based initiative called Assignment Zero, in which anyone, journalist or not, can file an “investigative” news article. Rosen called this “crowdsourcing” in an interview with The New York Times’s David Carr, who reported the story without expressing the slightest skepticism and without presenting an opposing view to Rosen’s. And there is an opposing point of view. In the world of Assignment Zero, if you are someone working for a politician with an ax to grind, you could use Assignment Zero to expose a pesky journalist. Or you could just go on the blog to take down someone who has rubbed you the wrong way.


pages: 238 words: 73,824

Makers by Chris Anderson

Amazon: amazon.comamazon.co.ukamazon.deamazon.fr

3D printing, Airbnb, Any sufficiently advanced technology is indistinguishable from magic, Apple II, autonomous vehicles, barriers to entry, Buckminster Fuller, Build a better mousetrap, business process, crowdsourcing, dark matter, David Ricardo: comparative advantage, death of newspapers, dematerialisation, Elon Musk, factory automation, Firefox, future of work, global supply chain, global village, industrial robot, interchangeable parts, Internet of things, inventory management, James Hargreaves, James Watt: steam engine, Jeff Bezos, job automation, Joseph Schumpeter, Kickstarter, Lean Startup, manufacturing employment, Mark Zuckerberg, means of production, Menlo Park, Network effects, profit maximization, race to the bottom, Richard Feynman, Richard Feynman, Ronald Coase, self-driving car, side project, Silicon Valley, Silicon Valley startup, Skype, slashdot, South of Market, San Francisco, spinning jenny, Startup school, stem cell, Steve Jobs, Steve Wozniak, Steven Levy, Stewart Brand, supply-chain management, The Nature of the Firm, The Wealth of Nations by Adam Smith, transaction costs, trickle-down economics, Whole Earth Catalog, X Prize, Y Combinator

The Chandler site is just the first “microfactory” of many the company plans to build across America, each with about forty employees. Each will manufacture cars created by the community, which helps build them. It’s a glimpse into a whole new way to design, engineer, and produce cars—and maybe lots of other things, too. Local Motors is a car company built on Maker principles. Its designs are crowdsourced, as is the selection of mostly off-the-shelf components. It doesn’t patent ideas—the point is to give them away so that others can build on them and make them even better, for the benefit of all. It holds almost no inventory, and purchases components and prepares kits only after buyers have made a down payment and reserved a build date. It started with a question: How would you build a car company on the Web?

It can work in units of millions and units of ones: yet another scale-free network, just like the Internet. The thirty-eight-year-old Rogers favors military-style flight suits, an echo of his time as a captain in the Marines, including action in Iraq, and he boasts both a Harvard MBA and a stint as an entrepreneur in China. While at Harvard, Rogers saw a presentation on Threadless, the open-design T-shirt company, which showed him the power of crowdsourcing. Cars are more complicated than T-shirts, but both are examples of “platforms” on which many people can display their talents and collectively innovate. And in both cases there are far more people who can design them than are currently paid to do so. In the automotive world, the majority of students who study car design don’t get jobs in the industry; instead they end up designing toothpaste tubes or kids’ toys.

Most other components are simply ordered from car parts suppliers such as Penske Automotive Group; the engines and transmissions can be bought straight from big car makers such as BMW and GM, who will sell to third parties. The axle of the Rally Fighter comes from a Ford F-150 truck; the fuel cap comes from a Mitsubishi Eclipse. This combination—have the pros handle the elements that are critical to performance, safety, and manufacturability while the community designs the parts that give the car its shape and style—allows crowdsourcing to work even for a product whose use has life-and-death implications. The final assembly is done by the customers themselves under an expert mechanic’s tutelage, as part of a “build experience” at the Chandler factory. At any given time, a half dozen Rally Fighters are being built in two rows facing each other. Each has a custom tool cabinet and a rack of parts next to it; the mechanic coach is always working with one team or another.


pages: 302 words: 73,581

Platform Scale: How an Emerging Business Model Helps Startups Build Large Empires With Minimum Investment by Sangeet Paul Choudary

Amazon: amazon.comamazon.co.ukamazon.deamazon.fr

3D printing, Airbnb, Amazon Web Services, barriers to entry, bitcoin, blockchain, business process, Clayton Christensen, collaborative economy, crowdsourcing, cryptocurrency, data acquisition, frictionless, game design, hive mind, Internet of things, invisible hand, Kickstarter, Lean Startup, Lyft, M-Pesa, Mark Zuckerberg, means of production, multi-sided market, Network effects, new economy, Paul Graham, recommendation engine, ride hailing / ride sharing, shareholder value, sharing economy, Silicon Valley, Skype, Snapchat, social graph, social software, software as a service, software is eating the world, Spread Networks laid a new fibre optics cable between New York and Chicago, TaskRabbit, the payments system, too big to fail, transport as a service, two-sided market, Uber and Lyft, Uber for X, Wave and Pay

Industrial designers will sell directly to consumers in much the same way that graphic designers currently do on platforms like Threadless and 99Designs. Collaboration models in industrial design and assembly will become networked as well. g. Crowdsourcing and the Wikipedia of everything The coordination of production has traditionally required a supply chain of integrated, top-down processes and controls. Wikipedia reconfigured this linear process and allowed it to be managed cyclically on a network. Wikipedia allows anyone to contribute content to a self-policing/semi-autonomous editorial base that works together to create a constantly changing document on the platform. Similarly, Waze, an Israeli traffic prediction app, crowdsources driving information from multiple drivers while simultaneously using algorithms to determine authenticity before distributing traffic conditions to the wider community.

Platform Scale explains the design of a family of emerging digital business models that enables today’s startups to achieve rapid scale: the platform business model. The many manifestations of the platform business model - social media, the peer economy, cryptocurrencies, APIs and developer ecosystems, the Internet of things, crowdsourcing models, and many others - are becoming increasingly relevant. Yet, most new platform ideas fail because the business design and growth strategies involved in building platforms are not well understood. Platform Scale is a builder’s manual for anyone building a platform business today. It lays out a structured approach to designing and growing a platform business model and addresses the key factors that lead to the success and failure of these businesses.

Every time that users participate on these platforms, they contribute value in the form of content and data. As users participate more often, platforms scale faster. Airbnb and Uber fight employee-driven organizations with ecosystems. Apple and Android created ecosystems of developers around their respective platforms to disrupt an entire industry. Increasingly numbers of companies are turning to crowdsourcing to solve problems that they traditionally solved in-house. The user-employee distinction is probably least stark in the case of a host of labor platforms that try to be Uber for X. Platforms like Homejoy, MyClean, and SpoonRocket create ecosystems of contract workers who might as well be employees. While some of these platforms are still negotiating the regulatory structures governing these new business models, many others have already demonstrated the power of producer ecosystems to drive value creation in a networked age.


pages: 274 words: 73,344

Found in Translation: How Language Shapes Our Lives and Transforms the World by Nataly Kelly, Jost Zetzsche

Amazon: amazon.comamazon.co.ukamazon.deamazon.fr

airport security, Berlin Wall, Celtic Tiger, crowdsourcing, Donald Trump, glass ceiling, Machine translation of "The spirit is willing, but the flesh is weak." to Russian and back, randomized controlled trial, Ray Kurzweil, Skype, speech recognition, Steve Jobs, the market place

Technical solutions for capturing and channeling the thousands of messages were quickly in place, but the majority of the messages were in Haitian Creole, a language unknown to most responders. The relatively few professional translators in the area were already completely overwhelmed by other responses and were unable to handle this onslaught of additional translation tasks. Enter Rob Munro, a linguist and graduate fellow at Stanford who had been developing methods for processing large volumes of SMS text messages in less-common languages. He’d also been working on crowd-sourcing projects. These two distinct specialties became the perfect combination for a new project called Mission 4636, which was named after the number of the free phone line the individuals used to communicate. Munro went about setting up a team for the task. In the first week alone, he assembled more than a thousand volunteers from a total of forty-nine different countries. An online chat room served as both the orientation venue for newly joining volunteers and as a platform for translators to communicate with each other and their coordinators.

It decided to engage the crowd, to allow its users to determine how they would like to see the site translated into their languages. Facebook users rallied in support of the cause. Within just a couple of weeks of starting the effort, they launched the first language, Spanish. Envision a tiny snowball at the top of the mountain. Users responded with positive feedback, so the company opened up its crowdsourcing platform to enable users to translate the site into French and German. Imagine the snowball beginning to roll down the mountain. The following year, 2008, was the year of internationalization at Facebook. “One can argue that translations contributed the most growth,” explains Ghassan Haddad, director of internationalization at Facebook.13 He notes that the number of users in Italy skyrocketed following the launch of the Italian language, jumping from 375,000 to 933,000 in just four months.

Facebook is currently available in seventy-seven languages, including U.S. English, and another thirty languages are in various phases of translation progress. The currently available languages represent over 90 percent of the world population and over 95 percent of people with access to the Internet. The company has continued to tap into its user base to produce the translated versions of its website. Facebook’s crowdsourced translation model has since served as an example for many hundreds of organizations throughout the world, including various nonprofits and charitable organizations. In fact, there are now entire companies that make money from setting up such online communities and paying professional translators to provide the translations through these portals. “Since our users are major stakeholders and partners in the translation, the launchability of additional languages depends greatly on their involvement,” Haddad observes.


pages: 510 words: 120,048

Who Owns the Future? by Jaron Lanier

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3D printing, 4chan, Affordable Care Act / Obamacare, Airbnb, augmented reality, automated trading system, barriers to entry, bitcoin, book scanning, Burning Man, call centre, carbon footprint, cloud computing, computer age, crowdsourcing, David Brooks, David Graeber, delayed gratification, digital Maoism, en.wikipedia.org, facts on the ground, Filter Bubble, financial deregulation, Fractional reserve banking, Francis Fukuyama: the end of history, George Akerlof, global supply chain, global village, Haight Ashbury, hive mind, if you build it, they will come, income inequality, informal economy, invisible hand, Jacquard loom, Jaron Lanier, Jeff Bezos, job automation, Kevin Kelly, Khan Academy, Kickstarter, Kodak vs Instagram, life extension, Long Term Capital Management, Mark Zuckerberg, meta analysis, meta-analysis, moral hazard, mutually assured destruction, Network effects, new economy, Norbert Wiener, obamacare, packet switching, Peter Thiel, place-making, Plutocrats, plutocrats, Ponzi scheme, post-oil, pre–internet, race to the bottom, Ray Kurzweil, rent-seeking, reversible computing, Richard Feynman, Richard Feynman, Ronald Reagan, self-driving car, side project, Silicon Valley, Silicon Valley ideology, Silicon Valley startup, Skype, smart meter, stem cell, Steve Jobs, Steve Wozniak, Stewart Brand, Ted Nelson, The Market for Lemons, Thomas Malthus, too big to fail, trickle-down economics, Turing test, Vannevar Bush, WikiLeaks

A market economy should not just be about “businesses,” but about everyone who contributes value. I could just as well frame my argument in the language of barter and sharing. Leveraging cloud computing to make barter more efficient, comprehensive, and fair would ultimately lead to a similar design to what I am proposing. The usual Manichaean portrayal of the digital world is “new versus old.” Crowdsourcing is “new,” for instance, while salaries and pensions are “old.” This book proposes pushing what is “new” all the way instead of part of the way. We need not shy away. Big Talk, I Know . . . Am I making a Swiftian modest proposal, or am I presenting a plan on the level? It’s a little of both. I hope to widen the way people think about digital information and human progress. We need a palate cleansing, a broadening of horizons.

Automated milling machines and similar devices are already ubiquitous for shaping parts, such as forms for molds; robotic arms to assemble components are not as common, but still present in certain applications, such as assembling parts of large items like cars and big TVs. Detail work (like fitting touchscreens into the frame of a tablet) is still mostly done by hand, but that might change soon. At first manufacturing robots will be expensive, and there will be plenty of well-paying jobs created to operate them, but eventually they will become cheap and the data to operate them might then be crowdsourced, sending manufacturing down the same road traveled by the recorded music industry. A current academic and hobbyist craze is known as “3D printing.” A 3D printer looks a little like a microwave oven. Through the glass door, you can watch roaming robotic nozzles deposit various materials under software control in an incremental way to form a product as if by magic. You download a design from the ’net, as if you were downloading a movie file, send it to your 3D printer, and come back after a while.

Instead of just driving prices down, it turns consumers into a priori funders of innovation. But at an Amazon-like scale there would inevitably be an even bigger wave of tricksters, scammers, and the clueless to be dealt with. Kickstarter continues to produce some wonderful success stories and a huge ocean of doomed or befuddled proposals. Maybe the site will enter into an endless game with scammers and the clueless, as it scales up, and render itself irrelevant. Or it might adopt crowdsourced voting or automatic filters to keep out crap, only to find that crap is smart and happy to jump through hoops to get through. Or maybe Kickstarter will become more expensive to use, and less naïvely “democratic,” because human editors will block useless proposals. Maybe it will learn to take on at least a little risk to go with the benefits. Whatever happens, success will be dependent on finding some imperfect but survivable compromise.


pages: 215 words: 55,212

The Mesh: Why the Future of Business Is Sharing by Lisa Gansky

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Airbnb, Amazon Mechanical Turk, Amazon Web Services, banking crisis, barriers to entry, carbon footprint, cloud computing, credit crunch, crowdsourcing, diversification, Firefox, Google Earth, Internet of things, Kickstarter, late fees, Network effects, new economy, peer-to-peer lending, recommendation engine, RFID, Richard Florida, Richard Thaler, ride hailing / ride sharing, sharing economy, Silicon Valley, smart grid, social web, software as a service, TaskRabbit, the built environment, walkable city, yield management, young professional, Zipcar

http://www.scoutlabs.com Skibsted Ideation A/S: Uses design as a marketing tool. http://www.skibstedid.com Sourcemap: Helps consumers find and share stories about where products come from and what they are made of. http://blog.sourcemap.org MISCELLANEOUS Thousands of Mesh businesses are thriving, from small start-ups to large cap companies. Among the more difficult to categorize include businesses that offer dog rentals, crowdsource creative ideas, run design contests, and aim to conserve resources by connecting couriers with people who want to send parcels. In this category, you will find a whole host of miscellaneous Mesh businesses. In his third year at UCLA, Chuck Gordon needed to move out of his Los Angeles apartment before spending a semester abroad in Singapore. Faced with exorbitant storage costs, Gordon was forced to get creative.

Similarly, open-source share platforms use advanced data capacity to make valuable information available to the public. You’ll find these models, and others, in this category. In 2009 a new civic engagement tool called CitySourced hit the streets in San Jose, California, allowing citizens to identify and report civic issues on the go. Using the CitySourced smartphone application, people can file sightings of graffiti, littering, potholes, and so on to city hall. Think of it as civic crowdsourcing. The app lets you photograph an infraction and locate it via your phone’s GPS tracking device. Once the image uploads successfully, users can then add comments about the problem and share it on Twitter as well. It’s a techy occasion for government to improve citizen accountability. Celltradeusa: Enables dissatisfied cell phone customers to get out of their service contracts by finding others who want in.

http://www.everytrail.com SabbaticalHomes: Internet-based directory for academic home exchanges, home rentals, and house-sitting opportunities. http://sabbaticalhomes.com SingleSpotCamping: Connects landowners with camping guests. http://www.singlespotcam ping.com TravellingTogether.EU: Connects people who want travel partners. http://www.travellingtogether.eu Virgin Limited Edition: Luxury retreat rentals. http://www.ulusaba.virgin.com/en/vle/our_collection waze: Crowdsourced maps in real time. www.waze.com UPCYCLING, RECYCLING, AND WASTE MANAGEMENT Mesh organizations aim to extend the useful life of products and reduce waste in landfills by facilitating material exchanges among individuals and businesses. They also decrease raw material resource demand by offering creative recycling services, including airport trolley upcycling, electronic and commercial waste recycling, and more.

The Orbital Perspective: Lessons in Seeing the Big Picture From a Journey of 71 Million Miles by Astronaut Ron Garan, Muhammad Yunus

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Airbnb, barriers to entry, book scanning, Buckminster Fuller, clean water, corporate social responsibility, crowdsourcing, global village, Google Earth, Indoor air pollution, jimmy wales, optical character recognition, ride hailing / ride sharing, shareholder value, Silicon Valley, Skype, smart transportation, Stephen Hawking, transaction costs, Turing test, Uber for X, web of trust

We also need tools to analyze that data and to translate the analysis into more effective and targeted approaches that can dramatically improve society’s ability to meet our grand challenges. Fortunately, along with the dramatic increase in our ability to produce data, there also have been recent developments in the power and ability of tools to analyze, make use of, and communicate the insights of that data worldwide. Among these developments is the use of crowdsourcing to process data in what is commonly known as a hackathon or codeathon. These mass collaborations are organized around various themes and were born out of a public–╉private initiative called Random Hacks of Kindness. Other ingenious mass collaboration tools include ReCAPTCHA and Duolingo, which tap the previously unutilized, distributed efforts of millions of people to perform massive tasks—╉often without users knowing they are taking part in a mass collaboration.

The app also offers information about the driver and details about the car. It certifies that others have ridden in a particular car, that they were safe and comfortable, that they gave the driver a good rating, and that the company has done some level of filtering. This technology represents a new model of community-based provisional trust, created only for the period during which a user needs the service. It is crowdsourced certification that requires very little overhead and infrastructure, and that is highly adaptive to change. By comparison, a traditional taxi system is much more like the ISS program. It operates in a hierarchical command-and-control structure. There is strict licensing, regulation, and tests. Trust is established not by other users but by the presence of a taxi permit. This is the old tried-and-true model of creating trust, institutional trust, which requires a great deal of infrastructure and overhead, takes a long time to develop, is very inflexible, and is not very open to innovation.

When many people review and comment on a particular room for rent or an Uber driver, those evaluations start to become statistically accurate. The driver or homeowner has demonstrated a track record of living up to agreements, and the collective wisdom of the crowd can point to a high level of dependability. This is similar to Duolingo’s use of beginning language students to provide translations or ReÂ�CAPTCHA’s ability to crowdsource the accuracy of book scans. Community-Based Trust These examples relate to personal trust, but there are countless similar examples of communities that form online for a specific purpose and operate in a coordinated way for the greater good. Wikipedia, for instance, was built on the premise that people enjoy interacting within a community, which in the case of Wikipedia, is a global village documenting human knowledge.


pages: 219 words: 63,495

50 Future Ideas You Really Need to Know by Richard Watson

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23andMe, 3D printing, access to a mobile phone, Albert Einstein, artificial general intelligence, augmented reality, autonomous vehicles, BRICs, Buckminster Fuller, call centre, clean water, cloud computing, collaborative consumption, computer age, computer vision, crowdsourcing, dark matter, dematerialisation, digital Maoism, Elon Musk, energy security, failed state, future of work, Geoffrey West, Santa Fe Institute, germ theory of disease, happiness index / gross national happiness, hive mind, hydrogen economy, Internet of things, Jaron Lanier, life extension, Marshall McLuhan, megacity, natural language processing, Network effects, new economy, oil shale / tar sands, pattern recognition, peak oil, personalized medicine, phenotype, precision agriculture, profit maximization, RAND corporation, Ray Kurzweil, RFID, Richard Florida, Search for Extraterrestrial Intelligence, self-driving car, semantic web, Skype, smart cities, smart meter, smart transportation, statistical model, stem cell, Stephen Hawking, Steve Jobs, Steven Pinker, Stewart Brand, strong AI, Stuxnet, supervolcano, telepresence, The Wisdom of Crowds, Thomas Malthus, Turing test, urban decay, Vernor Vinge, Watson beat the top human players on Jeopardy!, web application, women in the workforce, working-age population, young professional

The Google-backed biotech company 23andMe was offering individuals gene sequencing for $999 in 2011. At the time of writing (June 2012) the cost had fallen to $299. A decade earlier this would have cost close to $10,000, while James Watson, the codiscoverer of DNA and one of the people behind the Human Genome Project, paid around $2 billion to work out how to make sequencing work. Interestingly, 23andMe plugs into the idea of crowd-sourcing data, too, by sending regular questionnaires to thousands of users asking about them about, for example, specific food allergies. When the responses to such surveys are matched against known genetic information they can potentially find the causes of certain traits in a matter of months rather than years and for minimal cost. Power to the patient What are the main outcomes of being able to access this type of information?

In the end, it really is up to you to look after yourself by whatever method you choose from the hundreds of possibilities available so that you don’t need medicine. Yes, patients know best and can be trusted to have access to all their data. the condensed idea Patient power timeline 2014 Apple introduce iMedic monitoring feature on iPhone 6 2018 Dunnhumby and Tesco put in charge of 25 percent of UK hospitals 2020 Launch of Medipedia, a crowd-sourced medical directory 2025 All medical records accessed via the “cloud” 2030 All hospitals rated eBay style by patients 2040 TripAdvisor launches hospital review spin-off 25 Medical data mining Medicine, like insurance, isn’t always that smart. Both tend to be reactive, and personal risks are assessed using aggregated historical data, which is linked to questions about how old someone is, where they live and what they do for a living.

Jaron Lanier, sometimes referred to as the creator of the term “virtual reality,” believes that crowd intelligence is something of a fallacy analogous with the belief of hyperlibertarians that the free market is all-wise and ultimately benefits all. To quote Lanier: “The beauty of the Internet is that it connects people. The value is in the other people. If we start to believe that the Internet itself is an entity that has something to say, we’re devaluing those people and making ourselves into idiots.” The danger with crowd-sourced wisdom is that the aggregator may become more important and influential than the aggregated. Taken to the extreme, collective intelligence would mean that individuals would not be required to make individual judgments or take on individual responsibilities. Coming together? But how long will this last? Presently, our newfound hyperconnectivity is making many of us lonely. We have begun to trade intimacy for familiarity and we no longer connect deeply with anything or anyone anymore.


pages: 138 words: 40,787

The Silent Intelligence: The Internet of Things by Daniel Kellmereit, Daniel Obodovski

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3D printing, Airbnb, Amazon Web Services, Any sufficiently advanced technology is indistinguishable from magic, autonomous vehicles, barriers to entry, business intelligence, call centre, Clayton Christensen, cloud computing, connected car, crowdsourcing, data acquisition, en.wikipedia.org, Erik Brynjolfsson, first square of the chessboard, first square of the chessboard / second half of the chessboard, Freestyle chess, Google X / Alphabet X, Internet of things, Network effects, Paul Graham, Ray Kurzweil, RFID, self-driving car, Silicon Valley, smart cities, smart grid, software as a service, Steve Jobs, web application, Y Combinator, yield management

People can start asking, “What can you do to make it a better place: more efficient, safer, cleaner, etc.? What are the new ways to think about energy management, the removal chain, and pollution?” If local governments don’t necessarily need to focus on execution and operations so much anymore, but more on governing, that is also a different situation. If, instead of having to design the management system for the transport network for each city top down, you crowd-source it or take it from another city with relevant data — have the solution come out from start-ups, individuals, NGOs, corporations, you name it — then the city government takes a new role. It would ensure that minorities get as much service as majorities do, that budgets are allocated correctly, that the experts and planners use their expertise for the public good. There’s room for this new citizenship.

Volvo, for example, has successfully demonstrated road trains as part of the EU’s SARTRE (Safe Road Trains for the Environment) Project, which has several cars following one another in a platoon formation; the lead car has a professional driver taking responsibility for the platoon, while following vehicles operate in a semi-autonomous mode, reducing the distance between the vehicles, and reducing drag and fuel consumption, while getting to their destination faster.23 You may be familiar with the crowd-sourced navigation application Waze, which is one of the most accurate personal navigation applications today because it uses real-time traffic and construction information provided by users. For example, it can get you from Palo Alto to San Francisco during rush hour within five minutes of the ETA. But it still requires physical user input. What if we take this concept a notch further and imagine cars automatically populating an application like this with real-time data like speed, acceleration, weather conditions, and more?

Again, Assaf explains: We were also giving people feedback on their phone about distances they traveled and surrounding data. We also embedded air-quality sensors that measure CO, NO2, relative humidity, and temperature. All the data is collected by the sensors on the wheel and is channeled through the phone to the cloud. With open APIs, anybody can write apps to the wheel. In Copenhagen, as people ride around, each bike populates its own part of a real-time map. You get this very nice crowd-sourced and crowd-sensed map of real-time weather, pollution, and so on. Steve Hudson of Omnilink started his journey into the world of personal tracking devices in 2004 with a location-based platform to monitor and manage criminals who are assigned to an alternative program instead of being incarcerated. It’s well known that jails are overcrowded, but there is also a higher probability of re-offending after jail time, and the costs of keeping people in jail are too high.


pages: 385 words: 101,761

Creative Intelligence: Harnessing the Power to Create, Connect, and Inspire by Bruce Nussbaum

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3D printing, Airbnb, Albert Einstein, Berlin Wall, Black Swan, clean water, collapse of Lehman Brothers, Credit Default Swap, crony capitalism, crowdsourcing, Danny Hillis, declining real wages, demographic dividend, Elon Musk, en.wikipedia.org, Eugene Fama: efficient market hypothesis, Fall of the Berlin Wall, follow your passion, game design, housing crisis, Hyman Minsky, industrial robot, invisible hand, James Dyson, Jane Jacobs, Jeff Bezos, jimmy wales, John Gruber, Joseph Schumpeter, Kickstarter, lone genius, manufacturing employment, Mark Zuckerberg, Martin Wolf, new economy, Paul Graham, Peter Thiel, race to the bottom, reshoring, Richard Florida, Ronald Reagan, shareholder value, Silicon Valley, Silicon Valley ideology, Silicon Valley startup, six sigma, Skype, Steve Ballmer, Steve Jobs, Steve Wozniak, supply-chain management, Tesla Model S, The Chicago School, The Design of Experiments, the High Line, The Myth of the Rational Market, thinkpad, Tim Cook: Apple, too big to fail, tulip mania, We are the 99%, Y Combinator, young professional, Zipcar

client=ob&q=NASDAQ:AAPL, accessed October 17, 2012. 189 As Walter Isaacson’s biography: Isaacson, Steve Jobs. 189 The iTunes app acts: http://www.apple.com/itunes/, accessed September 5, 2012. 189 face-to-face dimension: Benjamin, “The Work of Art in the Age of Mechanical Reproduction.” 190 Boeing has begun using new: accessed September 5, 2012, http://www.boeing.com/commercial/ 787family/background.html/; accessed September 5, 2012, http://www.boeing.com/commercial/aeromagazine/ articles/qtr_4_06/article_04_2.html. 190 IBM has moved into: Jessi Hempel, “Crowdsourcing,” September 24, 2009, accessed September 5, 2012, http://www.businessweek.com/stories/ 2006-09-24/crowdsourcing; http://www-07.ibm.com/services/ph/portfolios/ ITS/its_s_cs_c_nationalcity.html, accessed September 9, 2012; http://www.cnbc.com/id/17169877?__source=vty, accessed September 9, 2012. 191 Corning is developing new: http://9to5mac.com/2012/ 06/04/corning-announces-slim-flexible-willow-glass-video/, accessed September 5, 2012; http://www.apple.com/about/job-creation/, accessed September 9, 2012; http://en.wikipedia.org/wiki/Gorilla_Glass, accessed September 9, 2012. 191 From its founding in 1939: In the spring of 2012, I assembled a panel of six retired HP engineers and researchers who’d worked there from the early glory days through the company’s decline, and spent two days talking with them in order to understand the culture of HP and how it had changed. 191 advanced degrees in electrical engineering: Lee Fleming, “Finding the Organizational Sources of Technological Breakthroughs: The Story of Hewlett-Packard’s Thermal InkJet,” Industrial and Corporate Change, vol. 11, no. 5, 1059–84 (Oxford University Press, 2002); “Case Study: Spitting Image,” Economist, September 19, 2002, accessed September 10, 2012, http://www.economist.com/node/1324685. 192 “HP Labs was a wonderful place”: Fleming, “Finding the Organizational Sources of Technological Breakthroughs.” 192 “I bore easily”: Ibid. 192 “very far, very fast”: Ibid. 192 In 1978, Vaught and Donald: Ibid. 192 From the beginning of what: http://en.wikipedia.org/wiki/Dot_matrix_printer, accessed September 5, 2012; http://eightiesclub.tripod.com/id325.htm, accessed September 5, 2012. 192 Dot-matrix printers were “impact printers”: Stan Retner, “History of Inkjet Printers Development,” Toner Cartridge Depot, November 21, 2007, accessed September 5, 2012, http://blog.tonercartridgedepot.com/2007/ 11/21/history-of-inkjet-printers-development/. 192 Printing was slow and loud: http://en.wikipedia.org/wiki/Dots_per_inch, accessed September 5, 2012. 192 In fact, the joke going: personal interviews with the six retired HP engineers I talked with in Portland, Oregon, in the spring of 2012. 193 For most of its early history: Ibid.; Frank Cloutier, “Building One of the World’s Largest Technology Businesses (and How to Have Fun and Profit from Your Hobbies),” presentation at MIT, March, 2, 2004, accessed at http://techtv-dev.mit.edu/videos/ 15930-building-one-of-the-world-s-largest-technology-businesses-and-how-to-have-fun-and-profit-from-your-home. 193 “We weren’t the largest”: Cloutier, “Building One of the World’s Largest Technology Businesses.” 193 And yet on Christmas Eve: Fleming, “Finding the Organizational Sources of Technological Breakthroughs; “Case Study: Spitting Image.” 193 as Vaught caught sight: Fleming, “Finding the Organizational Sources of Technological Breakthroughs.” 193 “Inventors just don’t go home”: Ibid. 193 “if you think about it”: Ibid. 193 (Because of this explosive process): Thomas Kraemer, “Printing Enters the Jet Age,” American Heritage Invention and Technology, Spring 2001, vol. 6, no. 4, 18–27; accessed September 5, 2012, http://tomsosu.blogspot.com/2012/ 02/history-of-hp-inkjet-printers-in.html. 194 “They had tremendous fun”: Alan G.

FIND YOUR WANDERER In their early days, many of the big corporations we now consider traditional, risk-averse, and efficiency-focused were every bit as creative as today’s start-ups. They were younger, more in touch with their roots, and connected to the culture of their founders. They could jump on new creative ideas and pivot them into wildly successful products and brands. And many are trying to achieve this same creative spirit today—Boeing has begun using new composite materials for its 787 Dreamliner, IBM has moved into crowdsourcing and wiring cities for innovation, and Corning is developing new glass for iPhone screens. But few companies have enjoyed the success that Hewlett-Packard had in its heyday. From its founding in 1939 in a Silicon Valley garage, HP had the kind of culture that today’s start-up entrepreneurs would love to emulate. Managers gave their employees, especially the engineers in HP labs, the freedom to play, to mine knowledge from sources that interested them, and to frame ideas however they wanted.

See also Creativity assessing, 251–57 author’s goal in developing concept of, 38–39 author’s writing and research on, 11–14, 30 beliefs about genius and, 3–9 cultivating, 257–61 design thinking paradigm and, 14–17 economics of, 240–45 five competencies of, 33–37 (see also Framing; Knowledge mining; Making; Pivoting; Playing) Indie Capitalism and (see Indie Capitalism) origination of term, 17 reassessing value of, 263–66 research on, 14–33 (see also Research, creativity) Creativity. See Creative Intelligence (CQ) Crony Capitalism. See Financial capitalism Crowdcube, 245 Crowdfunding, 36, 85–88, 170, 198–99, 244–45 Crowdsourcing, 191 Csikszentmihalyi, Mihaly, 22–23, 25, 26, 254 Cubism, 89 Culture. See also Sociocultural context embodiment of values of (see Embodiment) engagement framing in online, 97–106 United States and global, 31 (see also Global cultural environment) Curry, Michael, 123 Cyclone vacuum cleaners, 62–63 Dancing with the Stars TV program, 254 Daring Fireball website, 170 Davos, World Economic Forum, 227 DeLong, Bradford, 237 Demby, Eric, 158 Democrats, 94, 249 Dengue fever disease game, 139–40 Deregulation, 232–33 Deresiewicz, William, 78 Designer Fund, 180 Design intelligence.


pages: 323 words: 95,939

Present Shock: When Everything Happens Now by Douglas Rushkoff

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algorithmic trading, Andrew Keen, bank run, Benoit Mandelbrot, big-box store, Black Swan, British Empire, Buckminster Fuller, cashless society, citizen journalism, clockwork universe, cognitive dissonance, Credit Default Swap, crowdsourcing, Danny Hillis, disintermediation, Donald Trump, double helix, East Village, Elliott wave, European colonialism, Extropian, facts on the ground, Flash crash, game design, global supply chain, global village, Howard Rheingold, hypertext link, Inbox Zero, invention of agriculture, invention of hypertext, invisible hand, iterative process, John Nash: game theory, Kevin Kelly, laissez-faire capitalism, Law of Accelerating Returns, loss aversion, mandelbrot fractal, Marshall McLuhan, Merlin Mann, Milgram experiment, mutually assured destruction, Network effects, New Urbanism, Nicholas Carr, Norbert Wiener, Occupy movement, passive investing, pattern recognition, peak oil, price mechanism, prisoner's dilemma, Ralph Nelson Elliott, RAND corporation, Ray Kurzweil, recommendation engine, Silicon Valley, Skype, social graph, South Sea Bubble, Steve Jobs, Steve Wozniak, Steven Pinker, Stewart Brand, supply-chain management, the medium is the message, The Wisdom of Crowds, theory of mind, Turing test, upwardly mobile, Whole Earth Catalog, WikiLeaks, Y2K

(She later announced the winning song in a misguided and much-ridiculed parody of The Sopranos—as if to demonstrate facility with the everything-is-everything resonances of a self-reflexive mediaspace. All she succeeded in doing was to equate the Clinton dynasty with that of a fictional mob family. Even if she wasn’t fractalnoid, her audience was busy making the connections.) Corporations are attempting to enter the feedback loop as well—or at least trying to create limited opportunities for controlled feedback to occur. Crowdsourcing is really just a corporation’s way of trying to focus the otherwise random feedback from consumers onto a particular task. Unfortunately, they’re doing so without fully considering the liabilities. General Motors, for example, invited consumers to make commercials online for one of its SUVs. The company developed a very sophisticated set of Web utilities through which users could select footage, edit, add music, write title cards, and create special effects.

But instead of making commercials for the vehicle, more creative participants produced videos criticizing the gas-guzzling Chevy Tahoe and the way they saw GM equating machismo and patriotism with wasteful energy consumption.4 Web visitors quickly voted these to the top of the favorites list, where they garnered the attention of television news shows. Indeed, the campaign went more viral than GM could have hoped. Screech. To GM, who eventually pulled down the website, this must have seemed like an assault, some sort of activist prank or media terrorism. Why was everyone attacking GM, when all the company had done was offer people the chance to make some videos? Wasn’t this how crowdsourcing is supposed to work? For their part, the people who made the videos were simply using the tools GM provided and beginning the conversation that the company said it wanted to have. Again, the limits of openness had been reached, feedback iterated spontaneously and instantaneously into screech, and another company rethought whether it wanted to have a social media strategy at all.5 Of course, in a landscape where everyone is connecting and feeding back to everything and everyone else, there is no such thing as not having a social media strategy.

As he and microfinance innovator April Rinne explained in a recent Washington Post op-ed, “Say, for example, you are trying to solve a complex problem such as the global financial crisis. Do you ask an economist, a sociologist or a political scientist? Each of them individually is too constrained. The more multi-faceted the problem, the more forces intersect and the more challenges one must face within a siloed system.”24 On the one hand, this means democratizing innovation and change—not crowdsourcing, per say, where you just get customers to do your advertising work for you—but creating an environment where everyone connected with a culture or industry feels welcome to participate in its development. It’s the way amateur gearheads develop the best new technologies for cycling, which are then incorporated into the designs and products of major manufacturers. It’s the way Adobe encourages the users of its programs to create their own plug-ins, which are then shared online or incorporated into the next release.


pages: 313 words: 95,077

Here Comes Everybody: The Power of Organizing Without Organizations by Clay Shirky

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Andrew Keen, Berlin Wall, bioinformatics, Brewster Kahle, c2.com, crowdsourcing, en.wikipedia.org, hiring and firing, hive mind, Howard Rheingold, Internet Archive, invention of agriculture, invention of movable type, invention of the printing press, invention of the telegraph, jimmy wales, Kuiper Belt, lump of labour, Mahatma Gandhi, means of production, Merlin Mann, Nash equilibrium, Network effects, Nicholas Carr, Picturephone, place-making, Pluto: dwarf planet, prediction markets, price mechanism, prisoner's dilemma, profit motive, Richard Stallman, Ronald Coase, Silicon Valley, slashdot, social software, Stewart Brand, supply-chain management, The Nature of the Firm, The Wealth of Nations by Adam Smith, The Wisdom of Crowds, transaction costs, ultimatum game, Yogi Berra

The most complete account of the enormous changes in intellectual, religious, political, and economic life occasioned by increasingly abundant and cheap printed matter is Elizabeth L. Eisenstein’s two-volume work The Printing Press as an Agent of Change, Cambridge University Press (1979). Eisenstein also has an abridged volume of the same history, The Printing Revolution in Early Modern Europe, Cambridge University Press (2005). Page 75: Crowdsourcing Jeff Howe introduced the term “crowdsourcing” in a 2006 article for Wired magazine, available at www.wired.com/wired/archive/14.06/crowds.html. Howe is currently at work on a book by the same name and writes a weblog on the subject at crowdsourcing.typepad.com. CHAPTER 4: PUBLISH, THEN FILTER Page 84: social networking site After the 2002 success of Friendster, the first widely adopted social networking service, many more were created. Judith Meskill created a list of over three hundred (!) social networking services by 2005, and many more have been created since then.

In contrast to the situation a few years ago, taking and publishing photographs doesn’t even require the purchase of a camera (mobile phones already sport surprisingly high-quality digital cameras), and it certainly doesn’t require access either to a darkroom or to a special publishing outlet. With a mobile phone and a photo-sharing service, people are now taking photographs that are being seen by thousands and, in rare cases, by millions of people, all without any money changing hands. The twin effects are an increase in good amateur photographs and a threat to the market for professionals. Jeff Howe, author of the forthcoming Crowdsourcing, describes iStockPhoto.com, a Web-based clearinghouse for photographers to offer their work for use in advertising and promotional materials (a practice called stock photography). Prior to services like iStockPhoto, amateurs had no outlet for selling their photos, no matter what the quality, leaving the market to professionals. Because one of the services provided by professionals was the simple availability and findability of their photos relative to the amateurs, they commanded a premium for each photo sold.


pages: 329 words: 95,309

Digital Bank: Strategies for Launching or Becoming a Digital Bank by Chris Skinner

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algorithmic trading, Amazon Web Services, Any sufficiently advanced technology is indistinguishable from magic, augmented reality, bank run, Basel III, bitcoin, business intelligence, business process, business process outsourcing, call centre, cashless society, clean water, cloud computing, corporate social responsibility, credit crunch, crowdsourcing, cryptocurrency, demand response, disintermediation, don't be evil, en.wikipedia.org, fault tolerance, fiat currency, financial innovation, Google Glasses, high net worth, informal economy, Infrastructure as a Service, Internet of things, Jeff Bezos, Kevin Kelly, Kickstarter, M-Pesa, margin call, mass affluent, mobile money, Mohammed Bouazizi, new economy, Northern Rock, Occupy movement, platform as a service, Ponzi scheme, prediction markets, pre–internet, quantitative easing, ransomware, reserve currency, RFID, Satoshi Nakamoto, Silicon Valley, smart cities, software as a service, Steve Jobs, strong AI, Stuxnet, trade route, unbanked and underbanked, underbanked, upwardly mobile, We are the 99%, web application, Y2K

It is the reason why Linden Labs’ Second Life had to regulate their banks in the virtual world with bank licences in the real world, and why QQ is being regulated by the People’s Republic of China. But this maybe ignores a basic tenet of the internet: freedom. So as we move into the melding of online and offline into real-time, we could see a major shift away from bank infrastructures such as Visa, MasterCard and SWIFT into new infrastructures, such as those provided by Bitcoin. This is a more significant threat to bank services because it is a crowdsourced bank. Before I finish talking about social money, it’s also worth a quick note on complementary currencies, which are also related to Bitcoin because these are often referred to as community currencies, and Bitcoin is the community currency of the mobile internet generation. These currencies are on the rise as social money in the real world, and fuelled for broader acceptability through our networked world.

They now offer a direct online smart piggy bank in America, as well as partnerships with banks like BBVA for the Compass app in the USA, ICICI Bank for the iWish service in India and ANZ in Asia. In these instances the overseas banks offer the SmartyPig service under their own brands. Social funding and investing Social funding and investing falls into a number of sub-categories, but the major areas are crowdfunding and social trading. Crowdfunding differs from social lending in that it is investing for returns in new business start-ups and, like crowdsourcing, it pools the money of the masses into a nice venture fund to get things started. Much of the focus of crowdfunding has been around Kickstarter, the American leader in this space. Kickstarter provides a platform for funding by pre-selling your idea, rather than providing equity in the business. For example, you have a conceptual music idea, and you pre-sell the idea through Kickstarter with the hope of getting enough monies to fund the implementation of the idea (unlike other sites where you get an equity stake in the business).

That’s an important development, but it’s not a clear space. There are other crowdfunding services like Indiegogo, crowdrise, razoo and more, and even specialist sites for vertical markets like MedStartr for start-ups in Medicines. The UK has a number of crowdfunding sites – like Funding Circle, CrowdCube, Seedrs and ThinCats – so it’s a hot market space to watch right now. According to Massolution, a research firm specializing in crowdsourcing and crowdfunding solutions, crowdfunding platforms raised almost $1.5 billion worldwide in 2011, with a growth rate of 63% CAGR. They forecast that the funding figures will have doubled in 2012 to near $3 billion raised from 530 platforms, up from 452 in 2011. So this is already a serious alternative to bank credit for business and small start-ups. Social investing is illustrated by two market leading developments: eToro and Stocktwits. eToro launched in 2007 as a social network for foreign exchange trading, and is now the largest social investment network worldwide.


pages: 283 words: 85,824

The People's Platform: Taking Back Power and Culture in the Digital Age by Astra Taylor

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A Declaration of the Independence of Cyberspace, Andrew Keen, barriers to entry, Berlin Wall, big-box store, Brewster Kahle, citizen journalism, cloud computing, collateralized debt obligation, Community Supported Agriculture, conceptual framework, corporate social responsibility, cross-subsidies, crowdsourcing, David Brooks, digital Maoism, disintermediation, don't be evil, Donald Trump, Edward Snowden, Fall of the Berlin Wall, Filter Bubble, future of journalism, George Gilder, Google Chrome, Google Glasses, hive mind, income inequality, informal economy, Internet Archive, Internet of things, invisible hand, Jane Jacobs, Jaron Lanier, Jeff Bezos, job automation, Julian Assange, Kevin Kelly, Kickstarter, knowledge worker, Mark Zuckerberg, means of production, Naomi Klein, Narrative Science, Network effects, new economy, New Journalism, New Urbanism, Nicholas Carr, oil rush, Peter Thiel, Plutocrats, plutocrats, pre–internet, profit motive, recommendation engine, Richard Florida, Richard Stallman, self-driving car, shareholder value, sharing economy, Silicon Valley, Silicon Valley ideology, slashdot, Slavoj Žižek, Snapchat, social graph, Steve Jobs, Stewart Brand, technoutopianism, trade route, Whole Earth Catalog, WikiLeaks, winner-take-all economy, Works Progress Administration, young professional

Barriers to entry have been removed, gatekeepers have been demolished, and the costs of creating and distributing culture have plummeted. New tools not only have made cultural production more efficient but have equalized opportunity. NYU professor Clay Shirky, perhaps the leading proponent of this view, calls this process “social production.” Harvard’s Yochai Benkler uses the term “peer production,” business writer Jeff Howe calls it “crowdsourcing,” and Don Tapscott and his coauthor Anthony D. Williams say “wikinomics.” Whatever term they use, the commentators agree that a revolution is unfolding, with the potential to transform not just culture but also politics and the economy. They put social production on a pedestal, holding it up as more egalitarian, ethical, and efficient than the old model it is said to supersede. Tapping the deep vein of American populism, new-media thinkers portray the amateur ethos flourishing online as a blow against the elitism and exclusivity of the professions, their claims to expertise and authority, and the organizations they depend on, and there’s something appealing about this view.10 The professional class is not blameless by any means: it has erected often arbitrary barriers in the form of credentialing and licensing and has often failed to advance the public good while securing its own position.

While the economics of the Web might apply to remixing memes or posting in online forums, the costs and risks associated with creative acts that require leaving one’s computer have hardly collapsed. Where will this new paradigm leave projects like The Oath? Following Shirky’s logic, Laura Poitras is one of those professionals who should be overthrown by noble amateurs, her labor-intensive filmmaking process a throwback to another era, before creativity was a connected, collective process. The Internet might be a wonderful thing, but you can’t crowdsource a relationship with a terrorist or a whistle-blower. Makers of art and culture have long straddled two economies, the economy of the gift and the economy of the market, as Lewis Hyde elegantly demonstrated in his book The Gift: Creativity and the Artist in the Modern World. Unlike other resources, Hyde explained, culture is passed from person to person, between whom it forms “feeling-bonds,” an initiation or preservation of affection.

What we don’t know can and does hurt us, as we have seen in debacle after debacle, the truth revealed only after the damage has been done. Faced with this devastation, the cheerleaders of new media counter that a combination of volunteerism, technological savvy, and market economics will lead, as a matter of course, to the best possible outcome. Innovation will make up for any losses as if by magic: old inefficiencies will vanish, crowdsourcing—allowing readers to assist with reporting for free—will provide cheaper content, and algorithms will sort through mountains of data to extract interesting stories. By properly harnessing new tools, the newsrooms of the future will be able to do more with less, or they will simply cease to exist. “Maybe media won’t be a job at all, but will instead be a hobby. There is no law that says that industries have to remain at any given size,” former WIRED editor-in-chief Chris Anderson reflected in a 2009 interview with Der Spiegel.


pages: 302 words: 82,233

Beautiful security by Andy Oram, John Viega

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Albert Einstein, Amazon Web Services, business intelligence, business process, call centre, cloud computing, corporate governance, credit crunch, crowdsourcing, defense in depth, en.wikipedia.org, fault tolerance, Firefox, loose coupling, market design, Monroe Doctrine, new economy, Nicholas Carr, Nick Leeson, Norbert Wiener, optical character recognition, packet switching, performance metric, pirate software, Search for Extraterrestrial Intelligence, security theater, SETI@home, Silicon Valley, Skype, software as a service, statistical model, Steven Levy, The Wisdom of Crowds, Upton Sinclair, web application, web of trust, x509 certificate, zero day, Zimmermann PGP

Within days, mailing lists such as “Daily Dave” were collaborating to speculate about what the exploit was and even share code. Imagine the effectiveness of a more professional social network where security engineers could share empirical data and results from tests and experiments. Security in Numbers Social networking isn’t just about connecting people into groups to trade. It’s a medium for crowdsourcing, which exploits the wisdom of crowds to predict information. This could also play an interesting role in the future security market. To give you a simple example of crowdsourcing, one Friday at work someone on my team sent out a simple spreadsheet containing a quiz. It was late morning on the East Coast, and therefore late on Friday afternoon in Europe and late evening in our Hyderabad office. Most people on the team were in Redmond and so were sitting in traffic; most Brits were getting ready to drink beer and eat curry on Friday evening; and most Indians were out celebrating life.

Recommendations, reviews, and rankings are key components of what is called the reputation economy. These filters help people find things and present them in a contextually useful way. Few information security tools today attempt to provide contextually useful information. What we will likely see are tools that merge their particular contributions with reputation mechanisms. A code review tool that finds a potential vulnerability may match it to crowdsourced advice, which is itself ranked by the crowd and then provides contextual information like “50% of people who found this vulnerability also had vulnerability X.” Ratings and ranking will help connect the mass supply of information with the demand. To summarize the three trends in the democratization of security tools, I believe that real platforms will emerge in the security field that connect people, processes, and technology.

Send email to index@oreilly.com. 269 3-D Secure protocol, 77 e-commerce security, 84 security pitfall in, 71 Ayres, Ian, 164 Azure cloud operating system, 152 B B.J.’s Wholesale Club, 50 backend control systems, 18–20 backward compatibility LANMAN password encoding, 6 learned helplessness and, 2 legacy systems, 7 PGP issues, 117 balance in information security, 202–207 banking industry (see financial institutions) banking trojans, 141, 249 banner ads exploit-laden, 89–92, 143 honeyclients and, 143 banner farms, 98, 99 Barings Bank security breach, 38–49 Barnes & Noble, 50 Bass-O-Matic cipher, 117 behavioral analytics, 254 Bell Labs background, 171, 173 software development lifecycle, 174–178 Bellis, Ed, 73–86 Bernstein, Peter, 33 Bidzos, Jim, 117, 118 Biham, Eli, 117 biometrics, 37–38 BITS Common Criteria for Software, 193 Black Hat Conference, 161 blacklisting, 252, 254 Blaster virus, 248 blogging, 166 BoA Factory site, 65 Bork, Robert, 241 Boston Market, 50 botnets army building software, 67 attack infrastructure, 66 challenges in detecting, 231 client-side vulnerability, 131 CPC advertising, 100, 101 cyber underground and, 64 functionality, 64, 69, 230 peer-to-peer structure, 66 BPM (Business Process Management) levels of effective programs, 157 multisite security, 156–158 potential for, 154–158 supply chain composition and, 155 270 INDEX BPMI (Business Process Management Initiative), 157 breaches (see security breaches) bridge CAs, 111 Briggs, Matt, 140 brute-force attacks, 28, 251 buffer overflows security vulnerability, 15, 131 SQL Slammer worm, 225 Business Process Management (see BPM) Business Process Management Initiative (BPMI), 157 business rules engines, 157 C California AB 1950, 207 California SB 1386 balance in information security, 203–205 on data sharing, 36, 38 on reporting breaches, 55 passage of, 207 call options, 40 Callas, Jon, 107–130 Capture-HPC honeyclient, 138, 145 CardSystems security breach, 211 Carnegie Mellon CMMI process, 185 Carr, Nicholas, 157 Carter Doctrine, 201 CAs (see certificate authorities) cashiers (cyber underground) defined, 65 drop accounts, 70 CDC (Centers for Disease Control and Prevention), 36 Center for Internet Security (CIS), 45 Center for Strategic and International Studies (CSIS), 201 Centers for Disease Control and Prevention (CDC), 36 certificate authorities, 112 (see also introducers in PGP) certification support, 111 DSG support, 203 establishing trust relationships, 27 hierarchical trust, 109 SET requirements, 78 certificates, 109 (see also specific types of certificates) defined, 111 revoking, 120–122 self-signed, 109 verifying, 109 Web of Trust support, 113 certification defined, 111 OpenPGP colloquialism for, 112 OpenPGP support, 111 CFAA (Computer Fraud and Abuse Act), 207 Charney, Scott, 201 Chuvakin, Anton, 213–224, 226 Cigital, 171, 188 Citi, 79 CLASP methodology, 187, 188 click fraud botnet support, 66, 101 CPA advertising, 102 federal litigation, 102 client-side vulnerabilities, 133 (see also honeyclients) background, 131–132 malware exploitation, 15, 132, 141–143 naïveté about, 8–9 Clinton, Bill, 17 cloud computing applying security to, 152 builders versus breakers, 151 defined, 150 identity management services, 154 CNCI (Comprehensive National Cybersecurity Initiative), 202 CNN network, 16 COBIT regulation, 214 Code Red virus, 248 Commerce, Department of, 180 commercial software (see software acquisition) Commission Junction affiliate network, 102 Commission on Cyber Security for the 44th Presidency, 201 Common Vulnerabilities and Exposures (CVE) database, 131 communication cyber underground infrastructure, 65, 66 information security and, 207–211 Comprehensive National Cybersecurity Initiative (CNCI), 202 Computer Fraud and Abuse Act (CFAA), 207 confidentiality of data, 85 confirmation traps defined, 10 intelligence analysts, 12 overview, 10–11 rationalizing capabilities, 13 stale threat modeling, 12 contagion worm exploit, 131 cookies, stuffed, 102 cost per action (see CPA advertising) cost per click (see CPC advertising) Cost Per Thousand Impressions (see CPM advertising) COTS (see software acquisition) coverage metrics, 46 CPA advertising functionality, 100 inflating costs, 102–103 stuffed cookies, 102 CPC advertising click-fraud detection services, 101 functionality, 100–101 syndication partnerships, 100 CPM advertising basis of, 98 fraud-prone, 100–103 credit card information as shared secret, 75–76, 85 card associations and, 82 checking site authenticity, 26 consumers and, 81, 83 current market value, 66 CV2 security code, 76 cyber underground and, 65 devaluing data, 71 e-commerce security, 73–75 financial institutions, 82 identity theft, 23–25 merchants and service providers, 81, 83 PCI protection, 44 proposed payment model, 86 spyware stealing, 69 SQL injection attacks, 69 TJX security breach, 50 virtual cards, 79 cross-certification, 111 cross-site scripting, 188 crowdsourcing, 161 Crypto Wars, 118 CSIS (Center for Strategic and International Studies), 201 culture, organizational, 200–202 cumulative trust, 110 Curphey, Margaret, 169 Curphey, Mark, 147–169 CV2 security code, 76 CVE (Common Vulnerabilities and Exposures) database, 131 cyber underground attack infrastructure, 66 attack methods, 68–70 cashiers, 65 combating, 71–72 communication infrastructure, 65 CSI-FBI Study, 63 data exchange example, 67 fraudsters and attack launchers, 65 goals of attacks, 63, 226, 230 information dealers, 64 INDEX 271 information sources, 68 makeup and infrastructure, 64–66 malware producers, 64 money laundering and, 70 payoffs, 66–71 resource dealers, 64 Cydoor ad network, 90 D Danford, Robert, 144 Data Encryption Standard (DES), 4 data integrity, 85 Data Loss Database (DataLossDB), 36, 55–58 data responsibility incentive/reward structure, 72 social metric for, 72 data theft as cottage industry, 67 botnet support, 66 combating, 71 from merchant stores, 68 incident detection considerations, 237 spyware and, 69 data translucency additional suggestions, 245 advantages, 244 disadvantages, 245 overview, 239–242 personal data and, 244 real-life example, 243 data-sharing mechanisms DHS support, 36 security flaws in, 35 databases data translucency in, 239–246 logging support, 221 security breaches and, 239 Dave & Buster’s, 50 Davies, Donald, 148 DCS systems, 18 DDoS (distributed denial of service) attacks on major ISPs, 16 botnet support, 66, 231 client-side vulnerability, 131 honeyclients and, 138 LANs and, 28 deceptive advertisements, 94–98 Defense, Department of, 213 Dell computers, 131 Deloitte & Touche, LLP, 201 denial of service (see DDoS) Department of Agriculture, 196 Department of Commerce, 180 Department of Defense, 213 Department of Homeland Security, 36 272 INDEX deperimeterization, 156 DES (Data Encryption Standard), 4 designated revokers, 121 DHCP lease logs, 237 DHS (Department of Homeland Security), 36 Diffie, Whitfield, 112 digital certificates (see certificates) Digital Point Systems, 102 Digital Signature Guidelines (DSG), 202–203 direct trust defined, 109 root certificates, 110 directionality, 227 distributed denial of service (see DDoS) distribution channels, 166 DKIM email-authentication, 124 Dobbertin, Hans, 119 doing the right thing in information security, 211– 212 drop accounts, 70 Drucker, Peter, 163 DSG (Digital Signature Guidelines), 202–203 DSW Shoe Warehouse, 50 Dublin City University, 144 Dunphy, Brian, 225–237 Durick, J.D., 138 dynamic testing, 190 E e-commerce security 3-D Secure protocol, 76–78 analyzing current practices, 74–75 authorizing transactions, 84 broken incentives, 80–83 confidentiality of data, 85 consumer authentication, 83 data integrity, 85 exploiting website vulnerabilities, 68 friendly fraud and, 84 merchant authentication, 83 new security model, 83–86 not sharing authentication data, 84 portability of authentication, 85 primary challenges, 73 proposed payment model, 86 SET protocol, 78 shared secrets and, 75–76, 85 virtual cards, 79 EAP (Extensible Authentication Protocol), 51 Earned Value Management (EVM), 173 eBay CPA advertising, 102 DDoS attacks on, 16 principle of reliability, 160 ECPA (Electronic Communications Privacy Act), 207 Edelman, Benjamin, 89–105, 210, 250 Edwards, Betsy, 178 Einstein, Albert, 147 Electronic Communications Privacy Act (ECPA), 207 email log handling, 221 malware exploits, 248 EMBED tag, 94 encryption LAN Manager sequence, 4 PGP support, 107, 116–120 security certificates and, 22, 24 SET support, 78 Encyclopædia Britannica, 94–98 event logs (see logs) EVM (Earned Value Management), 173 executables, malware exploits and, 143 exportable signatures, 125 extended introducers, 123 Extensible Authentication Protocol (EAP), 51 F Facebook social network, 159, 165, 166 failing closed, 8 failing open, 8 false negatives, 236 false positives, 217, 236 Federal Sentencing Guidelines, 209 Federal Trade Commission (see FTC) financial institutions banking trojans, 141, 249 credit card information, 82 cyber attacks on, 68 drop accounts, 70 exploiting website vulnerabilities, 68, 187 federated authentication programs, 210 infosecurity and, 208 Finjan security firm, 65 Finney, Hal, 117 firewalls energy company vulnerabilities, 18 host logging, 232 log handling, 216, 221 need for new strategies, 248 SQL Slammer worm, 225 watch lists, 231 Flash ActionScript, 93 Forester, C.


pages: 437 words: 113,173

Age of Discovery: Navigating the Risks and Rewards of Our New Renaissance by Ian Goldin, Chris Kutarna

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2013 Report for America's Infrastructure - American Society of Civil Engineers - 19 March 2013, 3D printing, Airbnb, Albert Einstein, AltaVista, Asian financial crisis, asset-backed security, autonomous vehicles, banking crisis, barriers to entry, battle of ideas, Berlin Wall, bioinformatics, bitcoin, Bonfire of the Vanities, clean water, collective bargaining, Colonization of Mars, Credit Default Swap, crowdsourcing, cryptocurrency, Dava Sobel, demographic dividend, Deng Xiaoping, Doha Development Round, double helix, Edward Snowden, Elon Musk, en.wikipedia.org, epigenetics, experimental economics, failed state, Fall of the Berlin Wall, financial innovation, full employment, Galaxy Zoo, global supply chain, Hyperloop, immigration reform, income inequality, indoor plumbing, industrial robot, information retrieval, intermodal, Internet of things, invention of the printing press, Isaac Newton, Islamic Golden Age, Khan Academy, Kickstarter, labour market flexibility, low cost carrier, low skilled workers, Lyft, Malacca Straits, megacity, Mikhail Gorbachev, moral hazard, Network effects, New Urbanism, non-tariff barriers, Occupy movement, On the Revolutions of the Heavenly Spheres, open economy, Panamax, personalized medicine, Peter Thiel, post-Panamax, profit motive, rent-seeking, reshoring, Robert Gordon, Search for Extraterrestrial Intelligence, Second Machine Age, self-driving car, Shenzhen was a fishing village, Silicon Valley, Silicon Valley startup, Skype, smart grid, Snapchat, special economic zone, spice trade, statistical model, Stephen Hawking, Steve Jobs, Stuxnet, TaskRabbit, too big to fail, trade liberalization, trade route, transaction costs, transatlantic slave trade, uranium enrichment, We are the 99%, We wanted flying cars, instead we got 140 characters, working poor, working-age population, zero day

“Prejudice, Not Brainpower, Is Behind the Gender Gap.” The Times. Retrieved from www.thetimes.co.uk. 11. XPrize (2015). “Who We Are.” XPrize.org. Retrieved from www.xprize.org. 12. Barnett, Chance (2015, June 9). “Trends Show Crowdfunding to Surpass VC in 2016.” Forbes. Retrieved from www.forbes.com. 13. Crowdsourcing.org (2015). “Global Crowdfunding Market to Reach $34.4B in 2015, Predicts Massolution’s 2015 CF Industry Report.” Retrieved from www.crowdsourcing.org/editorial. 14. World Bank (2013). “Crowdfunding’s Potential for the Developing World.” Information for Development Program. Washington, D.C.: The World Bank. 15. Ibid. 16. National Science Foundation (2014). “Table 4-3: US R&D Expenditures, by Performing Sector, Source of Funds, and Character of Work: 2011.”

Too often, we resist or suppress new ideas because they threaten vested interests. Copernicus’s sun-centric theory wasn’t the only Aha! idea to meet fierce opposition: Swiss scribes rallied against the printing press; Dutch guilds fought advances in shipbuilding; French paper makers burned machines that would have sped up pulp-making.6 Likewise, today’s fossil fuel industry is resisting the transition to alternatives; mainstream banks throw cold water on crowd-sourced lending; and taxi drivers cry foul over apps that help commuters buy rides from one another. Is every new idea a good one? No, but in a Renaissance moment that should be our default assumption—unless the idea directly harms people. Now more than ever, society has the capacity to judge an idea, share it and spark a better one.* Let’s applaud experimentation, even with society’s sacred cows—or some of the best discoveries of the twenty-first century might never happen.

In 2010, there were about 100 crowdfunding platforms running; together they raised just under $900 million for posted projects.12 By 2015, over 1,250 platforms together raised an estimated $35 billion.13 That’s more than the global venture capital industry invests in an average year (about $30 billion), and is on pace to triple, at least, by 2020.14 Crowdfunding allows a wide population to support discovery work, and scientists especially need to get better at extending that invitation as part of the research proposals they write. But crowdsourcing has its limits. Even faced with the best proposals, the crowd seems unlikely to take much interest in research. Over 70 percent of 2015 crowdfunding was in the form of short-term, person-to-person loans that lenders expect to be repaid, with interest.15 And science is notoriously bad at keeping to a quick repayment schedule when it’s camped out on the far northern frontier of human understanding.


pages: 226 words: 71,540

Epic Win for Anonymous: How 4chan's Army Conquered the Web by Cole Stryker

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4chan, barriers to entry, Berlin Wall, Chelsea Manning, cognitive dissonance, Columbine, crowdsourcing, Firefox, future of journalism, hive mind, informal economy, Internet Archive, Julian Assange, Mark Zuckerberg, Marshall McLuhan, Mason jar, pre–internet, Silicon Valley, slashdot, social web, Stephen Hawking, Steve Jobs, Stewart Brand, technoutopianism, wage slave, We are Anonymous. We are Legion, Whole Earth Catalog, WikiLeaks

Japanese culture is deeply embedded in underground Internet communities like 4chan, partially because the initial scarcity of anime in the West drove anime nerds to the web to find information about their hobby—but also because certain strains of anime lean towards the transgressive, and transgression loves company. /adv/ Advice One of the more recent social experiments on 4chan, the /adv/ board is a crowd-sourced advice column. Sometimes responses are genuine, even heartfelt. Sometimes they’re snarky and mean, but in a lighthearted, creative way. A lot of the questions deal with nerds asking help for dealing with girls. Here’s the top question right now, verbatim: Ok, so here’s my problem. Next fall, I got into my last year of college. I’ve havent declared a major, but I can finish either English or Psychology in two semesters.

Interestingly, anonymous posters on Slashdot are jokingly labeled “Anonymous Coward.” Matt Haughey was a big fan of Slashdot, but he wasn’t crazy about the interface. Slashdot had editors that picked from submitted stories. Matt was looking for something more democratic, so he created MetaFilter, a community where anyone’s story could land on the front page. The community blog became most notable for its Ask Metafilter section, which was an early example of information crowd-sourcing. You could ask an obscure question and, due to the size and quality of the community, sometimes get surprisingly informed answers. This kind of querying would influence sites like Yahoo Answers, Quora, Reddit, and, to an extent, even 4chan. According to Haughey, MetaFilter also developed its own memespeak pretty early on. Probably in the first year, 2000 or so, I noticed people shouting “double post!”

Eventually someone provides a list of potential perpetrators’ Facebook pages. Youtube account owners name is Martin. They live in Bugojno, use googlemaps. [link to a YouTube account] This faggot commented their youtube account and is a possible friend. This is the Vrbas river, the one from the video. The thread is peppered with criticisms from those who would decry moralfaggotry. Despite the naysayers, this crowd-sourced detective work is one of the most exhilarating things about 4chan. They are able to accomplish much in the aggregate that they wouldn’t alone. As philospher Pierre Lévy says, “No one knows everything. Everyone knows something.” All it takes is one person to translate a bit of dialogue, recognize a style of license plate, or pinpoint a specific mountain range in the background of a fuzzy YouTube video.


pages: 307 words: 17,123

Behind the cloud: the untold story of how Salesforce.com went from idea to billion-dollar company--and revolutionized an industry by Marc Benioff, Carlye Adler

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Albert Einstein, Apple's 1984 Super Bowl advert, barriers to entry, Bay Area Rapid Transit, business continuity plan, call centre, carbon footprint, Clayton Christensen, cloud computing, corporate social responsibility, crowdsourcing, iterative process, Maui Hawaii, Nicholas Carr, platform as a service, Silicon Valley, software as a service, Steve Ballmer, Steve Jobs

In the coming weeks, tens of thousands of users agreed, and the post ranked as the number-one idea for months. Three months later, as a direct result of this intelligence, Dell released several consumer notebooks and desktops with the Linux operating system preinstalled. Using the 128 The Technology Playbook Internet and our Ideas technology platform, Dell has gained the ability to listen to its customers. As Jeff Howe explains in his book, Crowdsourcing: Why the Power of the Crowd Is Driving the Future of Business, ‘‘Dell’s IdeaStorm attempts to capture the collective intelligence of the crowd. . . . It’s using the crowd to brainstorm new innovations.’’2 The result? Ideas turning into revenue within months. Michael Dell, pleased with the immediate return on investment, shared his experience with Howard Schultz of Starbucks. He even did a demo for him.

Matt Hines, ‘‘Salesforce.com’s Brash New Ads Reflect the Style of Its Leader,’’ SearchCRM.com, March 13, 2002, http: //searchcrm.techtarget.com/news/article/0,289142,sid11 gci809857,00.html. Part 3 1. David Berlind, ‘‘Full Text of Marc Benioff’s Internal Memo to Salesforce Staff on Oracle/Siebel Deal,’’ Between the Lines, September 12, 2005, blogs.ZDNet.com. Part 5 1. Rochelle Garner, ‘‘Microsoft Undermined by Salesforce .com in Web Sales,’’ Bloomberg.com, Jan. 25, 2008, http:// www.bloomberg.com/apps/news?pid=20601087&sid=afU TE1bpZWp4&refer=home. 2. Jeff Howe, Crowdsourcing: Why the Power of the Crowd Is Driving the Future of Business, New York: Crown Business, 2008, p. 158. 3. Jeff Jarvis, ‘‘Hey Starbucks, How About Coffee Cubes?’’ BusinessWeek, April 15, 2008, http://www.businessweek.com /magazine/content/08 17/b4081000030457.htm. 4. Jeff Jarvis, ‘‘Dell Learns to Listen,’’ BusinessWeek, October 17, 2007, http://www.businessweek.com/bwdaily/dnflash/ content/oct2007/db20071017 277576.htm. 262 Notes 5.

., 43, 255 Cisco, 13, 91, 100, 140, 145, 203, 220, 258 City Tours, 49–51, 54, 57–58, 62 Clark, Don, 23, 72 Clean Air-Cool Planet, 162 Cleveland, Bruce, 64 Closing, 93 Coca-Cola, 86 CODA, 125 Collaboration: developing communities of, 131–132, 145; philanthropic, 159–161 Committee Encouraging Corporate Philanthropy (CECP), 218 Companies: collaborating with, 131–132; incorporating philanthropic models in existing, 135–139 Competition: going after market leaders, 34, 36–38; leveraging, 60–61; relationships with, 39–40; surprising, 38 Conde, Cris, 89–91 Confidence, 16 Connery, Nancy, 15, 16, 233–234, 248 Conservation International, 162 Contra Costa Times, 31 Contracts: annual service, 207–208; converting subscriptions to, 82–85, 207–208; writing with light and love, 188–192 Cooperative sales efforts, 92 Corporate philanthropy: choosing cause for, 144–146; creating self-sustaining model for, 153–156; employee-inspired foundations, 161–165; foundations in business model, 140–144; giving back to communities, 191; Google’s commitment to, 160–161; Hasbro’s, 141–142; in-kind product donations, 156–158, 166; incorporating in existing company, 135–139; integrating with organization, 139–140; involving new hires in, 243–244; 272 listening to constituents, 148–152; partner and network involvement in, 159–161; reasons for, 147–148; sharing financial successes, 217–218; sharing philanthropic models, 146–147; success of 1–1–1 Model, 256; supporting employee sabbaticals, 1–3; sustaining foundations, 166–168 Corporate sales teams: developing, 88–89; international, 172–173; selling corporate services, 98–100; in sequential growth strategies, 177–178 Costs: event, 57–59; managing while expanding, 176–177; reducing start-up company, 206–207 Council on Foundations, 148 Critical Metrics, 250 Criticism, 9–11 CRM (customer relationship management): developing international divisions for, 169–170, 173; Microsoft’s venture into, 42; origins of salesforce.com, 11–12; positioning End of Software mission, 24–25; potential sales via telephone, 77–78; potentials for SaaS online products, 6; scalability challenge for, 8–9; Siebel goes public, 5 CRM Fusion, 160 CRM ticker symbol, 213 Crowdsourcing (Howe), 129 Culture: aligning employees to, 242–244; beginning of salesforce.com, 12; defining company, 11–12; recruiting new talent into, 15, 16, 17, 19, 233–239; transferring globally, 178–179, 192, 195–196, 197 Customer relationship management. See CRM Customers: accessibility and satisfied, 98–99; being involved in dialogues of, 130; building trust with, 110–113; contacting personally, 114; contract for, 219–220; contracts for, 207–208; developing network of, 53–54; ease of product adoption by, 119; enlisting for sales, 73–76; harnessing ideas of, 127–130; influencing products, 115–118; introducing prospects to happy, 100–101; leveraging change with, 82–85; listening to, 13–14, 85–86; special support for professional, 98–100; supporting existing, 97–98; testimony of, 47–52; treating as partners, 69–71; visiting, 93 CustomerStat, 52 Customization features, 115–118 D Dalai Lama, His Holiness, 2, 11 Dell, 100, 128–129, 172 Dell, Michael, 128, 129, 130, 151, 196 Deloitte, 99, 148 Dempsey, David, 170 DiBianca, Suzanne, 140, 146 Digg, 127 Disaster relief, 163–164 Discounts, 78–79, 83–84 Disney, Walt, 103, 203 Dominguez, Frank, 11, 20, 106–107, 139–140 Dot-com crash, 27 Index Draper, Tim, 153 Dreamforce, 61–63, 65 DuPont, 99 E E*TRADE, 100, 203 E-Rate, 144 Earth Council, 163 EBay, 108, 114, 140–141, 183 Ebersole, Scott and Wendi, 247 Editorials, 47 80/20 rule, 12–13, 174 Einstein, Albert, 11 Einstein, David, 24 Ellison, Larry, 14–15, 16–17, 30, 31, 136, 137, 138, 204, 226 Employees: being on-message, 55; career paths for, 250–252; corporate philanthropy and, 147; employee-inspired foundations, 161–165; empowering as volunteers, 141–142, 161–162, 163–164; engaging and growing, 247–248; feedback from, 249–252; finding innovative, 240; firing, 249; fostering loyal, 246–247; incentives for, 245–246; listening to, 81; measuring success of, 251; moving to satellite offices, 193–196; as part of marketing team, 33–34, 35; retaining, 242–244; sabbaticals for, 1–3; training, 252, 253–254 Employees.


pages: 288 words: 66,996

Travel While You Work: The Ultimate Guide to Running a Business From Anywhere by Mish Slade

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Airbnb, Atul Gawande, business process, Checklist Manifesto, cloud computing, crowdsourcing, Firefox, Google Chrome, Google Hangouts, Inbox Zero, job automation, Lyft, remote working, side project, Skype, speech recognition

Now onto the practicalities of how to do this… Use Google Translate (www.worktravel.co/gtranslate) to translate a few key words and phrases ("hello", "goodbye", "do you speak English?", "delicious!", etc.). You can hear how they sound by clicking on the "speaker" symbol. If you want to practise these words, use a flashcard app like Anki (www.worktravel.co/anki). If you actually want to have a go at learning the language, Duolingo (www.worktravel.co/duolingo) should be your first port of call. It's a language-learning and crowdsourced text-translation platform, available in a number of languages. It's gamified, free, and immensely fun – so it ticks all the boxes. You may end up being asked to translate phrases like "The bear will not fit through the door" and "My yellow turtles drink milk", but you will learn how to speak the language. Also give Michel Thomas audiobooks a try: www.worktravel.co/michel. And there are a number of language-learning podcasts available on iTunes.

(A person at the store will often do it for you, but if not, you might want to look online for instructions – just in case the instructions on the packet are in a different language.) Does the SIM allow tethering, so that you can share your phone's internet connection with your laptop? Not all SIM cards allow this, but it's a useful thing to have because it means you'll be able to work even if you arrive at your apartment and the wifi happens to be shoddy. As well as using the above instructions, you might want to check out the following websites for their crowd-sourced info on SIM packages around the world (bear in mind that the info might be incomplete or out of date): TripAdvisor forum (www.worktravel.co/taforum): click on the country you're interested in, then type something like "monthly prepaid SIM 3G". Prepaid with Data (www.worktravel.co/prepaid): a massively useful resource, but it often doesn't have all the information/available packages for each SIM card provider.

SeatGuru (www.worktravel.co/seatguru) is both your match made in heaven and your potential rabbit hole: there's just way too much fun to be had with airline-related information. SeatGuru has seating maps for all airlines, but where things get really cool is that the maps are colour-coded according to how good the seats are: some are considered superior according to the price you paid, while others are marked as downright awful and not worth a penny. And who decides on the "colours" of the seats? Anyone – including you! The information is crowdsourced by users of the site. You'll also see a few written reviews of seats next to each plane's seating map. (If you want to waste the rest of your day on airplane-related geekery, head to SeatGuru to compare all the airlines' first class cabins: www.worktravel.co/firstclass. You can also browse SeatGuru's ever-fascinating blog: www.worktravel.co/sgblog.) Frequent flyer deals In frequent flyer land, everything's constantly in flux.


pages: 552 words: 168,518

MacroWikinomics: Rebooting Business and the World by Don Tapscott, Anthony D. Williams

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accounting loophole / creative accounting, airport security, Andrew Keen, augmented reality, Ayatollah Khomeini, barriers to entry, bioinformatics, Bretton Woods, business climate, business process, car-free, carbon footprint, citizen journalism, Clayton Christensen, clean water, Climategate, Climatic Research Unit, cloud computing, collaborative editing, collapse of Lehman Brothers, collateralized debt obligation, colonial rule, corporate governance, corporate social responsibility, crowdsourcing, death of newspapers, demographic transition, distributed generation, don't be evil, en.wikipedia.org, energy security, energy transition, Exxon Valdez, failed state, fault tolerance, financial innovation, Galaxy Zoo, game design, global village, Google Earth, Hans Rosling, hive mind, Home mortgage interest deduction, interchangeable parts, Internet of things, invention of movable type, Isaac Newton, James Watt: steam engine, Jaron Lanier, jimmy wales, Joseph Schumpeter, Julian Assange, Kevin Kelly, knowledge economy, knowledge worker, Marshall McLuhan, medical bankruptcy, megacity, mortgage tax deduction, Netflix Prize, new economy, Nicholas Carr, oil shock, online collectivism, open borders, open economy, pattern recognition, peer-to-peer lending, personalized medicine, Ray Kurzweil, RFID, ride hailing / ride sharing, Ronald Reagan, scientific mainstream, shareholder value, Silicon Valley, Skype, smart grid, smart meter, social graph, social web, software patent, Steve Jobs, text mining, the scientific method, The Wisdom of Crowds, transaction costs, transfer pricing, University of East Anglia, urban sprawl, value at risk, WikiLeaks, X Prize, young professional, Zipcar

When disaster struck Haiti two years later, Ushahidi’s director of crisis mapping, Patrick Meier, sprang into action. Meier had been enjoying a quiet evening watching the news at his home in Boston. It was 7:00 p.m. when he first learned about the earthquake. By 7:20, he’d contacted a colleague in Atlanta. By 7:40, the two were setting up a dedicated site for Haiti on the Ushahidi platform. By 8:00, they were gathering intelligence from everywhere, in a global effort to crowdsource assistance for Haiti. Since the majority of incoming text messages were in Creole, they needed a translation service. And since most reports lacked sufficient location details, they needed a way to quickly identify the GPS coordinates so that incidents could be mapped as accurately as possible. So Meier reached out to dozens of Haitian communities for help, including the large diaspora in Boston.

Sean Wise, a management professor and VC himself, leads one of a growing number of outfits determined to prove that a form of community-powered venture capital can both filter the global wealth of opportunities and channel more intellectual horsepower into making each investment successful. And he’s not just talking about it; he’s doing it—cofounding a company, VenCorps, that uses mass collaboration at every stage of the process. “For Venture Capital 2.0 to succeed,” he says, “there will need to be exponentially more people involved.” Just as Goldcorp used mass collaboration to locate their drilling sites, or Wikipedia crowdsourced the publication of expert articles, or Threadless works with customers to design T-shirts, VenCorps is leveraging collaboration. Wise is deploying the power of mass collaboration, not just in the process of choosing which start-ups to fund, but to help grow those start-up ventures after the investment is made. “VenCorps is basically wikinomics applied to venture capital,” says Wise. The money being invested by VenCorps in small companies comes from their own fund, but the choice of where to invest it belongs to the VenCorps community.

To be clear, collaborative innovation is not about “everybody doing everything,” as critics such as Jaron Lanier have suggested. Nor is it a wholesale replacement for cutting-edge R&D or the art of a good marketing campaign. It’s not about putting product duds in the public domain and hoping that someone will turn them into gold. Nor is it about enticing smart and talented people to give away their valuable ideas for free. Sure, a number of companies have exploited so-called crowdsourcing to get marketing and other services on the cheap. But schemes like these are not sustainable and rarely provide the foundation for a dynamic and fertile business ecosystem. In the most successful instances of mass collaboration, companies carve out meaningful roles for contributors and allow community members to share in the ownership and fruits of their creations. They make their core products modular, reconfigurable, and editable.


pages: 561 words: 114,843

Startup CEO: A Field Guide to Scaling Up Your Business, + Website by Matt Blumberg

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airport security, Albert Einstein, bank run, Broken windows theory, crowdsourcing, deskilling, fear of failure, high batting average, high net worth, hiring and firing, Inbox Zero, James Hargreaves, Jeff Bezos, job satisfaction, Kickstarter, knowledge economy, knowledge worker, Lean Startup, Mark Zuckerberg, minimum viable product, pattern recognition, performance metric, pets.com, rolodex, shareholder value, Silicon Valley, Skype

Those who work diligently at setting their company’s vision and strategy from the beginning not only have more focus, a better framework for decision making and a more unified team; they also end up launching their businesses in different—and much better—ways than they had initially planned. Dave Morgan, CEO, Simulmedia THE TOP-DOWN APPROACH In the early years of a startup, the only way to define your mission, vision, and values is by way of a top-down process. There’s a simple reason for this: at this stage, your company consists almost entirely of co-founders and executives. There is no crowd of employees to crowd-source from. Either the CEO or a few members of the senior team have to sit down and craft these basic statements, being careful to separate the what (mission and strategy) from the how (values). When Return Path turned nine years old, we were ready to take another approach. The company had gone through a major reorganization (we had sold or spun off a several business units and refocused on a new, tightly defined core).

Although they obviously differed a bit here and there, we were pleased that the 12 teams had come up with fairly similar views of the company’s mission, values and strategy. This was less surprising about some aspects than others. For example, I wasn’t surprised that there was a high degree of convergence in the way people thought about the organization’s values since we had a strong values-driven culture that people were living every day, even if those values hadn’t been well articulated in the past. But it was a little surprising that we could effectively crowdsource a strategy statement and key performance metrics at a time when the business was at a fork in the road. Given this degree of alignment, our task as an executive team became less about picking concepts and more about picking words. We worked together to come up with a solid draft that took the best of what was submitted to us. We worked with a copywriter to make the statements flow well. Then we shared the results with the company and opened the floor for comments.

The first thing we decided to do was to pick a different framework. The Collis/Rukstad formula was a little heavy for us. We decided to borrow from Patrick Lencioni’s fantastic book, The Advantage: Why Organizational Health Trumps Everything Else in Business, and answer five simple questions for ourselves: Why do we exist? How do we behave? What do we do? How will we succeed? What is most important, right now? We might have crowdsourced the process again, even with 350 people, if we had felt that we were at a real turning point in the life of the business. Because we viewed this exercise as more of a refresh, we did a hybrid of top-down and bottom-up approaches. This time, we started by working through drafts of the governing document as an executive team. We were able to get to a solid working draft in about three hours. From there, we presented the results at an all-hands meeting and walked the company through the current statements, the logic of needing a refresh, the change in framework, and the working draft.


pages: 398 words: 107,788

Coding Freedom: The Ethics and Aesthetics of Hacking by E. Gabriella Coleman

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Benjamin Mako Hill, crowdsourcing, Debian, dumpster diving, en.wikipedia.org, financial independence, ghettoisation, Hacker Ethic, informal economy, Jacob Appelbaum, Jaron Lanier, Jason Scott: textfiles.com, Jean Tirole, knowledge economy, laissez-faire capitalism, Louis Pasteur, means of production, Paul Graham, pirate software, popular electronics, RFC: Request For Comment, Richard Stallman, rolodex, Ronald Reagan, Silicon Valley, Silicon Valley startup, slashdot, software patent, software studies, Steve Ballmer, Steven Levy, Ted Nelson, the scientific method, The Structural Transformation of the Public Sphere, web application, web of trust

Yet as the domain of free software has grown and matured, it has without doubt shifted the axis of intellectual property law, providing a model that has inspired others to build similar endeavors in various fields stretching from journalism to science. Thus, one of the most profound political effects of free software has been to weaken the hegemonic status of intellectual property law; copyright and patents now have company. Nevertheless, the existence of free software (and the related though distinct digital practices, such as crowdsourcing) should not be mobilized to make overblown assessments of the role of digital media formations in changing the more general political makeup of society. No simple connection between democracy and social media can be sustained (Ginsburg 2008; Hindman 2008; Lovink 2007; Morozov 2011; Rossiter 2007), nor is that what I am advancing here.3 Instead, we should recognize the viable alternatives in a moment when intellectual property law is itself undergoing rapid transformation.

Since the term’s invention, it has not only become the governing metaphor by which to understand contemporary Internet technologies and the social practices that cluster around them. It also has been stretched so far and so wide that it now encompasses software (blogs and wikis), corporate platforms (Flickr, Twitter, Facebook, YouTube, and Myspace), projects and nonprofits (Wikipedia, Debian, and Creative Commons), and collaborative techniques (remixing and crowdsourcing). There are certainly points of connection to be made between these domains, technologies, practices, and projects. Yet this constant conflation obscures far more than it reveals. When used in celebratory terms, Web 2.0 puts on equal footing a user who uploads a video on YouTube or a photo on Flickr (corporate-owned, proprietary platforms) and a free software developer or even a Wikipedian who is part of a nonprofit, collective effort.

In the case of Debian—explored in detail in this book—its policies, direction, and imperatives are decided by a collective that not only creates software but also has been innovative, quite successfully so, in terms of institution building. Just as significant is the fact that free software licensing ensures that the fruits of labor are equally available to all—a condition unmet by many forms of crowdsourced labor, much less ones that unfold on corporate and cloud-based platforms, such as Flickr, where collaboration is said to flourish, and yet where users can lose access to their data when and if the company folds or takes down a service. The politics of F/OSS, narrowly defined though they may be, are obfuscated and severely distorted when they are lumped in with Web 2.0. When the organizational sociologies of these projects are ignored, it is far easier to collapse them into the category of more informal, less coordinated forms of production, thereby obscuring how these distinct forms of production ethically, politically, and economically function.


pages: 310 words: 89,653

The Interstellar Age: Inside the Forty-Year Voyager Mission by Jim Bell

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Albert Einstein, crowdsourcing, dark matter, Edmond Halley, Edward Charles Pickering, en.wikipedia.org, Eratosthenes, gravity well, Isaac Newton, Kuiper Belt, Mars Rover, planetary scale, Pluto: dwarf planet, polynesian navigation, Ronald Reagan, Saturday Night Live, Search for Extraterrestrial Intelligence, Stephen Hawking, V2 rocket

Every spacecraft leaving Earth will have some type of computer, and so we may be establishing a positive precedent with the New Horizons digital message, especially the crowd-sourcing aspect of it. Before, it was just a few of us who were attempting to speak for the Earth. But with New Horizons we’re making a serious effort to involve as much of the Earth as we can. And that’s certainly something I think Carl would have liked.” I’m a member of Jon Lomberg’s advisory board for what is being called the One Earth: New Horizons Message Project, and as we begin ramping up our public engagement in formulating what some are calling the Voyager Golden Record 2.0 message, it will be interesting to see how different today’s crowd-sourced message to the future will be from the message so carefully crafted forty years ago by a select group of people for the Voyager record.

In any case, a group of people led by Jon Lomberg are awaiting expected approval by NASA to upload a yet-to-be-determined “digital interstellar message” into the New Horizons spacecraft’s permanent long-term flash memory once the mission has completed its science objectives. More than ten thousand people from 140 countries signed online petitions to support bringing this message project forward to NASA and the New Horizons project, which no doubt helped the idea gain official approval. The contents of the message—its text, images, art, and/or music—will be crowd-sourced, a distinctively more modern way of soliciting multiple opinions through the Internet. “Previous messages from Earth, portraits of our planet and our species, have been made by small groups of experts,” Jon Lomberg noted. “This initiative proposes that this time, for the first time, the whole world can participate. The Voyager record has become an iconic image of the twentieth century, signifying our emergence as a galactic species.


pages: 340 words: 96,149

@War: The Rise of the Military-Internet Complex by Shane Harris

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Amazon Web Services, barriers to entry, Berlin Wall, Brian Krebs, centralized clearinghouse, clean water, computer age, crowdsourcing, data acquisition, don't be evil, Edward Snowden, failed state, Firefox, Julian Assange, mutually assured destruction, Silicon Valley, Silicon Valley startup, Skype, Stuxnet, uranium enrichment, WikiLeaks, zero day

He says the company employs network forensics and reverse engineering of malware to understand the hackers’ tactics, techniques, and motivations. He is careful to avoid any suggestion that the company breaks in to their adversaries’ computers—the former G-man spent years prosecuting people for violating anti-hacking laws. But the word hunt reveals a more aggressive form of analysis than many other firms in the business will admit to. CrowdStrike deploys sensors on its clients’ networks and uses crowdsourcing to collect more information on hacks as they’re happening, rather than wait for a client to be hit and collect evidence after the fact. It uses intelligence to attribute, as closely as possible, the hacker to a particular country or group. This is one of the hardest things to do in cyber forensics, because skilled hackers conceal their physical location, often by launching their attacks from compromised computers in other countries.

But the day-to-day work of defending critical facilities will be the job of corporations, who will perform the task as well if not better than government. Lockheed Martin and its ilk will create a new business in scanning traffic and applying their proprietary methods for detecting malware and hacker activity—methods that will be based on the real-time intelligence they collect from their own, vast global information networks, as well as those of their customers. It will be a kind of crowdsourcing. Similarly, companies such as CrowdStrike and the newly merged Mandiant and FireEye will promise to protect their customers’ networks from prospective threats, the same way we expect security guards to keep intruders out of our homes and office buildings, not just to investigate the invasion after it happens. The military-Internet complex is like its industrial predecessor insofar as the government has always outsourced national security to some degree.

See also Defense Industrial Base; military-industrial complex counterterrorism, [>]–[>], [>], [>]–[>], [>], [>], [>] crashes, computer, [>]–[>], [>]–[>], [>], [>], [>], [>] credit/debit cards, [>], [>]–[>], [>]–[>], [>], [>], [>], [>]–[>] critical infrastructures: cyber attacks, annual, [>], [>]; cyber attack threat, [>], [>], [>], [>], [>], [>], [>]–[>]; declaration of war issues, [>], [>], [>]; definition, [>], [>], [>]–[>]; executive orders, [>]–[>], [>]–[>], [>] Croom, Charlie, [>], [>], [>], [>] crowdsourcing, [>], [>] CrowdStrike Services, [>]–[>], [>], [>], [>] cryptologists, [>], [>], [>], [>] Cyber Command. See US Cyber Command cybercrime, [>], [>]–[>], [>]–[>], [>]–[>], [>], [>], [>]. See also intellectual property; network forensics cyber espionage, [>], [>], [>], [>], [>], [>]–[>], [>]–[>], [>]. See also China, cyber campaign against the US; spyware cyber espionage by the US: of Americans, [>]–[>], [>], [>], [>]–[>], [>], [>] (see also Fourth Amendment; legal issues, monitoring by the NSA; privacy issues); by companies (see under private sector); by the FBI, [>]–[>]; of foreigners, [>], [>]–[>], [>]–[>], [>], [>], [>], [>]; global telecommunications, [>], [>]–[>], [>], [>], [>] (see also Tailored Access Operations); by Mandiant, [>]–[>]; propaganda, [>], [>], [>], [>], [>]–[>]; of individuals vs. groups of people, [>]–[>]; two reasons for, [>] cyber kill chain, [>]–[>] cyber security: companies (see under private sector); cyber hygiene, [>]; cyber sentry model, [>]; defense tactics, [>], [>]–[>], [>], [>]–[>], [>], [>]–[>], [>]–[>]; enemy among us, [>]–[>]; federal guidelines, [>]; future innovations, [>]–[>]; log-in and password, [>], [>], [>], [>], [>]; as a national priority, [>], [>], [>], [>], [>]; patent rights, [>]; shift from counterterrorism to, [>], [>], [>], [>]; standards development, [>]–[>], [>]–[>], [>]–[>]; used in marketing, [>]–[>].


pages: 163 words: 46,523

The Kickstarter Handbook: Real-Life Success Stories of Artists, Inventors, and Entrepreneurs by Steinberg, Don

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3D printing, crowdsourcing, Kickstarter, Skype, Y Combinator

(Kickstarter keeps 5 percent of all project funding, so the company and its early backers are clearly doing fine financially.) Along the way, a new word was born for a novel way to support arts and invention: crowdfunding. It’s yet another way that the reach of the Internet has been put to work. Thousands of individuals contributed information to help build the free online encyclopedia Wikipedia—that’s crowdsourcing. Turn that into money, and you have crowdfunding, a means of moving money among people, circumventing traditional sources and decision makers and gatekeepers, a sort of grassroots redistribution of wealth. Kickstarter is part of a diverse ecosystem offering new ways for people to connect with one another online, to exchange ideas, stuff, and sometimes hard currency. That universe broadly includes eBay and other auction sites, where buyers and sellers find each other and one person’s extra money is swapped for another person’s vintage vinyl LPs.

Meet Matt Haughey Matt Haughey, backer extraordinaire Matt Haughey is one of those mythical beings: the mysterious benefactor who will pledge money to a Kickstarter project just because he thinks it’s cool, even if he doesn’t know the creator personally. As of March 2012, Haughey had backed eighty-four projects (and almost all of them ended up successfully funded). As an online entrepreneur himself—he created the crowdsourced news site MetaFilter—he appreciates the power of the Web to bring people and ideas together, and he loves the Kickstarter concept. “I feel that artists shouldn’t have to pay for paint. Inspiration should be the limiting factor in art, not cost,” he says. (Through a mutual connection, he became a “very small” [his words] early investor in Kickstarter, but definitely does not speak for the company.)


pages: 179 words: 43,441

The Fourth Industrial Revolution by Klaus Schwab

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3D printing, additive manufacturing, Airbnb, Amazon Mechanical Turk, Amazon Web Services, augmented reality, autonomous vehicles, barriers to entry, Baxter: Rethink Robotics, bitcoin, blockchain, Buckminster Fuller, call centre, clean water, collaborative consumption, conceptual framework, continuous integration, crowdsourcing, disintermediation, distributed ledger, Edward Snowden, Elon Musk, epigenetics, Erik Brynjolfsson, future of work, global value chain, Google Glasses, income inequality, Internet Archive, Internet of things, invention of the steam engine, job automation, job satisfaction, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, life extension, Lyft, megacity, meta analysis, meta-analysis, more computing power than Apollo, mutually assured destruction, Narrative Science, Network effects, Nicholas Carr, personalized medicine, precariat, precision agriculture, Productivity paradox, race to the bottom, randomized controlled trial, reshoring, RFID, rising living standards, Second Machine Age, secular stagnation, self-driving car, sharing economy, Silicon Valley, smart cities, smart contracts, software as a service, Stephen Hawking, Steve Jobs, Steven Levy, Stuxnet, The Spirit Level, total factor productivity, transaction costs, Uber and Lyft, Watson beat the top human players on Jeopardy!, WikiLeaks, winner-take-all economy, women in the workforce, working-age population, Y Combinator, Zipcar

Much of the information and my own analysis in this book are based on ongoing projects and initiatives of the World Economic Forum and has been developed, discussed and challenged at recent Forum gatherings. Thus, this book also provides a framework for shaping the future activities of the World Economic Forum. I have also drawn from numerous conversations I have had with business, government and civil society leaders, as well as technology pioneers and young people. It is, in that sense, a crowd-sourced book, the product of the collective enlightened wisdom of the Forum’s communities. This book is organized in three chapters. The first is an overview of the fourth industrial revolution. The second presents the main transformative technologies. The third provides a deep dive into the impact of the revolution and some of the policy challenges it poses. I conclude by suggesting practical ideas and solutions on how best to adapt, shape and harness the potential of this great transformation. 1.

Table 2: Examples of professions most and least prone to automation Source: Carl Benedikt Frey and Michael Osborne, University of Oxford, 2013 It is interesting to note that it is not only the increasing abilities of algorithms, robots and other forms of non-human assets that are driving this substitution. Michael Osborne observes that a critical enabling factor for automation is the fact that companies have worked hard to define better and simplify jobs in recent years as part of their efforts to outsource, off-shore and allow them to be performed as “digital work” (such as via Amazon’s Mechanical Turk, or MTurk, service, a crowdsourcing internet marketplace). This job simplification means that algorithms are better able to replace humans. This job simplification means that algorithms are better able to replace humans. Discrete, well-defined tasks lead to better monitoring and more high-quality data around the task, thereby creating a better base from which algorithms can be designed to do the work. In thinking about the automation and the phenomenon of substitution, we should resist the temptation to engage in polarized thinking about the impact of technology on employment and the future of work.


pages: 58 words: 12,386

Big Data Glossary by Pete Warden

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business intelligence, crowdsourcing, fault tolerance, information retrieval, linked data, natural language processing, recommendation engine, web application

Protocol Buffers An open sourced version of the system that Google uses internally on most of its projects, the Protocol Buffers stack is an IDL similar to Thrift. One difference is that Thrift includes network client and server code in its generated stubs, whereas protobuf limits its scope to pure serialization and deserialization. The biggest differentiator between the two projects is probably their developer base. Though the code is open source, Google is the main contributor and driver for Protocol Buffers, whereas Thrift is more of a classic crowd-sourced project. If your requirements skew towards stability and strong documentation, Protocol Buffers is going to be attractive, whereas if you need a more open, community-based approach, Thrift will be a lot more appealing. About the Author A former Apple engineer, Pete Warden is the founder of OpenHeatMap, and writes on large-scale data processing and visualization. Colophon


pages: 50 words: 15,603

Orwell Versus the Terrorists: A Digital Short by Jamie Bartlett

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augmented reality, barriers to entry, bitcoin, blockchain, crowdsourcing, cryptocurrency, Edward Snowden, ethereum blockchain, Kuwabatake Sanjuro: assassination market, Satoshi Nakamoto, technoutopianism, Zimmermann PGP

This, argued Bell, wasn’t illegal, it was just a type of gambling. But here’s the ruse: if enough people were sufficiently angry with a particular individual – each anonymously contributing just a few dollars – the prize pool would become so large that someone would be incentivised to make a prediction and then fulfil it themselves in order to take the pot. This is where encrypted messages and untraceable payment systems come in. A crowd-sourced – and untraceable – murder would unfold as follows. First, the would-be assassin sends his prediction in an encrypted message that can be opened only by a digital code known to the person who sent it. He then makes the kill and sends the organisation that code, which would unlock his (correct) prediction. Once verified by the organisation, presumably by watching the news, the prize money – in the form of a digital currency donated to the pot – would be publicly posted online as an encrypted file.


pages: 348 words: 39,850

Data Scientists at Work by Sebastian Gutierrez

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Albert Einstein, algorithmic trading, bioinformatics, bitcoin, business intelligence, chief data officer, clean water, cloud computing, computer vision, continuous integration, correlation does not imply causation, crowdsourcing, data is the new oil, DevOps, domain-specific language, follow your passion, full text search, informal economy, information retrieval, Infrastructure as a Service, inventory management, iterative process, linked data, Mark Zuckerberg, microbiome, Moneyball by Michael Lewis explains big data, move fast and break things, natural language processing, Network effects, nuclear winter, optical character recognition, pattern recognition, Paul Graham, personalized medicine, Peter Thiel, pre–internet, quantitative hedge fund, quantitative trading / quantitative finance, recommendation engine, Renaissance Technologies, Richard Feynman, Richard Feynman, self-driving car, side project, Silicon Valley, Skype, software as a service, speech recognition, statistical model, Steve Jobs, stochastic process, technology bubble, text mining, the scientific method, web application

Tunkelang: We use the usual tricks of the data science trade—machine learning models, A/B testing, crowdsourced evaluation, data collection, and similar techniques. Most importantly, we look at data and logs below the aggregate level. It’s easy to be lazy and look at aggregates—for example, favoring one machine-learned model over another because it performs better on average. Drilling down into the differences and looking at specific examples is often what gives us a real understanding of what’s going on. Gutierrez: What nascent tool are you most excited about? Tunkelang: I’m not sure it still qualifies as nascent, but I’m very excited about human computation. I can’t imagine data science today without crowdsourcing for data collection and evaluation. For example, I’m studying Italian using Duolingo, a free language-learning app that doubles as a crowdsourced text translation platform.

You would think that a company like Facebook would not have any reasons to publish the research they do internally because it would be telling competitors what they do. But, in fact, there is a big incentive to do this. The incentive is that for projects that are very upstream of applications, but even for projects that are very close to applications, the best way to measure the quality of what you’re doing is to test your methods on some standard data set or measure yourself through the kind of formal crowd-sourcing that peer review is. And for projects that are far from products, it’s a much more accurate process than internal evaluation despite all its shortcomings. www.it-ebooks.info Data Scientists at Work Submitting yourself to the scrutiny of the scientific community is a much better way of evaluating the quality of a piece of work than internal evaluation. It’s very difficult for a small number of people who may not be specialists to critically evaluate a piece of work within a company.This type of evaluation essentially leads to internal hype.

Kohavi, Ronny (speaker), 34 LinkedIn, 27, 34 low level process, 22, 29 marketing organization, 22 Max, 40 metadata, 26 motivated people, 22 non–data scientist, 23 non-numerical data, 40 on-demand Internet media, 19 one-on-one talks, 28 operations research, 23 personalization algorithms and recommender systems, 21 personalization model, 24, 27 Poisson distributions, 41 predictive model, 23, 29–30, 37, 43 probability distributions, 41 product org, 20 qualitative research, 26 regression model, 38 research path, 31 riveting and exciting experience, 20 search autocomplete, 21 self-selection, 38 source data, 27 streaming score, 30 studying models, 27 tackling implications, 31 technology selection, 34 Teradata, 33 text analytics, 40 thought process, 25 time, projects, and priorities, 31 tool-set knowledge, 36 viewing data, 24 VP of Science and Algorithms, Netflix, 19 Smith, Anna analytics engineer, 199 big transition, 202 Bitly, 204, 213 conferences, 214 data science interviews, 213 data scientist, 199 disciplines, 215 domain experience, 215 high bullshit radar, 215 humility, 215 outside of work, 216 Reddit data, 215 Twitter, 214 work and learning, 214 blog, 201 business development person and myself, 202 communication, 203 computer science–related work, 201 data science, 204 eBay and Amazon, 201 galaxy project, 200 Hadoop cluster, 202 informatics and data science–type, 200 information, 204 JSON format, 204 machine learning algorithms, 201 MapReduce program, 204 mathematics, 213 normalization technique, 203 Personality-wise, 205 physics, 204 pretty and understandable, 203 problem approach, 213 problem solving and thinking, 205 project-based metrics, 212 quantum computers, 200 recommendations system, 212 Rent the Runway, 204 assumption, 210 body measurements and fit, 207 champion data, 206 cohesive community, 218 collaborative effort, 206 collaborative supportive community, 211 comfortable and expose personal details, 211 consulting-type team role, 206 CTO, 206 customary data engineering, 207 customer support piece, 207 D3.js tools, 209 data guarding, 217 data scientist, 210 display behavior, 210 distance metric, 208 dress size, 208 ego-driven field, 218 fabrics, 208 www.it-ebooks.info Index fashion industry, 206 feedback and opinions, 217 fun projects, 216 Google analytics, 209 in New York, 218, 219 knowledge and insights, 216 latent variable, 210 marketing and the financial reports, 205 mobile devices, 209 non-data pieces, 205 operations side, 205 personal feedback mechanism, 211 pixel logs, 208 positivity and patience, 218 Python, 209 real-world physical attributes, 211 reviews, 211 right dress, 211 strategy, 217 systems and frameworks, 205 Tableau reports, 205 Team Geek, 217 variations, 208 warehouse operations piece, 206 warehouse-to-consumer-and-back piece, 207 web-site operations piece, 207 Runway product, 200 slow transition, 201 social commitment, 199 statistical confidence, 203 trial and error, 203 websites, 202 Statistical pattern recognition, 48 Sunlight Foundation, 319 T Techmeme and Prismatic, 95 Teradata, 33, 319 Tunkelang, Daniel AT&T Bell Labs, 83 Bill Gates, 103 challenging problems, 85 Chief Scientist, Endeca, 83 cocktail party, 94 communication, 97 compare and contrast, 85 conservative assumptions, 99 crazy and novel ideas, 98 creative problem solvers, 100 crowdsourcing, 97 customers’ data, 93 data science, 92, 102, 104 data science trade, 97 data types, 95 decision tree model, 90 digital library, 93 economic graph, 88 economic opportunity, 88 entropy calculations, 93 Galene, 87 Google, 89, 91 head of Search Quality, LinkedIn, 83–84 health and well-being, 104 hiring and outreach, 95 hiring and training people, 102 hiring process, 101 human–computer interaction, 86 hypothesis generation, 96 IBM Thomas J.


pages: 272 words: 83,378

Digital Barbarism: A Writer's Manifesto by Mark Helprin

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Albert Einstein, anti-communist, Berlin Wall, carbon footprint, computer age, crowdsourcing, hive mind, invention of writing, Jacquard loom, Jacquard loom, Plutocrats, plutocrats, race to the bottom, semantic web, Silicon Valley, Silicon Valley ideology, the scientific method, Yogi Berra

But that it is an echo chamber is the choice and view of those who recoil from independent thought. As in the worst of medieval scholasticism, they dare not venture beyond the rim of received authority lest they fall off the edge of the earth. To help those who cannot face the terror of doing something independently, the electronic age has provided WEbook,™ which, according to the Washington Post, “by adopting the growing crowd-sourcing model [“Crowd-sourcing” was invented by sheep.]…hopes to help frustrated writers realize their potential…. Members can help one another overcome writer’s block” (if you have writer’s block you should heed it as you would heed a cobra), and the company has an employee who (Tolstoy would have appreciated this) “makes the final call in disagreements between writers or helps moderate brainstorming sessions.”103 Such stunning mental dependency was often evident in the voluminous reaction to my single editorial piece, and may have been inspired there from the top down, by the leader of the movement, Lawrence Lessig, who is also and not coincidentally a passionate advocate of “remix,” or, in my terminology, Legos.™ Taking a work that someone else has made, chopping it up, and rearranging it, perhaps adding or subtracting elements according to whim, is a favored “art” form of a generation weaned on push-button alternate endings and Microsoft’s “cut and paste.”


pages: 298 words: 81,200

Where Good Ideas Come from: The Natural History of Innovation by Steven Johnson

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Ada Lovelace, Albert Einstein, Alfred Russel Wallace, carbon-based life, Cass Sunstein, cleantech, complexity theory, conceptual framework, cosmic microwave background, crowdsourcing, data acquisition, digital Maoism, discovery of DNA, Dmitri Mendeleev, double entry bookkeeping, double helix, Douglas Engelbart, Drosophila, Edmond Halley, Edward Lloyd's coffeehouse, Ernest Rutherford, Geoffrey West, Santa Fe Institute, greed is good, Hans Lippershey, Henri Poincaré, hive mind, Howard Rheingold, hypertext link, invention of air conditioning, invention of movable type, invention of the printing press, invention of the telephone, Isaac Newton, Islamic Golden Age, Jacquard loom, James Hargreaves, James Watt: steam engine, Jane Jacobs, Jaron Lanier, John Snow's cholera map, Joseph Schumpeter, Joseph-Marie Jacquard, Kevin Kelly, lone genius, Louis Daguerre, Louis Pasteur, Mason jar, Mercator projection, On the Revolutions of the Heavenly Spheres, online collectivism, packet switching, PageRank, patent troll, pattern recognition, price mechanism, profit motive, Ray Oldenburg, Richard Florida, Richard Thaler, Ronald Reagan, side project, Silicon Valley, silicon-based life, six sigma, Solar eclipse in 1919, spinning jenny, Steve Jobs, Steve Wozniak, Stewart Brand, The Death and Life of Great American Cities, The Great Good Place, The Wisdom of Crowds, Thomas Kuhn: the structure of scientific revolutions, transaction costs, urban planning

The coffeehouse model of creativity helps explain one of those strange paradoxes of twenty-first-century business innovation. Even as much of the high-tech culture has embraced decentralized, liquid networks in their approach to innovation, the company that is consistently ranked as the most innovative in the world—Apple—remains defiantly top-down and almost comically secretive in its development of new products. You won’t ever see Steve Jobs or Jonathan Ive crowdsourcing development of the next-generation iPhone. If open and dense networks lead to more innovation, how can we explain Apple, which on the spectrum of openness is far closer to Willy Wonka’s factory than it is to Wikipedia? The easy answer is that Jobs and Ive simply possess a collaborative genius that has enabled the company to ship such a reliable stream of revolutionary products. No doubt both men are immensely talented at what they do, but neither of them can design, build, program, and market a product as complex as the iPhone on their own, the way Jobs and Steve Wozniak crafted the original Apple personal computer in the now-legendary garage.

We have, all of us, seen firsthand how innovative a space the Web can be, and we have assembled a great deal of local knowledge about the forces that make that innovation possible. In assembling the seven patterns of innovation, I have tried to organize that knowledge into productive categories, and I hope I have provided a few insights into how the Web works that will surprise the natives. But even the most devoted crowd-sourcing, microblogging Wikipedia-head has doubts about how portable the Web experience is to real-world innovation environments. Just because the patterns work for Google doesn’t mean that they are relevant for an understaffed nonprofit, or auto-parts manufacturer, or city government. And so one way to think about the pages that follow is as an argument that the particular magic that we have seen on the Web has a long history that predates the Web and can be reproduced in other environments. 4 Patents actually have a complicated historical relationship to the idea of open information networks.

The Empathy Exams: Essays by Leslie Jamison

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Atul Gawande, crowdsourcing, Hernando de Soto, In Cold Blood by Truman Capote, land reform, Skype, Slavoj Žižek

It seems likely that for all her wound has given her—perspective, the grit of survival, an insightful meditation on beauty—Grealy would still trade back these wound boons for a pretty face. This confession of willingness is her greatest gift of honesty, not arguing that beauty was more important than profundity, just admitting that she might have chosen it—that beauty was more difficult to live without. Interlude: Outward When I started writing this essay, I decided to crowdsource. I wrote a message to some of my favorite women asking them to tell me about their thoughts on female pain. “Please don’t not-respond,” I wrote; “it would make me feel totally alone in my obsession with gendered woundedness.” They responded. “Perhaps too obvious,” wrote a friend in divinity school, “but the fall?” She pointed out that Eve is defined by the pain of childbirth. Another friend suggested that perhaps childbirth shapes women as a horizon of anticipation.

Decades ago, for another context, E. M. Cioran once dubbed Jamison’s rare and beautiful mode “thinking against oneself,” and her formal embodiments of her self-suspicion are as dazzling as tough-minded—her casually bravura recital of a random street attack via Propp’s Morphology of the Folktale, the infinite regressions of her medical acting, where “Leslie Jamison” is another case study, the collage and crowdsourcing of her “Grand Unified Theory of Female Pain,” and the contrapuntal staccato inside her lyricism. “I kept running into an opacity at the core of bodily experience,” she says, “a resistance to language, an empty center: how can pain mean? … The essays in this book were memoir until they couldn’t stand to be memoir anymore.” Robert Polito May 2013 A Conversation with Leslie Jamison This interview between Leslie Jamison and Merve Emre originally appeared in Paris Review Daily and is reprinted here with permission.


pages: 224 words: 64,156

You Are Not a Gadget by Jaron Lanier

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1960s counterculture, accounting loophole / creative accounting, additive manufacturing, Albert Einstein, call centre, cloud computing, crowdsourcing, death of newspapers, digital Maoism, Douglas Hofstadter, Extropian, follow your passion, hive mind, Internet Archive, Jaron Lanier, jimmy wales, John Conway, John von Neumann, Kevin Kelly, Long Term Capital Management, Network effects, new economy, packet switching, PageRank, pattern recognition, Ponzi scheme, Ray Kurzweil, Richard Stallman, Silicon Valley, Silicon Valley startup, slashdot, social graph, stem cell, Steve Jobs, Stewart Brand, Ted Nelson, telemarketer, telepresence, The Wisdom of Crowds, trickle-down economics, Turing test, Vernor Vinge, Whole Earth Catalog

If we can’t reformulate digital ideals before our appointment with destiny, we will have failed to bring about a better world. Instead we will usher in a dark age in which everything human is devalued. This kind of devaluation will go into high gear when information systems become able to act without constant human intervention in the physical world, through robots and other automatic gadgets. In a crowdsourced world, the peasants of the noosphere will ride a dismal boomerang between gradual impoverishment under robot-driven capitalism and a dangerously sudden, desperate socialism. The Only Product That Will Maintain Its Value After the Revolution There is, unfortunately, only one product that can maintain its value as everything else is devalued under the banner of the noosphere. At the end of the rainbow of open culture lies an eternal spring of advertisements.

A lot of such layers become a system unto themselves, one that functions apart from the reality that is obscured far below. Making money in the cloud doesn’t necessarily bring rain to the ground. The Big N Here we come to one way that the ideal of “free” music and the corruption of the financial world are connected. Silicon Valley has actively proselytized Wall Street to buy into the doctrines of open/free culture and crowdsourcing. According to Chris Anderson, for instance, Bear Stearns issued a report in 2007 “to address pushback and other objections from media industry heavyweights who make up a big part of Bear Stearns’s client base.” What the heavyweights were pushing back against was the Silicon Valley assertion that “content” from identifiable humans would no longer matter, and that the chattering of the crowd with itself was a better business bet than paying people to make movies, books, and music.


pages: 267 words: 82,580

The Dark Net by Jamie Bartlett

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3D printing, 4chan, bitcoin, blockchain, brain emulation, carbon footprint, crowdsourcing, cryptocurrency, deindustrialization, Edward Snowden, Filter Bubble, Francis Fukuyama: the end of history, global village, Google Chrome, Howard Rheingold, Internet of things, invention of writing, Johann Wolfgang von Goethe, Julian Assange, Kuwabatake Sanjuro: assassination market, life extension, litecoin, Mark Zuckerberg, Marshall McLuhan, moral hazard, Occupy movement, pre–internet, Ray Kurzweil, Satoshi Nakamoto, Skype, slashdot, technological singularity, technoutopianism, Ted Kaczynski, The Coming Technological Singularity, Turing test, Vernor Vinge, WikiLeaks, Zimmermann PGP

This, argued Bell, wasn’t illegal, it was just a type of gambling. But here’s the ruse: if enough people were sufficiently angry with a particular individual – each anonymously contributing just a few dollars – the prize pool would become so large that someone would be incentivised to make a prediction and then fulfil it themselves in order to take the pot. This is where encrypted messages and untraceable payment systems come in. A crowd-sourced – and untraceable – murder would unfold as follows. First, the would-be assassin sends his prediction in an encrypted message that can be opened only by a digital code known to the person who sent it. He then makes the kill and sends the organisation that code, which would unlock his (correct) prediction. Once verified by the organisation, presumably by watching the news, the prize money – in the form of a digital currency donated to the pot – would be publicly posted online as an encrypted file.

It is second nature to people like Amir, but most people don’t know how to browse the net anonymously using Tor, how to pay with Bitcoin, or how to send a message encrypted with PGP. A crypto-party is a small workshop to show them how. It’s typically twenty or so people being walked through the basics of online security by volunteer experts, free to attend and often held in someone’s home, at a university, or even a pub. Wolf’s tweet sparked a global, grass-roots movement.fn4 There is even a free crypto-party handbook, which was crowdsourced in less than twenty-four hours by activists all over the world, and continues to be publicly edited and updated. Shortly after the Snowden revelations, a group of privacy activists held a very large crypto-party on the campus of Goldsmiths, University of London. I joined around two hundred people, all of whom wanted to learn how to stay anonymous online. In packed workshop sessions, each one hour long, we learned how to use Tor to browse anonymously; how to spend Bitcoins; how to use PGP.


pages: 237 words: 64,411

Humans Need Not Apply: A Guide to Wealth and Work in the Age of Artificial Intelligence by Jerry Kaplan

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Affordable Care Act / Obamacare, Amazon Web Services, asset allocation, autonomous vehicles, bank run, bitcoin, Brian Krebs, buy low sell high, Capital in the Twenty-First Century by Thomas Piketty, combinatorial explosion, computer vision, corporate governance, crowdsourcing, en.wikipedia.org, Erik Brynjolfsson, estate planning, Flash crash, Gini coefficient, Goldman Sachs: Vampire Squid, haute couture, hiring and firing, income inequality, index card, industrial robot, invention of agriculture, Jaron Lanier, Jeff Bezos, job automation, John Maynard Keynes: Economic Possibilities for our Grandchildren, Loebner Prize, Mark Zuckerberg, mortgage debt, natural language processing, Own Your Own Home, pattern recognition, Satoshi Nakamoto, school choice, Schrödinger's Cat, Second Machine Age, self-driving car, sentiment analysis, Silicon Valley, Silicon Valley startup, Skype, software as a service, The Chicago School, Turing test, Watson beat the top human players on Jeopardy!, winner-take-all economy, women in the workforce, working poor, Works Progress Administration

Imagine a clothing store where you are photographed in several different outfits, and the images are immediately (and anonymously, by obscuring your face) posted to a special website where visitors can offer their opinion as to which one makes you look slimmer. Within seconds, you get objective, statistically reliable feedback from impartial strangers, who earn points if you complete a purchase. (This concept is called “crowdsourcing.”) Why put your faith in a salesperson motivated by commission when you can find out for sure? Reflecting these two different effects of automation on labor (replacing workers and rendering skills obsolete), economists have two different names for the resulting unemployment. The first is “cyclical,” meaning that people are cycling in and out of jobs.5 In bad times, the pool of people who are between jobs may grow, leading to higher unemployment.

See moral agency conservatives, 162, 163, 187 consumer behavior: Amazon pricing policies and, 99–101, 103–4 automated tracking/analysis of, 55, 64–75, 90, 92, 96–105, 178 as class signifier, 109, 117 comparison shopping and, 54, 100 purchasing power and, 115 targeted website ads based on, 64–75 wealth and, 57, 109, 110–11, 112, 114, 117–18, 165–66 contracts, 90, 97, 202 synthetic intellect rights to, 91, 199–201 voiding of, 88 cookies (computer hard drive notations), 65–69 cooking, 6, 39, 47 Cornell University, 24 corporations: employees as agents of, 82–83 family-owned vs. broad ownership of, 177–82 high PBI index of, 15, 181 legal personhood of, 90, 215n9 as liability insulation, 91 moral agency of, 80, 87 punishment of, 87–88 synthetic intellect parallel, 90, 199–200 tax benefits for, 14, 177, 180–81 coupons, 105 CPM (cost per thousand), 71 credit cards, 89, 96 crime, 80, 82–88 crop picking, 39, 141 CROPS (Clever Robots for Crops program), 143 crowdsourcing, 136 C3PO (milquetoast humanoid), 40 customers. See consumer behavior cyberspace, 37 cyclical unemployment, 136–37, 219n5 dark factory, 200 DARPA (Defense Advanced Research Projects Agency), 95 Dartmouth College, 215n9 data, 7, 36, 45, 48, 51, 67 commercial importance of, 96–97, 98, 103 sharing of, 28 speed of analysis of, 53, 68, 103–4 unnormalized, 53–54 Data Mining, 152 debt, 156, 176 Deepwater Horizon.


pages: 252 words: 72,473

Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy by Cathy O'Neil

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Affordable Care Act / Obamacare, Bernie Madoff, big data - Walmart - Pop Tarts, call centre, carried interest, cloud computing, collateralized debt obligation, correlation does not imply causation, Credit Default Swap, credit default swaps / collateralized debt obligations, crowdsourcing, Emanuel Derman, housing crisis, illegal immigration, Internet of things, late fees, medical bankruptcy, Moneyball by Michael Lewis explains big data, new economy, obamacare, Occupy movement, offshore financial centre, payday loans, peer-to-peer lending, Peter Thiel, Ponzi scheme, prediction markets, price discrimination, quantitative hedge fund, Ralph Nader, RAND corporation, recommendation engine, Sharpe ratio, statistical model, Tim Cook: Apple, too big to fail, Unsafe at Any Speed, Upton Sinclair, Watson beat the top human players on Jeopardy!, working poor

After all, to police the WMDs we need people with the skills to build them. Their research tools can replicate the immense scale of the WMDs and retrieve data sets large enough to reveal the imbalances and injustice embedded in the models. They can also build crowdsourcing campaigns, so that people across society can provide details on the messaging they’re receiving from advertisers or politicians. This could illuminate the practices and strategies of microtargeting campaigns. Not all of them would turn out to be nefarious. Following the 2012 presidential election, for example, ProPublica built what it called a Message Machine, which used crowdsourcing to reverse-engineer the model for the Obama campaign’s targeted political ads. Different groups, as it turned out, heard glowing remarks about the president from different celebrities, each one presumably targeted for a specific audience.


pages: 268 words: 74,724

Who Needs the Fed?: What Taylor Swift, Uber, and Robots Tell Us About Money, Credit, and Why We Should Abolish America's Central Bank by John Tamny

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Airbnb, bank run, banks create money, Bernie Madoff, bitcoin, Bretton Woods, Carmen Reinhart, correlation does not imply causation, Credit Default Swap, crony capitalism, crowdsourcing, Donald Trump, Downton Abbey, fiat currency, financial innovation, Fractional reserve banking, full employment, George Gilder, Home mortgage interest deduction, Jeff Bezos, job automation, Joseph Schumpeter, Kenneth Rogoff, Kickstarter, liquidity trap, Mark Zuckerberg, market bubble, moral hazard, mortgage tax deduction, NetJets, offshore financial centre, oil shock, peak oil, Peter Thiel, price stability, profit motive, quantitative easing, race to the bottom, Ronald Reagan, self-driving car, sharing economy, Silicon Valley, Silicon Valley startup, Steve Jobs, The Wealth of Nations by Adam Smith, too big to fail, Uber for X, War on Poverty, yield curve

Imagine the U.S. economy without the advances that nontraditional forms of finance provided credit for. Returning to Spike Lee, his early successes made him bankable in Hollywood. But in 2014, he turned to Kickstarter to attain $1.25 million in financing for Da Sweet Blood of Jesus. Kickstarter is a website where the creative go to find investors for their projects. They set a number they’d like to raise, and if successful they find individuals eager to “crowd-source” whatever project it is they seek funds for. The investors acquire a stake in the creative dream of others who need credit to animate their dreams. Capitalism is always and everywhere a two-way street. Explaining his utilization of Kickstarter to The Economist, Lee observed that traditional movie studios “are looking for tent-pole movies, movies that make a billion dollars, open on the same day all around the world.

., 157–58 The Battle of Bretton Woods (Steil), 95, 169 Bear Stearns, 120 Beatty, Warren, 23–24, 28 Beckworth, David, 138–39 Berkshire Hathaway, 62, 85 Bernanke, Ben, 41–47, 72, 106, 128, 149, 154, 164 Bezos, Jeff, 59, 97–98, 150 Biden, Joe, 59 billion-dollar “unicorn” companies, 28, 148 Biography of the Dollar (Karmin), 100 Bitcoin, 144 Blinder, Alan, 1 Bloomberg news organization, 42 Blumenthal, Michael, 117, 170 Bonnie & Clyde (film), 23 Brady, Tom, 16 Bretton Woods monetary conference, 95, 169 Brookes, Warren, 49, 50, 69, 72, 97 Brown, James, 25 Buffett, Warren, 59, 62, 78, 85, 150 Burns, Arthur, 169, 170 Bush, George W., 71, 72–73, 118–19, 121, 171 cab fares during periods of heavy demand, 11–12 Candy, John, 22 Capital City (Kessner), 30 capitalism credit and crowdsourcing, 110 failure as feature of, 58, 89, 100, 125 and filling of unmet needs, 112, 179 turning scarcity into abundance, 53–54, 81 car companies, 56–57 car manufacturing process, 65–66 Carroll, Pete, 18–20 Carter, Jimmy, 117, 170 Cassel, Gustav, 119 Cato Institute, 135 The CEO Tightrope (Trammell), 123–24 The Changed Face of Banking (Smith), 111, 129 Chinese economy, 94, 96, 118, 135–36, 137, 138 Chinese stock market, 152–53 Citadel hedge fund, 41, 42, 43 Citigroup, 128 Cleveland, Ohio, 137–38 Clinton, Bill, 51–52, 71, 72, 171 Clinton, Hillary, 48, 51–52, 59 coaching and recruiting of college athletes, 15–21, 78–79 Cochrane, John, 102 computer company failures, 57 Congress.


pages: 98 words: 25,753

Ethics of Big Data: Balancing Risk and Innovation by Kord Davis, Doug Patterson

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4chan, business process, corporate social responsibility, crowdsourcing, en.wikipedia.org, Mahatma Gandhi, Mark Zuckerberg, Netflix Prize, Occupy movement, performance metric, side project, smart grid, urban planning

The more such additional data is available (in addition to more easily accessible tools and computing resources), the easier it is to reattach supposedly “anonymous” data sets to canonical “personally identifying information” such as name, address, and phone number. In one widely cited study, for instance, researchers were able to reidentify many users from an “anonymized” data set released by Netflix for the purposes of crowd-sourcing recommendation algorithms by comparing it to user profiles on IMDB (http://www.securityfocus.com/news/11497). You might not think that a few movie ratings could be “personally identifying information,” but given the right auxiliary information, they are. In the opening quote to this chapter, Ohm was talking specifically about the particular sense of the word “anonymous” that relates to an individual’s personal privacy.


pages: 103 words: 24,033

The Immigrant Exodus: Why America Is Losing the Global Race to Capture Entrepreneurial Talent by Vivek Wadhwa

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3D printing, card file, corporate governance, crowdsourcing, Elon Musk, immigration reform, labour mobility, open economy, pattern recognition, Ray Kurzweil, Sand Hill Road, Silicon Valley, Silicon Valley startup, software as a service, Y2K

The irony is that the majority of these skilled immigrants, and the thousands of startup founders who have been barred from getting a visa, remain intent on obtaining one. Despite treatment from the US government that many I spoke with called “insulting” or “humiliating,” most remained willing to go through great effort and expense in this quest for the opportunity to legally work and build a company in America. For example, Mayel de Borniol tried to launch his company, Babelverse, in Chile after US immigration policies forced him out. The crowd-sourced translation company was selected as a winner at a major technology conference and received offers of significant funding. De Borniol is still fighting to get a visa that will allow him to work and build his startup in the United States. Immigrants Anand and Shikha Chhatpar built a burgeoning Facebook games company in the United States. Immigration officials unexpectedly forced them out in 2010.


pages: 72 words: 21,361

Race Against the Machine: How the Digital Revolution Is Accelerating Innovation, Driving Productivity, and Irreversibly Transforming Employment and the Economy by Erik Brynjolfsson

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Amazon Mechanical Turk, Any sufficiently advanced technology is indistinguishable from magic, autonomous vehicles, business process, call centre, combinatorial explosion, corporate governance, crowdsourcing, David Ricardo: comparative advantage, easy for humans, difficult for computers, Erik Brynjolfsson, factory automation, first square of the chessboard, first square of the chessboard / second half of the chessboard, Frank Levy and Richard Murnane: The New Division of Labor, hiring and firing, income inequality, job automation, John Maynard Keynes: technological unemployment, Joseph Schumpeter, Khan Academy, Kickstarter, knowledge worker, labour mobility, Loebner Prize, low skilled workers, minimum wage unemployment, patent troll, pattern recognition, Ray Kurzweil, rising living standards, Robert Gordon, self-driving car, shareholder value, Skype, too big to fail, Turing test, Tyler Cowen: Great Stagnation, Watson beat the top human players on Jeopardy!, winner-take-all economy

Decouple benefits from jobs to increase flexibility and dynamism. Tying health care and other mandated benefits to jobs makes it harder for people to move to new jobs or to quit and start new businesses. For instance, many a potential entrepreneur has been blocked by the need to maintain health insurance. Denmark and the Netherlands have led the way here. 15. Don’t rush to regulate new network businesses. Some observers feel that “crowdsourcing” businesses like Amazon’s Mechanical Turk exploit their members, who should therefore be better protected. However, especially in this early, experimental period, the developers of these innovative platforms should be given maximum freedom to innovate and experiment, and their members’ freely made decisions to participate should be honored, not overturned. 16. Eliminate or reduce the massive home mortgage subsidy.


pages: 94 words: 26,453

The End of Nice: How to Be Human in a World Run by Robots (Kindle Single) by Richard Newton

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3D printing, Black Swan, British Empire, Buckminster Fuller, Clayton Christensen, crowdsourcing, deliberate practice, fear of failure, Filter Bubble, future of work, Google Glasses, Isaac Newton, James Dyson, Jaron Lanier, Jeff Bezos, job automation, Lean Startup, low skilled workers, Mark Zuckerberg, move fast and break things, Paul Erdős, Paul Graham, recommendation engine, rising living standards, Robert Shiller, Robert Shiller, Silicon Valley, Silicon Valley startup, skunkworks, Steve Ballmer, Steve Jobs, Y Combinator

This is how you leap-frog the robot hordes. Cruelly, just when original, idiosyncratic, deep thought becomes more important to a good life, it has become exponentially easier to do the reverse, to conform and think the same as everyone else. In other words, it is precisely because you are connected to all the knowledge in the world that to stop and think original thoughts just got harder. Because you live in a crowd-sourced, socially-and-globally-connected accelerated world you can learn with a sweep of your index finger what choices will conform with and win the approval of your peers. It’s never been easier to be nice. Social decision-making apps will enable you to poll your social network for their opinion on anything: from what shoes to wear to how to have your eggs served to what music to listen to or who to vote for.


pages: 514 words: 152,903

The Best Business Writing 2013 by Dean Starkman

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Asperger Syndrome, bank run, Basel III, call centre, clean water, cloud computing, collateralized debt obligation, Columbine, computer vision, Credit Default Swap, credit default swaps / collateralized debt obligations, crowdsourcing, Erik Brynjolfsson, eurozone crisis, Exxon Valdez, factory automation, full employment, Goldman Sachs: Vampire Squid, hiring and firing, hydraulic fracturing, income inequality, jimmy wales, job automation, late fees, London Whale, low skilled workers, Mahatma Gandhi, market clearing, Maui Hawaii, Menlo Park, Occupy movement, oil shale / tar sands, price stability, Ray Kurzweil, Silicon Valley, Skype, sovereign wealth fund, stakhanovite, Steve Jobs, Stuxnet, the payments system, too big to fail, Vanguard fund, wage slave, Y2K

During a meeting in New York City, an executive at one of the nation’s largest sports media companies quipped that Bleacher Report’s new strategy was akin to spritzing a little room deodorizer after leaving a steaming deposit in the toilet and failing to flush. An attendee recalls everyone laughing uproariously. In August of this year, Turner Broadcasting announced it was quite willing to put its logo next to Bleacher Report’s, scooping up the website for a purported $200 million. Bleacher Report has joined the Huffington Post in the exclusive club of Web properties converting free, crowd-sourced content into nine-digit paydays. The transaction was not just a valuation, but a validation. “Information has become more important than the source of information,” says Michael Hall, director of new media for the New England Sports Network. In today’s world, information is money—and few move information faster or more efficiently than Bleacher Report and its roughly 6,000 contributors. “They understand, probably better than any media outlet today, the exact value generated for them for every monthly unique visitor, every pageview served,” continues Hall.

“I can guarantee you that there are other publications out there that have frameworks on par with Bleacher Report’s,” he says. “So, ultimately, what’s their biggest differentiator? Free content!” Bleacher Report’s volunteer army generates scads of material—and the money the site doesn’t spend on writers is spent to move the company where it wants to go. It couldn’t get there, however, without addressing the pitfalls of crowdsourcing and lowest-common-denominator crap Kaufman mentioned to Google. So, in the last two years, the site has worked to rehabilitate its image: Would-be writers must gain admittance via a process that rejects seventeen out of every twenty applicants. Lead writers and knowledgeable featured columnists have been added to the roster, and many of the site’s early contributors have been bounced. “A few years ago I couldn’t look at their site without my eyes bleeding and my head pounding,” says veteran sports journalist Kevin Blackistone.

This would provide a leg up in bidding for whatever comes next. “By expanding their set of assets, it allows Turner to go after things, and, perhaps, successfully obtain things they couldn’t otherwise,” says Ed Desser, president of Desser Sports Media. Before this deal, Desser continues, Bleacher Report was “just another aggregator of customer-created content.” But now? The wave of the future. No media outlet can ignore the allures of crowdsourcing—or dismiss out of hand the rewards of reverse-engineering content. “There was a time when the traditional media viewed new media as not up to their standards. But that time has passed,” Desser notes. “Tastes change. Look at TV. Think about how much stuff would never have been on thirty years ago: vulgar language, sexual situations, eating bugs. It’s all out there now. We’re a long way from Ozzie and Harriet.”

Common Knowledge?: An Ethnography of Wikipedia by Dariusz Jemielniak

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Andrew Keen, barriers to entry, citation needed, collaborative consumption, collaborative editing, conceptual framework, continuous integration, crowdsourcing, Debian, deskilling, digital Maoism, en.wikipedia.org, Filter Bubble, Google Glasses, Hacker Ethic, hive mind, Internet Archive, invisible hand, Jaron Lanier, jimmy wales, job satisfaction, Julian Assange, knowledge economy, knowledge worker, Menlo Park, moral hazard, online collectivism, pirate software, RFC: Request For Comment, Richard Stallman, Silicon Valley, Skype, slashdot, social software, Stewart Brand, The Nature of the Firm, The Wisdom of Crowds, transaction costs, WikiLeaks, wikimedia commons

The innovative construction of interpersonal trust and identity on Wikipedia stems from the need to discard the traditional hierarchy of knowledge production, so that the social organization of collaboration could work the way it does. In this sense, some disregard for academic titles (in terms of purely formal recognition of authority, without some actual expertise) is embedded in the philosophy of the movement. While knowledge management may be just a fad in consulting in business literature (Jemielniak & Kociatkiewicz, 2009), management of knowledge through crowdsourcing has brought a successful redefinition of social knowledge boundaries, of which the Wikimedia movement is a part. The resulting inevitable redistribution of social power (Foucault, 1982) is probably even more significant in the long run than the parallel transformation of consumers of culture into its producers (Bruns, 2008). The new mode of knowledge production surpasses the traditional, hierarchical, turf-driven, and caste-like system that universities depend on (Gibbons, 2000; Godin & Gingras, 2000; Bartunek, 2011), being possibly more effective than research institutions at engaging the practitioners and society.

Editing Wikipedia is often described as fun, just as virtual gaming communities often enforce the ideology of play (Kücklich, 2009) and commercial organizations rely on redefining work as fun (Fleming & Spicer, 2004, 2007; Sørensen & Spoelstra, 2012). Thus, that work on open-collaboration platforms is perceived as a hobby should not necessarily signify that it does not involve worker exploitation. While Wikipedia is a not-for-profit organization and exploitation of editors, if any, benefits society as a whole, other organizations also using crowdsourcing and usergenerated content (as does TripAdvisor and IMDb) rely on elements of opencollaboration design, tested so well in the Wikipedia community, to maximize their revenues. This criticism of open-collaboration organization as a new form of making capital out of consumers and using them to create value for the producers does not apply directly to Wikipedia. Yet the thesis that the open-collaboration phenomenon leads univocally and definitely to liberating consumers from traditional neoliberal institutions and economics seems risky.

Boundary organizations: Enabling collaboration among unexpected allies. Administrative Science Quarterly, 53(3), 422–459. O’Mahony, S., & Ferraro, F. (2007). The emergence of governance in an open source community. The Academy of Management Journal, 50(5), 1079–1106. O’Neil, M. (2009). Cyberchiefs: Autonomy and authority in online tribes. New York: Pluto Press. O’Neil, M. (2010). Shirky and Sanger, or the costs of crowdsourcing. Journal of Science Communication, 9(1), 1–6. O’Neil, M. (2011a). The sociology of critique in Wikipedia. Critical Studies in Peer Production, 1(2). Retrieved from http://peerproduction.net/issues/issue-0/peer -reviewed-papers/sociology-of-critique/ O’Neil, M. (2011b). Wikipedia and authority. In G. Lovink & N. Tkacz (Eds.), Critical point of view: A Wikipedia reader (pp. 309–324). Amsterdam: Institute of Network Cultures.


pages: 497 words: 144,283

Connectography: Mapping the Future of Global Civilization by Parag Khanna

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1919 Motor Transport Corps convoy, 2013 Report for America's Infrastructure - American Society of Civil Engineers - 19 March 2013, 3D printing, 9 dash line, additive manufacturing, Admiral Zheng, affirmative action, agricultural Revolution, Airbnb, Albert Einstein, amateurs talk tactics, professionals talk logistics, Amazon Mechanical Turk, Asian financial crisis, asset allocation, autonomous vehicles, banking crisis, Basel III, Berlin Wall, bitcoin, Black Swan, blockchain, borderless world, Boycotts of Israel, Branko Milanovic, BRICs, British Empire, business intelligence, call centre, capital controls, charter city, clean water, cloud computing, collateralized debt obligation, complexity theory, corporate governance, corporate social responsibility, credit crunch, crony capitalism, crowdsourcing, cryptocurrency, cuban missile crisis, data is the new oil, David Ricardo: comparative advantage, deglobalization, deindustrialization, dematerialisation, Deng Xiaoping, Detroit bankruptcy, diversification, Doha Development Round, edge city, Edward Snowden, Elon Musk, energy security, ethereum blockchain, European colonialism, eurozone crisis, failed state, Fall of the Berlin Wall, family office, Ferguson, Missouri, financial innovation, financial repression, forward guidance, global supply chain, global value chain, global village, Google Earth, Hernando de Soto, high net worth, Hyperloop, ice-free Arctic, if you build it, they will come, illegal immigration, income inequality, income per capita, industrial robot, informal economy, Infrastructure as a Service, interest rate swap, Internet of things, Isaac Newton, Jane Jacobs, Jaron Lanier, John von Neumann, Julian Assange, Just-in-time delivery, Kevin Kelly, Khyber Pass, Kibera, Kickstarter, labour market flexibility, labour mobility, LNG terminal, low cost carrier, manufacturing employment, mass affluent, megacity, Mercator projection, microcredit, mittelstand, Monroe Doctrine, mutually assured destruction, New Economic Geography, new economy, New Urbanism, offshore financial centre, oil rush, oil shale / tar sands, oil shock, openstreetmap, out of africa, Panamax, Peace of Westphalia, peak oil, Peter Thiel, Plutocrats, plutocrats, post-oil, post-Panamax, private military company, purchasing power parity, QWERTY keyboard, race to the bottom, Rana Plaza, rent-seeking, reserve currency, Robert Gordon, Robert Shiller, Robert Shiller, Ronald Coase, Scramble for Africa, Second Machine Age, sharing economy, Shenzhen was a fishing village, Silicon Valley, Silicon Valley startup, six sigma, Skype, smart cities, Smart Cities: Big Data, Civic Hackers, and the Quest for a New Utopia, South China Sea, South Sea Bubble, sovereign wealth fund, special economic zone, spice trade, Stuxnet, supply-chain management, sustainable-tourism, TaskRabbit, telepresence, the built environment, Tim Cook: Apple, trade route, transaction costs, UNCLOS, uranium enrichment, urban planning, urban sprawl, WikiLeaks, young professional, zero day

In the 1980s, GPS technology firms began painstakingly driving and geo-coding roads all over the world, building up databases for the suites of navigational tools that are now in almost every new car’s dashboard. Google soon joined the fray, adding more satellite imagery and street views. Today every individual can become a digital cartographer: Maps have gone from Britannica to Wiki. OpenStreetMap, for example, crowdsources street views from millions of members who can also tag and label any structure, infusing local knowledge and essential insight for everything from simple commuting to delivering supplies during humanitarian disasters.*1 We can now even insert updated imagery from Planet Labs’ two dozen shoe-box-size satellites into 3-D maps and fly through the natural or urban environment. All of this is coming to the palm of your hand.

Even as traditional productivity metrics still fail to capture all the benefits created by such connectivity, innovation itself very much depends on it. Digital supply chains are now dispersed by design, with companies (both those fixed in one place and those operating distributed workforces) seeking to engineer serendipity among colleagues through shared work spaces and online tools that allow for constant crowdsourcing among people who have never met. Data forensics reveals how coders from diffuse geographies swarm to collaborate on projects and build partnerships that last across diverse gigs. The rapid emergence of a competitive global digital labor market is, however, a double-edged sword for the average Western consumer-worker. While many Asians on Upwork work three to four jobs simultaneously from public squares or coffee shops, under-skilled Americans face cyber-structural unemployment—especially with half of all jobs in advanced economies in tradable services sectors.

NATIONAL GEOSPATIAL-INTELLIGENCE AGENCY https://nga.​maps.​arcgis.​com/​home/ The National Geospatial-Intelligence Agency provides public access to large volumes of satellite and other geo-data and imagery in support of scientific research, natural disaster recovery operations, and crisis management. NORSE ATTACK MAP http://map.​norsecorp.​com/ Norse, a cyber-threat analysis firm, provides real-time visualizations of global cyber war based on data collected every second from Internet and Dark Web sources, plotting origins of attackers and target attacks. OPENSTREETMAP https://www.​openstreetmap.​org/ OpenStreetMap is a crowdsourced mapping platform maintained by a user community that constantly updates data on transportation networks, store locations, and myriad other content generated and verified through aerial imagery, GPS devices, and other tools. PLANET LABS https://www.​planet.​com/ Planet Labs uses a network of low-orbit satellites to capture the most current images of the entire earth and form composite digital renderings that can be used for commercial or humanitarian applications.


pages: 903 words: 235,753

The Stack: On Software and Sovereignty by Benjamin H. Bratton

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1960s counterculture, 3D printing, 4chan, Ada Lovelace, additive manufacturing, airport security, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, algorithmic trading, Amazon Mechanical Turk, Amazon Web Services, augmented reality, autonomous vehicles, Berlin Wall, bioinformatics, bitcoin, blockchain, Buckminster Fuller, Burning Man, call centre, carbon footprint, carbon-based life, Cass Sunstein, Celebration, Florida, charter city, clean water, cloud computing, connected car, corporate governance, crowdsourcing, cryptocurrency, dark matter, David Graeber, deglobalization, dematerialisation, disintermediation, distributed generation, don't be evil, Douglas Engelbart, Edward Snowden, Elon Musk, en.wikipedia.org, Eratosthenes, ethereum blockchain, facts on the ground, Flash crash, Frank Gehry, Frederick Winslow Taylor, future of work, Georg Cantor, gig economy, global supply chain, Google Earth, Google Glasses, Guggenheim Bilbao, High speed trading, Hyperloop, illegal immigration, industrial robot, information retrieval, intermodal, Internet of things, invisible hand, Jacob Appelbaum, Jaron Lanier, Jony Ive, Julian Assange, Khan Academy, linked data, Mark Zuckerberg, market fundamentalism, Marshall McLuhan, Masdar, McMansion, means of production, megacity, megastructure, Menlo Park, Minecraft, Monroe Doctrine, Network effects, new economy, offshore financial centre, oil shale / tar sands, packet switching, PageRank, pattern recognition, peak oil, performance metric, personalized medicine, Peter Thiel, phenotype, place-making, planetary scale, RAND corporation, recommendation engine, reserve currency, RFID, Sand Hill Road, self-driving car, semantic web, sharing economy, Silicon Valley, Silicon Valley ideology, Slavoj Žižek, smart cities, smart grid, smart meter, social graph, software studies, South China Sea, sovereign wealth fund, special economic zone, spectrum auction, Startup school, statistical arbitrage, Steve Jobs, Steven Levy, Stewart Brand, Stuxnet, Superbowl ad, supply-chain management, supply-chain management software, TaskRabbit, the built environment, The Chicago School, the scientific method, Torches of Freedom, transaction costs, Turing complete, Turing machine, Turing test, universal basic income, urban planning, Vernor Vinge, Washington Consensus, web application, WikiLeaks, working poor, Y Combinator

It is at this level of The Stack that the modern coherence of the state, which would produce one sort of public, and the operations of platforms, which would produce another, can come into conflict, overlapping and interlacing one another without universal jurisdiction or resolution, but it is also where they can reinforce each other with more pervasive forms of ambient governance. The geopolitics of the Cloud is everywhere and wants everything: the platform wars between Google, Facebook, Apple, and Amazon, anonymized servers routing the angry tweets from street battles, Anonymous going up against Mexican drug cartels, WikiLeaks crowd-sourcing counterespionage, Tor users building on top of Amazon Web Services services, carriers licensing content, content providers licensing bandwidth, proprietary fiber networks connected trading centers, and on, and on. It might seem at first blush that these events, each perhaps pushing legal boundaries in its own way, should be understood as disruptive contaminations of a standing political order—acts of resistance to the system, even.

For savvy urban designers, equally adept with physical and virtual envelopes, it's not difficult to make up long lists of possible projects: augmented reality Apps for ambulance paramedics and open-air surgical theaters; a mash-up of post-Twitter microblog Apps linked to post-Siri voice-control interfaces and trans-Google translation software, together posting anything you want to say to anyone anywhere always; citizen activists using GIS, mass-market geobrowsers, and modified drones to streaming real-time C3 video to 3D-printed phones; mining composite crowd-sourced behavioral data to optimize the recycling of post-purchase prosaic junk; real-time flu outbreak visualization and private microgovernance of microbiopolitical swarms (a premium upgrade only for club members); traffic control sensor and smart tollbooth hacks; individually reconfigurable robotic building interiors collapsing rooms and even floors serving different programs in morning and at night; anonymized parking markets based on bitcoin and namecoin; building exteriors featuring networked cinema, not on thirty-second loops but on eighteen-month lunar cycles; lifelong syncing of car-phone-home-Clouds platform allegiance chosen at birth like football team fandom; Google Office per-minute commercial office leasing apps; personal RFID managers; rock star privacy consultants—all driven by (at least partially) open APIs enabling other applications to build further on their existing traces.

In that the service is provided to a device-User that is in motion, moving through the City layer and encountering different contexts on the go, the App platform provides that provisional link between a preexisting physical spatial context and this User-directed overlay of a Cloud service onto immediate circumstances. As discussed in the City layer chapter, there is then a kind of programmatic blending between the urban situation through which a User moves and the interactions he may be having with a specific App and Cloud service. A mall becomes a game board, a sidewalk becomes a banking center, a restaurant becomes the scene of a crime in a crowd-sourced recommendation engine, birds are angry and enemies are identified, and the experience of these may be very different for different people and purposes. At any given moment, multiple Users interacting with different Apps in the same place may have brought their shared location into contrasting Cloud dramas; one may be ensconced in a first-person shooter game and the other in measuring his carbon footprint, further fragmenting any apparent solidarity of the crowd.


pages: 602 words: 177,874

Thank You for Being Late: An Optimist's Guide to Thriving in the Age of Accelerations by Thomas L. Friedman

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3D printing, additive manufacturing, affirmative action, Airbnb, AltaVista, Amazon Web Services, autonomous vehicles, Ayatollah Khomeini, barriers to entry, Berlin Wall, Bernie Sanders, bitcoin, blockchain, business process, call centre, centre right, Clayton Christensen, clean water, cloud computing, corporate social responsibility, crowdsourcing, David Brooks, demand response, demographic dividend, demographic transition, Deng Xiaoping, Donald Trump, Erik Brynjolfsson, failed state, Fall of the Berlin Wall, Ferguson, Missouri, first square of the chessboard / second half of the chessboard, Flash crash, game design, gig economy, global supply chain, illegal immigration, immigration reform, income inequality, indoor plumbing, Internet of things, invention of the steam engine, inventory management, Jeff Bezos, job automation, John von Neumann, Khan Academy, Kickstarter, knowledge economy, knowledge worker, land tenure, linear programming, low skilled workers, Lyft, Mark Zuckerberg, Maui Hawaii, Menlo Park, Mikhail Gorbachev, mutually assured destruction, pattern recognition, planetary scale, pull request, Ralph Waldo Emerson, ransomware, Ray Kurzweil, Richard Florida, ride hailing / ride sharing, Robert Gordon, Ronald Reagan, Second Machine Age, self-driving car, shareholder value, sharing economy, Silicon Valley, Skype, smart cities, South China Sea, Steve Jobs, TaskRabbit, Thomas L Friedman, transaction costs, Transnistria, urban decay, urban planning, Watson beat the top human players on Jeopardy!, WikiLeaks, women in the workforce, Y2K, Yogi Berra

If I want to submit the changes back to you, the original author, I make a pull request. You look at the new way I have laid out ‘How to Write a Column’; you can see all the changes. And if you like it, you press the ‘merge’ button. And then the next viewer sees the aggregate version. If you don’t like all of it, we have a way to discuss, comment, and review each line of code. It is curated crowdsourcing. But ultimately you have an expert—the person who wrote the original program—‘How to Write a Column’—who gets to decide what to accept and what to reject. GitHub will show that I worked on this, but you get to control what is merged with your original version. Today, this is the way you build software.” A decade and a half ago Microsoft created a technology called .NET—a proprietary closed-source platform for developing serious enterprise software for banks and insurance companies.

When a company like Udacity can respond to a major technological leap forward, such as TensorFlow from Google, and offer a course online to teach it to anyone in the world within three months, the word is going to get out and the market will change. Who is going to wait until next year to take that course on the campus of a university—assuming that school can even change its curriculum that quickly? Moreover, there are now game platforms such as Foldit, the crowdsourcing computer game, that enable anyone to contribute to important scientific research. These are becoming popular learning platforms. Foldit set up an online “game” where anyone could play and win a substantial cash prize by designing proteins. “Since proteins are part of so many diseases, they can also be part of the cure. Players can design brand new proteins that could help prevent or treat important diseases,” Foldit explains on its site.

While browsing Facebook, I saw a photo … of a tortured, dead body of a young Egyptian guy. His name was Khaled Said. Khaled was a twenty-nine-year-old Alexandrian who was killed by police. I saw myself in his picture … I anonymously created a Facebook page and called it ‘We Are All Khaled Said.’ In just three days, the page had over a hundred thousand people, fellow Egyptians who shared the same concern.” Soon Ghonim and his friends used Facebook to crowdsource ideas, and “the page became the most followed page in the Arab world,” he said. “Social media was crucial for this campaign. It helped a decentralized movement arise. It made people realize that they were not alone. And it made it impossible for the regime to stop it.” Ghonim was eventually tracked down in Cairo by Egyptian security services, beaten, and then held incommunicado for eleven days.


pages: 398 words: 86,023

The Wikipedia Revolution: How a Bunch of Nobodies Created the World's Greatest Encyclopedia by Andrew Lih

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Albert Einstein, AltaVista, barriers to entry, Benjamin Mako Hill, c2.com, Cass Sunstein, citation needed, crowdsourcing, Debian, en.wikipedia.org, Firefox, Hacker Ethic, HyperCard, index card, Jane Jacobs, Jason Scott: textfiles.com, jimmy wales, Marshall McLuhan, Network effects, optical character recognition, Ralph Waldo Emerson, Richard Stallman, side project, Silicon Valley, Skype, slashdot, social software, Steve Jobs, The Death and Life of Great American Cities, The Wisdom of Crowds, urban planning, urban renewal, Vannevar Bush, wikimedia commons, Y2K

More young people will learn about IBM from Wikipedia in coming years than from IBM itself.5 12_The_Wikipedia_Revolution There is value in trying to influence Wikipedia’s articles, transparently or sur-reptitiously. That has meant legions of volunteers act like street sweepers, constantly monitoring entries for bias. The story of Wikipedia has inspired businesses, governments, and academics to reevaluate accepted truths about producing works of knowledge. Credentials and central control, once considered the most important parameters for generating quality content, now yield to new terms: crowdsourcing, peer production, and open source intelligence. What was once only done top-down is now being viewed bottom-up. Books and essays have addressed the impact of projects freely driven by communities of scattered individuals: The Cathedral and the Bazaar by Eric S. Raymond, The Wisdom of Crowds by James Surowiecki, The Wealth of Networks by Yochai Benkler, The Long Tail by Chris Anderson, Infotopia by Cass R.

It quickly became a must-read for the Internet age. Even those not into software knew that the upstart Linux operating system, written by a distributed set of volunteers around the world, was posing a serious challenge to corporate-developed software like Microsoft’s. “The Cathedral and the Bazaar” was a description of that dynamic, and the essay directly influenced online communities and future thinking about effective, so-called crowdsourcing. Problem was, it was directly counter to Sanger’s belief in a strong authority. Raymond felt that Linus Torvalds’s letting go of top-down authority ultimately gave him the moral authority to do more things within the Linux project, with more people, without using a heavy hand: Linus, by successfully positioning himself as the gatekeeper of a project in which the development is mostly done by others, and nurturing interest in the project until it became self-sustaining, has shown an acute grasp of Kropotkin’s “principle of shared understanding.”


pages: 422 words: 104,457

Dragnet Nation: A Quest for Privacy, Security, and Freedom in a World of Relentless Surveillance by Julia Angwin

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AltaVista, Ayatollah Khomeini, barriers to entry, bitcoin, Chelsea Manning, clean water, crowdsourcing, cuban missile crisis, data is the new oil, David Graeber, Debian, Edward Snowden, Filter Bubble, Firefox, GnuPG, Google Chrome, Google Glasses, informal economy, Jacob Appelbaum, Julian Assange, market bubble, market design, medical residency, meta analysis, meta-analysis, mutually assured destruction, prediction markets, price discrimination, randomized controlled trial, RFID, Robert Shiller, Ronald Reagan, security theater, Silicon Valley, Silicon Valley startup, Skype, smart meter, Steven Levy, Upton Sinclair, WikiLeaks, Y2K, Zimmermann PGP

After selling a social networking website called the Names Database for $10 million in 2006, he and his wife moved to Valley Forge, Pennsylvania, so she could be close to her work at the pharmaceutical giant GlaxoSmithKline. A freshly minted millionaire, Weinberg experimented with a bunch of projects. He made his own TV studio, worked on a social network for golfers, and started a service that sought to use crowdsourcing to find better search results. As he played around with search, he started to get increasingly annoyed by Google search results that were filled with the equivalent of spam. So he decided to build a better search engine. “I wanted to go back to the Google old days when the focus was on quality links,” he told me. Privacy came up only after he launched the first version of the website to the technology community, and some users asked about the site’s privacy policies.

In 2009, an entrepreneur named: David Cancel, “The Future of Ghostery,” David Cancel (blog), January 19, 2010, http://davidcancel.com/the-future-of-ghostery/. In 2010, he sold it to an advertising services: Adam DeMartino, “Better Advertising Acquires Ghostery,” The Evidon Blog, January 19, 2010, http://www.evidon.com/blog/better-advertising-acquires-ghostery. one of the most comprehensive lists: There are some other crowd-sourced comprehensive lists—such as the EasyPrivacy list that can be added to AdblockPlus—https://easylist-downloads.adblockplus.org/easyprivacy.txt. (As of October 5, 2013, the list included 8,376 items.) of tracking technologies: Andy Kahl, in discussion with author, May 30, 2013. Brian Kennish, an engineer at Google: Julia Angwin, “Wall Street Journal Privacy Series Inspires One Start-Up,” Wall Street Journal, Digits (blog), February 27, 2011, http://blogs.wsj.com/digits/2011/02/27/wall-street-journal-privacy-series-inspires-one-start-up/.


pages: 459 words: 103,153

Adapt: Why Success Always Starts With Failure by Tim Harford

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Andrew Wiles, banking crisis, Basel III, Berlin Wall, Bernie Madoff, Black Swan, car-free, carbon footprint, Cass Sunstein, charter city, Clayton Christensen, clean water, cloud computing, cognitive dissonance, complexity theory, corporate governance, correlation does not imply causation, credit crunch, Credit Default Swap, crowdsourcing, cuban missile crisis, Daniel Kahneman / Amos Tversky, Dava Sobel, Deep Water Horizon, Deng Xiaoping, double entry bookkeeping, Edmond Halley, en.wikipedia.org, Erik Brynjolfsson, experimental subject, Fall of the Berlin Wall, Fermat's Last Theorem, Firefox, food miles, Gerolamo Cardano, global supply chain, Isaac Newton, Jane Jacobs, Jarndyce and Jarndyce, Jarndyce and Jarndyce, John Harrison: Longitude, knowledge worker, loose coupling, Martin Wolf, Menlo Park, Mikhail Gorbachev, mutually assured destruction, Netflix Prize, New Urbanism, Nick Leeson, PageRank, Piper Alpha, profit motive, Richard Florida, Richard Thaler, rolodex, Shenzhen was a fishing village, Silicon Valley, Silicon Valley startup, South China Sea, special economic zone, spectrum auction, Steve Jobs, supply-chain management, the market place, The Wisdom of Crowds, too big to fail, trade route, Tyler Cowen: Great Stagnation, web application, X Prize

The sheer power and interconnectedness of modern technology means that anyone can get hold of enough computing power to produce great new software. Thanks to outsourcing, even the hardware business is becoming easy to enter. Three-dimensional printers, cheap robots and ubiquitous design software mean that other areas of innovation are opening up, too. Yesterday it was customised T-shirts. Today, even the design of niche cars is being ‘crowd-sourced’ by companies such as Local Motors, which also outsource production. Tomorrow, who knows? In such fields, an open game with lots of new players keeps the innovation scoreboard ticking over. Most ideas fail, but there are so many ideas that it doesn’t matter: the internet and social media expert Clay Shirky celebrates ‘failure for free’. Here’s the problem, though: failure for free is still all too rare.

Peer monitoring is closely associated with the virtual world: it’s the fundamental building block of Google’s search algorithm (giving weight to how popular a site is with other sites), phenomena like eBay (which relies on buyers and sellers rating each other’s reliability) and Wikipedia (in which anyone can edit anyone else’s articles), and the open-source software movement which has delivered such successes as Firefox and Apache. But as Timpson shows, it’s applicable far behind the cutting edge of crowd-sourced technology. I witnessed a striking example of peer monitoring on my visit to the Hinkley B nuclear power station. I’d just received a briefing on Hinkley’s safety culture from Peter Higginson, an avuncular physicist from Shropshire who was responsible for the safety of Hinkley’s two massive advanced gas-cooled reactors. The safety culture sounded impressive, and depended heavily on peer monitoring.


pages: 370 words: 94,968

The Most Human Human: What Talking With Computers Teaches Us About What It Means to Be Alive by Brian Christian

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4chan, Ada Lovelace, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, Bertrand Russell: In Praise of Idleness, carbon footprint, cellular automata, Claude Shannon: information theory, cognitive dissonance, complexity theory, crowdsourcing, Donald Trump, Douglas Hofstadter, George Akerlof, Gödel, Escher, Bach, high net worth, Isaac Newton, Jacques de Vaucanson, Jaron Lanier, job automation, l'esprit de l'escalier, Loebner Prize, Menlo Park, Ray Kurzweil, RFID, Richard Feynman, Richard Feynman, Ronald Reagan, Skype, statistical model, Stephen Hawking, Steve Jobs, Steven Pinker, theory of mind, Turing machine, Turing test, Von Neumann architecture, Watson beat the top human players on Jeopardy!

The knowledge-base writing process can be compared to writing a book. Suppose every developer describes an episode without having any information on the others. Can you imagine what will be produced!” In fact, it’s quite easy to imagine what will be produced: “Eugene Goostman” ’s competitors. This is a central trade-off in the world of bot programming, between coherence of the program’s personality or style and the range of its responses. By “crowdsourcing” the task of writing a program’s responses to the users themselves, the program acquires an explosive growth in its behaviors, but these behaviors stop being internally consistent. Death of the Author; End of the Best Friend Do you need someone? Or do you need me? –SAY ANYTHING … Speaking of “writing a book”: this notion of style versus content, and of singularity and uniqueness of vision, is at the heart of recent debates about machine translation, especially of literature.

Both Google Translate and Cleverbot show weaknesses for (1) unusual and/or nonliteral phrasing, and (2) long-term consistency in point of view and style. On both of those counts, even as machine translation increasingly penetrates the world of business, literary novels remain mostly untranslatable by machine. What this also suggests, intriguingly, is that the task of translating (or writing) literary novels cannot be broken into parts and done by a succession of different humans either—not by wikis, nor crowdsourcing, nor ghostwriters. Stability of point of view and consistency of style are too important. What’s truly strange, then, is the fact that we do seem to make a lot of art this way. To be human is to be a human, a specific person with a life history and idiosyncrasy and point of view; artificial intelligence suggests that the line between intelligent machines and people blurs most when a purée is made of that identity.


pages: 357 words: 95,986

Inventing the Future: Postcapitalism and a World Without Work by Nick Srnicek, Alex Williams

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3D printing, additive manufacturing, air freight, algorithmic trading, anti-work, back-to-the-land, banking crisis, battle of ideas, blockchain, Bretton Woods, call centre, capital controls, carbon footprint, Cass Sunstein, centre right, collective bargaining, crowdsourcing, cryptocurrency, David Graeber, decarbonisation, deindustrialization, deskilling, Doha Development Round, Elon Musk, Erik Brynjolfsson, Ferguson, Missouri, financial independence, food miles, Francis Fukuyama: the end of history, full employment, future of work, gender pay gap, housing crisis, income inequality, industrial robot, informal economy, intermodal, Internet Archive, job automation, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, late capitalism, low skilled workers, manufacturing employment, market design, Martin Wolf, means of production, minimum wage unemployment, Mont Pelerin Society, neoliberal agenda, New Urbanism, Occupy movement, oil shale / tar sands, oil shock, patent troll, pattern recognition, post scarcity, postnationalism / post nation state, precariat, price stability, profit motive, quantitative easing, reshoring, Richard Florida, rising living standards, road to serfdom, Robert Gordon, Ronald Reagan, Second Machine Age, secular stagnation, self-driving car, Slavoj Žižek, social web, stakhanovite, Steve Jobs, surplus humans, the built environment, The Chicago School, Tyler Cowen: Great Stagnation, universal basic income, wages for housework, We are the 99%, women in the workforce, working poor, working-age population

Similarly, recent anti-fracking movements have been able to stop test drilling in various localities – but governments nevertheless continue to search for shale gas resources and provide support for companies to do so.7 In the United States, various movements to stop evictions in the wake of the housing crisis have made real gains in terms of keeping people in their homes.8 Yet the perpetrators of the subprime mortgage debacle continue to reap the profits, waves of foreclosures continue to sweep across the country, and rents continue to surge across the urban world. Small successes – useful, no doubt, for instilling a sense of hope – nevertheless wither in the face of overwhelming losses. Even the most optimistic activist falters in the face of struggles that continue to fail. In other cases, well-intentioned projects like Rolling Jubilee strive to escape the spell of neoliberal common sense.9 The ostensibly radical aim of crowdsourcing money to pay the debts of the underprivileged means buying into a system of voluntary charity and redistribution, as well as accepting the legitimacy of the debt in the first place. In this respect, the initiative is one among a larger group of projects that act simply as crisis responses to the faltering of state services. These are survival mechanisms, not a desirable vision for the future.

We can see this in the small but growing number of part-time, flexible and freelance jobs over the past thirty years.63 For instance, the relatively low unemployment levels of the UK after the 2008 crisis are largely a result of more self-employed people living off poverty wages.64 In the United States, more than 6.5 million people are forced to work part-time despite desiring full-time work.65 This casualisation also involves innovations such as crowd-sourced tasks, temporary staffing agencies and zero-hours contracts, along with the harsh working conditions and lack of benefits that accompany them. In the UK, for example, it is estimated that nearly 5 per cent of the working population is presently on zero-hours contracts.66 Surplus populations have also put downward pressure on wages. Estimates suggest that every 1 per cent increase in labour market slack is associated with a 1.6 per cent increase in income inequality.67 The stagnation of real wages and the declining share of income going to labour are both tied to an excess supply of labour,68 and most economists believe automation and the globalisation of the proletariat are central reasons why wages have been stagnant in recent decades.69 All of these trends have continued since the 2008 crisis as well, with slow real wage growth across the G20, and outright decline in the UK.70 The slow growth of wages leads precarity to also be expressed in the anxiety over high levels of consumer debt and low levels of personal savings.71 In the United States, for example, a full 34 per cent of fulltime workers live paycheque-to-paycheque, while in the UK, 35 per cent of people could not live off their savings for more than a month.72 And at its most vicious, precarity is indicated by a rise in depression, anxiety and suicides – an ‘excess’ that goes uncounted in traditional economic measures.73 Indeed, unemployment is associated with a fifth of all global suicides, and this has only worsened in the wake of the financial crisis.74 In addition to precarity, surplus populations and technological automation help to make sense of a recent labour market phenomenon: the emergence of ‘jobless recoveries’, in which economic growth returns after a crisis but job growth remains anaemic.75 Such recoveries have become standard for the US economy,76 and since the 1990s the trend has been towards longer and longer jobless recoveries.77 The current crisis is no exception, with more than a million full-time jobs yet to return, and forecasts suggesting that US unemployment will remain above pre-crisis levels until 2024.78 This is a global phenomenon as well, with the world economy creating jobs so slowly that the number of jobs will remain significantly below pre-crisis levels for at least a decade.79 While their cause is ultimately still a mystery, jobless recoveries appear to be closely related to automation.80 In fact, the only occupations that have experienced jobless recoveries are those that have been under threat from automation in recent decades – semi-skilled, routine jobs.81 Moreover, these job losses have occurred almost entirely during and in the wake of recessions.82 In other words, crisis periods are when automatable jobs disappear, never to be heard from again.


pages: 407 words: 109,653

Top Dog: The Science of Winning and Losing by Po Bronson, Ashley Merryman

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Asperger Syndrome, Berlin Wall, conceptual framework, crowdsourcing, delayed gratification, deliberate practice, Edward Glaeser, experimental economics, Fall of the Berlin Wall, fear of failure, game design, Jean Tirole, knowledge worker, loss aversion, Mark Zuckerberg, meta analysis, meta-analysis, Mikhail Gorbachev, phenotype, Richard Feynman, Richard Feynman, risk tolerance, school choice, shareholder value, Silicon Valley, six sigma, Steve Jobs

Lakhani, “The Determinants of Individual Performance and Collective Value in Private-Collective Software Innovation,” Harvard Business School Working Paper, No. 10-065 (2010) Hertel, Guido, Sven Niedner, & Stefanie Hermann, “Motivation of Software Developers in Open Source Projects: An Internet-Based Survey of Contributors to the Linux Kernel,” Research Policy, vol. 32(7), pp. 1159–1177 (2003) Jdamato12, “TopCoder Celebrates 400,000 Members as Payments Top $36 Million,” TopCoder.com, http://bit.ly/O0ehd4 (4/12/2012) Lakhani, Karim, Correspondence with Authors (2011, 2012) Lakhani, Karim, Interview with Author (2012) Lakhani, Karim R., “TopCoder (A): Developing Software through Crowdsourcing,” Harvard Business School Teaching Note, No. 5-611-071 (2011) Lakhani, Karim R., & David A. Garvin, “TopCoder (A): Developing Software through Crowdsourcing,” Harvard Business School Case Study, No. 9-610-032 (2010) Lakhani, Karim R., & Jill A. Panetta, “The Principles of Distributed Innovation,” Innovations, vol. 2(3), pp. 97–113 (2007) McKeown, Jim, “TopCoder One of Inc. Magazine’s 500 Fastest-Growing Companies in America for Second Consecutive Year,” Press Release (8/27/2008) Moon, Jae Yun, & Lee Sproull, “Essence of Distributed Work: The Case of the Linux Kernel,” First Monday, vol. 5(11) (2000) Noyes, Kathleen, “Top Honor for Linus Torvalds Highlights Linux’s Importance,” Operating Systems Blog, PC World, http://bit.ly/HTceE4 (4/19/2012) Peyrache, Eloic, Jacques Cremer, & Jean Tirole, “Some Reflections on Open Source Software,” Communications & Strategies, vol. 40, pp. 139–159 (2000) Raymond, Eric, “The Cathedral and the Bazaar: Musings on Linux and Open Source by an Accidental Revolutionary, Revised Edition,” Sebastopol, CA: O’Reilly & Assoc., Inc. (2001) Terwiesch, Christian, & Yi Xu, “Innovation Contests, Open Innovation, and Multiagent Problem Solving,” Management Science, vol. 54(9), pp. 1529–1543 (2008) Torvalds, Linus, “Re: [Announce] [patch] Modular Scheduler Core and Completely Fair Scheduler [CFS],” E-mail exchange, http://bit.ly/wxQVcQ (4/15/2007) Torvalds, Linus, & David Diamond, Just for Fun: The Story of an Accidental Revolutionary, New York: Harper Business (2002) Watson, Andrew, “Reputation in Open Source Software,” Working Paper (2005) “Who Uses TopCoder?”


pages: 391 words: 105,382

Utopia Is Creepy: And Other Provocations by Nicholas Carr

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Air France Flight 447, Airbnb, AltaVista, Amazon Mechanical Turk, augmented reality, autonomous vehicles, Bernie Sanders, book scanning, Brewster Kahle, Buckminster Fuller, Burning Man, Captain Sullenberger Hudson, centralized clearinghouse, cloud computing, cognitive bias, collaborative consumption, computer age, corporate governance, crowdsourcing, Danny Hillis, deskilling, Donald Trump, Elon Musk, factory automation, failed state, feminist movement, Frederick Winslow Taylor, friendly fire, game design, global village, Google bus, Google Glasses, Google X / Alphabet X, Googley, hive mind, impulse control, indoor plumbing, interchangeable parts, Internet Archive, invention of movable type, invention of the steam engine, invisible hand, Isaac Newton, Jeff Bezos, jimmy wales, job automation, Kevin Kelly, low skilled workers, Mark Zuckerberg, Marshall McLuhan, means of production, Menlo Park, mental accounting, natural language processing, Network effects, new economy, Nicholas Carr, oil shale / tar sands, Peter Thiel, Plutocrats, plutocrats, profit motive, Ralph Waldo Emerson, Ray Kurzweil, recommendation engine, Republic of Letters, robot derives from the Czech word robota Czech, meaning slave, Ronald Reagan, self-driving car, SETI@home, side project, Silicon Valley, Silicon Valley ideology, Singularitarianism, Snapchat, social graph, social web, speech recognition, Startup school, stem cell, Stephen Hawking, Steve Jobs, Steven Levy, technoutopianism, the medium is the message, theory of mind, Turing test, Whole Earth Catalog, Y Combinator

At least there we can be freed from the anxiety of not knowing where the edge between real and unreal lies. At least there we can find something to hold on to, even if it’s nothing. GHOSTS IN THE CODE April 4, 2007 LAST MONTH, AMAZON.COM WAS granted a broad patent for computer systems that incorporate human beings into automated data processing—the type of cybernetic arrangement that underpins the company’s Mechanical Turk crowdsourcing service. With Turk, a software programmer can write into a program a task that is difficult for a computer to do but easy for a person to carry out, such as identifying objects in photographs. At the point in the program when the “human input” is required, the task is posted to the Turk website where people carry it out for a small payment. The human input is then funneled back to the computer running the program.

., 64–65 contemplation, 241, 246 through work, 298–99 conversation, computer streaming of, 152–54 CopyBot controversy, 25–27 copyright laws: history of, 275–76 in online library controversies, 269–71, 275–78, 283 in virtual world, 25–27 Corporate Communalists, 83 corporate control, through self-tracking, 163–65 correspondence courses, 133–34 cosmetic surgery, 331, 334 Costeja González, Mario, 190–92, 194 Coupland, Douglas, 102, 103 Courant, Paul, 270, 272 courtesy: decline of, 157 inefficiency of, 152–54 Cowen, Tyler, 116 Crawford, Matthew, 265 creativity, 49, 64 before the virtual world, 60–61 economics of, 8–9 in music, 44–45, 294 stifled by iPad, 76–78 see also innovation “crisis of control,” 188–89 CRISPR, 334–35 crowdsourcing, 37 Cruz, Ted, 314 cultural memory, archiving of, 325–28 cutouts (remaindered record albums), 122 CyberLover, 55 cybernetics, 37–38, 214 cyberpunk, 113 cyberspace, xvii, 127 early idealism of, 85 “Cyborg Manifesto” (Haraway), 168–69 cyborgs, 131 cynicism, 158 Daedalus, 336, 340 Darnton, Robert, 270–75, 278 DARPA, 332 Dash Express, 56 data-mining, 186, 212, 255–59 data-protection agencies, 190–91 Data Protection Directive, 191, 193 Davidson, Cathy, 94 Davies, Alex, 195 Davies, William, 214–15 Dean, Jeff, 137 death, as hardware failure, 115 Declaration of Independence, 278, 325 “Declaration of the Independence of Cyberspace” (Barlow), 85 deep reading, 241 deletionists, 18–20, 58 democratization, xvi, xviii, 28, 86, 89, 115, 208, 271 internet perceived as tool for, 319–20 depression, 304 Derry, N.H., 296–97 Descartes, René, 301, 330 Dewey, John, 304 “digital dualism,” 129 “digital lifestyle,” 32–33 digital memory, 327 digital preservation, 325–28 Digital Public Library of America (DPLA), 268, 271–78 “Digital Republic of Letters,” 271 discovery, adventure of, 13–15 Disenchanted Night (Schivelbusch), 229 displaced agency, 265 distraction, xix, 14, 316 in consumerism, 65 video games and, 19 diversity, 65 DNA, 69–70, 334–35 Doctorow, Cory, 76–77 “Does the ‘New Economy’ Measure Up to the Great Inventions of the Past?”


pages: 125 words: 28,222

Growth Hacking Techniques, Disruptive Technology - How 40 Companies Made It BIG – Online Growth Hacker Marketing Strategy by Robert Peters

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Airbnb, bounce rate, business climate, citizen journalism, crowdsourcing, Google Glasses, Jeff Bezos, Lean Startup, Menlo Park, Network effects, new economy, pull request, revision control, ride hailing / ride sharing, search engine result page, sharing economy, Skype, TaskRabbit

In many ways the Mashable story is very old-fashioned, one-man-with-a-vision tale, while in another, it is an example of single-minded understanding of market focus with inherent flexibility to shift with the prevailing interest. Regardless, the growth has been impressive and highly effective. 99designs The online graphics design marketplace 99designs was founded in Melbourne, Australia in 2008 to create products via crowdsourcing. Designs are entered competitively for customer selection in a contest structure with the winner receiving cash payment. There is also an option to purchase templates and work with individual designers directly. Typical projects include logos, t-shirts, and websites. Traction for solid growth was actually built in to the concept from the beginning since it was a spinoff of SitePoint forums.


pages: 133 words: 36,528

Peak Car: The Future of Travel by David Metz

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autonomous vehicles, bike sharing scheme, Clayton Christensen, congestion charging, crowdsourcing, David Attenborough, decarbonisation, edge city, Edward Glaeser, Just-in-time delivery, Network effects, Richard Florida, Robert Gordon, Silicon Valley, Skype, urban sprawl, yield management, young professional

Outside city centres, where there is space for cars to move and park, buses are mostly used by the young and the old. Two kinds of services are needed: daytime routes penetrating residential neighbourhoods for older people; and evening and weekend services running fast along main roads for younger people, who employ mobile technology and social media to know when the bus is coming, data for which is supplied by the operators and by the users themselves, crowdsourced. Effective use of digital technologies to monitor bus movements and to book rail travel online is a contributing factor to reduced interest by younger people in car ownership. High‑density cities allow more choices of facilities, of shops, cinemas, jobs and leisure. Catchment areas are smaller, whether for schools or supermarkets, making walking and cycling more feasible. Public transport has more customers so that services can be more frequent and new investment justified, creating a virtuous circle of demand growth and operational improvement.


pages: 118 words: 35,663

Smart Machines: IBM's Watson and the Era of Cognitive Computing (Columbia Business School Publishing) by John E. Kelly Iii

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AI winter, call centre, carbon footprint, crowdsourcing, demand response, discovery of DNA, Erik Brynjolfsson, future of work, Geoffrey West, Santa Fe Institute, global supply chain, Internet of things, John von Neumann, Mars Rover, natural language processing, optical character recognition, pattern recognition, planetary scale, RAND corporation, RFID, Richard Feynman, Richard Feynman, smart grid, smart meter, speech recognition, Turing test, Von Neumann architecture, Watson beat the top human players on Jeopardy!

After receiving an initial query, Watson will be able to ask for additional information to help it understand more precisely what the human being wants to know. The learning capability includes a series of steps: hypothesis generation from evidence, hypothesis ranking, question generation, and answer acquisition. In addition to getting answers from humans it’s interacting with, Watson will be able to tap a directory of experts for advice or even learn through crowd-sourcing. As it acquires answers, it will build a collection of learned axioms that strengthen its command of given domains. Other improvements to Watson have come. People are now able to view the logic and evidence upon which Watson presents options. Watson is now able to digest not just textual information but also structured statistical data, such as electronic medical records. A different group at IBM is working on natural-language-processing technology that will allow people to engage in spoken conversations with Watson.


pages: 310 words: 34,482

Makers at Work: Folks Reinventing the World One Object or Idea at a Time by Steven Osborn

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3D printing, A Pattern Language, additive manufacturing, air freight, Airbnb, augmented reality, autonomous vehicles, barriers to entry, Baxter: Rethink Robotics, c2.com, computer vision, crowdsourcing, dumpster diving, en.wikipedia.org, Firefox, future of work, Google Chrome, Google Glasses, Google Hangouts, Hacker Ethic, Internet of things, Iridium satellite, Khan Academy, Kickstarter, Mason jar, means of production, Minecraft, minimum viable product, Network effects, Oculus Rift, patent troll, popular electronics, Rodney Brooks, Shenzhen was a fishing village, side project, Silicon Valley, Skype, slashdot, social software, software as a service, special economic zone, speech recognition, subscription business, telerobotics, urban planning, web application, Y Combinator

Someone once said, “Everyone is smarter than anyone.” And I appreciated you saying that you’ve been interviewing smart people and including me in that category. But really, I’m not. I’m passionate. That’s I think my biggest asset. I really like what I’m doing. But if I want to make a robot that’s going to be able to do really capable things, I need experts and I need their advice. And the best way to do that is to crowd-source the data. Right now, if I’m struggling with some sort of an engineering decision and I’m losing sleep over it, using my phone I can go onto the OpenROV forums and describe the problem I’m having, and as I doze off to sleep, the problem’s going around Europe. People in Europe are looking on the forums. And the people who are the highest paid in their fields got that way because they’re passionate about what they’re doing.

He was like, “Don’t worry about it. We’ll do a preorder for twenty, and we’ll see how it goes.” 1 www.instructables.com http://hackaday.com 2 Makers at Work So as a fundraiser for the Hack a Day blog, we did a presale for a week or two, selling an early manufactured version of the Bus Pirate. In that time, we sold a thousand of them, presale. This was before Kickstarter and Indiegogo. There was no crowdsourced funding concept out there. We just took preorders from people with the promise to deliver it as quickly as we could. From there, I thought, “Wow, there might actually be something to this.” I started my own site so that I could sell my own designs. I couldn’t do that while I was an author at Hack a Day because the editorial guidelines prohibited it. So I started my own site, Dangerous Prototypes, with the goal to post one new open-source hardware prototype every month, giving away all of the source code.


pages: 752 words: 131,533

Python for Data Analysis by Wes McKinney

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backtesting, cognitive dissonance, crowdsourcing, Debian, Firefox, Google Chrome, index card, random walk, recommendation engine, revision control, sentiment analysis, Sharpe ratio, side project, sorting algorithm, statistical model, type inference

Making such a plot from scratch is a bit of work, so pandas has a scatter_matrix function for creating one from a DataFrame. It also supports placing histograms or density plots of each variable along the diagonal. See Figure 8-23 for the resulting plot: In [93]: scatter_matrix(trans_data, diagonal='kde', color='k', alpha=0.3) Figure 8-23. Scatter plot matrix of statsmodels macro data Plotting Maps: Visualizing Haiti Earthquake Crisis Data Ushahidi is a non-profit software company that enables crowdsourcing of information related to natural disasters and geopolitical events via text message. Many of these data sets are then published on their website for analysis and visualization. I downloaded the data collected during the 2010 Haiti earthquake crisis and aftermath, and I’ll show you how I prepared the data for analysis and visualization using pandas and other tools we have looked at thus far.

beta function, Random Number Generation, Group Factor Exposures defined, Group Factor Exposures between_time method, Time of Day and “as of” Data Selection bfill method, Reindexing bin edges, Downsampling binary data formats, Storing Arrays on Disk in Binary Format–Storing Arrays on Disk in Binary Format, Binary Data Formats–Reading Microsoft Excel Files, Using HDF5 Format–Using HDF5 Format, Reading Microsoft Excel Files–Reading Microsoft Excel Files HDF5, Using HDF5 Format–Using HDF5 Format Microsoft Excel files, Reading Microsoft Excel Files–Reading Microsoft Excel Files storing arrays in, Storing Arrays on Disk in Binary Format–Storing Arrays on Disk in Binary Format binary moving window functions, Binary Moving Window Functions–Binary Moving Window Functions binary search of lists, Binary search and maintaining a sorted list–Binary search and maintaining a sorted list binary universal functions, Universal Functions: Fast Element-wise Array Functions binding, Variables and pass-by-reference, Closures: Functions that Return Functions defined, Variables and pass-by-reference variables, Closures: Functions that Return Functions binomial function, Random Number Generation bisect module, Binary search and maintaining a sorted list, Binary search and maintaining a sorted list bookmarking directories in IPython, Directory Bookmark System–Directory Bookmark System Boolean, Data Types for ndarrays, Boolean Indexing–Boolean Indexing, Methods for Boolean Arrays–Methods for Boolean Arrays, Booleans–Booleans arrays, Methods for Boolean Arrays–Methods for Boolean Arrays data type, Data Types for ndarrays, Booleans–Booleans indexing for arrays, Boolean Indexing–Boolean Indexing bottleneck library, Moving Window Functions braces ({}), Dict brackets ([]), Tuple, List break keyword, for loops broadcasting, Basic Indexing and Slicing, Repeating Elements: Tile and Repeat, Broadcasting–Setting Array Values by Broadcasting, Broadcasting, Broadcasting Over Other Axes–Broadcasting Over Other Axes, Setting Array Values by Broadcasting–Setting Array Values by Broadcasting defined, Basic Indexing and Slicing, Repeating Elements: Tile and Repeat, Broadcasting over other axes, Broadcasting Over Other Axes–Broadcasting Over Other Axes setting array values by, Setting Array Values by Broadcasting–Setting Array Values by Broadcasting bucketing, Bucketing Donation Amounts–Bucketing Donation Amounts C calendar module, Date and Time Data Types and Tools casting, Data Types for ndarrays cat method, Reading and Writing Data in Text Format, Vectorized string functions in pandas Categorical object, Discretization and Binning ceil function, Universal Functions: Fast Element-wise Array Functions center method, Vectorized string functions in pandas Chaco, Chaco–Chaco chisquare function, Random Number Generation chunksize argument, Reading and Writing Data in Text Format, Reading Text Files in Pieces, Reading Text Files in Pieces clearing screen shortcut, Keyboard Shortcuts clipboard, executing code from, Executing Code from the Clipboard–IPython interaction with editors and IDEs clock function, Timing Code: %time and %timeit close method, A Brief matplotlib API Primer, A Brief matplotlib API Primer, Files and the operating system closures, Closures: Functions that Return Functions–Closures: Functions that Return Functions cmd.exe, Windows collections module, Default values colons, Indentation, not braces cols option, Pivot Tables and Cross-Tabulation columns, grouping on, Selecting a Column or Subset of Columns–Selecting a Column or Subset of Columns column_stack function, Concatenating and Splitting Arrays combinations function, itertools module combine_first method, Combining and Merging Data Sets, Combining Data with Overlap, Combining Data with Overlap combining, Combining Data with Overlap–Combining Data with Overlap, Splicing Together Data Sources–Splicing Together Data Sources, Concatenating and combining lists–Concatenating and combining lists data sources, Splicing Together Data Sources–Splicing Together Data Sources data sources, with overlap, Combining Data with Overlap–Combining Data with Overlap lists, Concatenating and combining lists–Concatenating and combining lists commands, Keyboard Shortcuts, Using the Command History–Logging the Input and Output, Searching and Reusing the Command History–Searching and Reusing the Command History, Input and Output Variables–Input and Output Variables, Logging the Input and Output–Logging the Input and Output, Interactive Debugger, Interactive Debugger (see also magic commands) debugger, Interactive Debugger history in IPython, Using the Command History–Logging the Input and Output, Searching and Reusing the Command History–Searching and Reusing the Command History, Input and Output Variables–Input and Output Variables, Logging the Input and Output–Logging the Input and Output input and output variables, Input and Output Variables–Input and Output Variables logging of, Logging the Input and Output–Logging the Input and Output reusing command history, Searching and Reusing the Command History–Searching and Reusing the Command History searching for, Keyboard Shortcuts comment argument, Reading and Writing Data in Text Format comments in Python, Comments–Comments compile method, Regular expressions, Regular expressions complex128 data type, Data Types for ndarrays complex256 data type, Data Types for ndarrays complex64 data type, Data Types for ndarrays concat function, US Baby Names 1880-2010, Combining and Merging Data Sets, Merging on Index, Concatenating Along an Axis, Concatenating Along an Axis, Apply: General split-apply-combine, Concatenating and Splitting Arrays, Concatenating and Splitting Arrays, Concatenating and Splitting Arrays concatenating, Concatenating Along an Axis–Concatenating Along an Axis, Concatenating and Splitting Arrays–Stacking helpers: r_ and c_ along axis, Concatenating Along an Axis–Concatenating Along an Axis arrays, Concatenating and Splitting Arrays–Stacking helpers: r_ and c_ conditional logic as array operation, Expressing Conditional Logic as Array Operations–Expressing Conditional Logic as Array Operations conferences, Community and Conferences configuring matplotlib, matplotlib Configuration–matplotlib Configuration conforming, Reindexing contains method, Vectorized string functions in pandas contiguous memory, The Importance of Contiguous Memory–The Importance of Contiguous Memory continue keyword, for loops continuous return, Future Contract Rolling convention argument, Resampling and Frequency Conversion converting, Converting between string and datetime–Converting between string and datetime, Converting Timestamps to Periods (and Back)–Converting Timestamps to Periods (and Back) between string and datetime, Converting between string and datetime–Converting between string and datetime timestamps to periods, Converting Timestamps to Periods (and Back)–Converting Timestamps to Periods (and Back) coordinated universal time (UTC), Time Zone Handling copy argument, Database-style DataFrame Merges copy method, DataFrame copysign function, Universal Functions: Fast Element-wise Array Functions corr method, Correlation and Covariance, Correlation and Covariance correlation, Correlation and Covariance–Correlation and Covariance corrwith method, Correlation and Covariance cos function, Universal Functions: Fast Element-wise Array Functions cosh function, Universal Functions: Fast Element-wise Array Functions count method, Summarizing and Computing Descriptive Statistics, String Object Methods, Vectorized string functions in pandas, Data Aggregation, Tuple methods Counter class, Counting Time Zones in Pure Python cov method, Correlation and Covariance, Correlation and Covariance covariance, Correlation and Covariance–Correlation and Covariance CPython, Installation and Setup cross-section, Financial and Economic Data Applications crosstab function, Cross-Tabulations: Crosstab–Cross-Tabulations: Crosstab crowdsourcing, Plotting Maps: Visualizing Haiti Earthquake Crisis Data CSV files, Manually Working with Delimited Formats–Manually Working with Delimited Formats, Plotting Maps: Visualizing Haiti Earthquake Crisis Data Ctrl-A keyboard shortcut, Keyboard Shortcuts Ctrl-B keyboard shortcut, Keyboard Shortcuts Ctrl-C keyboard shortcut, Keyboard Shortcuts Ctrl-E keyboard shortcut, Keyboard Shortcuts Ctrl-F keyboard shortcut, Keyboard Shortcuts Ctrl-K keyboard shortcut, Keyboard Shortcuts Ctrl-L keyboard shortcut, Keyboard Shortcuts Ctrl-N keyboard shortcut, Keyboard Shortcuts Ctrl-P keyboard shortcut, Keyboard Shortcuts Ctrl-R keyboard shortcut, Keyboard Shortcuts Ctrl-Shift-V keyboard shortcut, Keyboard Shortcuts Ctrl-U keyboard shortcut, Keyboard Shortcuts cummax method, Summarizing and Computing Descriptive Statistics cummin method, Summarizing and Computing Descriptive Statistics cumprod method, Mathematical and Statistical Methods, Summarizing and Computing Descriptive Statistics cumsum method, Mathematical and Statistical Methods, Summarizing and Computing Descriptive Statistics cumulative returns, Return Indexes and Cumulative Returns–Return Indexes and Cumulative Returns currying, Currying: Partial Argument Application–Currying: Partial Argument Application, Currying: Partial Argument Application cursor, moving with keyboard, Keyboard Shortcuts custom universal functions, Custom ufuncs–Custom ufuncs cut function, Discretization and Binning, Discretization and Binning, Discretization and Binning, Discretization and Binning, Discretization and Binning, Quantile and Bucket Analysis, Bucketing Donation Amounts Cython project, Python as Glue, Other Speed Options: Cython, f2py, C–Other Speed Options: Cython, f2py, C c_ object, Stacking helpers: r_ and c_–Stacking helpers: r_ and c_ D data aggregation, Data Aggregation–Returning Aggregated Data in “unindexed” Form, Column-wise and Multiple Function Application–Column-wise and Multiple Function Application, Returning Aggregated Data in “unindexed” Form–Returning Aggregated Data in “unindexed” Form returning data in unindexed form, Returning Aggregated Data in “unindexed” Form–Returning Aggregated Data in “unindexed” Form using multiple functions, Column-wise and Multiple Function Application–Column-wise and Multiple Function Application data alignment, Arithmetic and data alignment–Operations between DataFrame and Series, Arithmetic methods with fill values–Arithmetic methods with fill values, Operations between DataFrame and Series–Operations between DataFrame and Series arithmetic methods with fill values, Arithmetic methods with fill values–Arithmetic methods with fill values operations between DataFrame and Series, Operations between DataFrame and Series–Operations between DataFrame and Series data munging, Data Munging Topics–Return Indexes and Cumulative Returns, Time Series and Cross-Section Alignment–Time Series and Cross-Section Alignment, Operations with Time Series of Different Frequencies–Using periods instead of timestamps, Time of Day and “as of” Data Selection–Time of Day and “as of” Data Selection, Splicing Together Data Sources–Splicing Together Data Sources asof method, Time of Day and “as of” Data Selection–Time of Day and “as of” Data Selection combining data, Splicing Together Data Sources–Splicing Together Data Sources for data alignment, Time Series and Cross-Section Alignment–Time Series and Cross-Section Alignment for specialized frequencies, Operations with Time Series of Different Frequencies–Using periods instead of timestamps data structures for pandas, Introduction to pandas Data Structures–Index Objects, Series–Series, DataFrame–DataFrame, Index Objects–Index Objects, Panel Data–Panel Data DataFrame, DataFrame–DataFrame Index objects, Index Objects–Index Objects Panel, Panel Data–Panel Data Series, Series–Series data types, Data Types for ndarrays–Data Types for ndarrays, Data Types for ndarrays–Data Types for ndarrays, Date and Time Data Types and Tools–Converting between string and datetime, Converting between string and datetime–Converting between string and datetime, ndarray Object Internals–NumPy dtype Hierarchy, NumPy dtype Hierarchy–NumPy dtype Hierarchy, Nested dtypes and Multidimensional Fields–Nested dtypes and Multidimensional Fields, Scalar Types–Dates and times, Numeric types–Numeric types, Strings–Strings, Booleans–Booleans, Type casting–Type casting, None–None, Dates and times–Dates and times for arrays, Data Types for ndarrays–Data Types for ndarrays for ndarray, Data Types for ndarrays–Data Types for ndarrays for NumPy, ndarray Object Internals–NumPy dtype Hierarchy, NumPy dtype Hierarchy–NumPy dtype Hierarchy hierarchy of, NumPy dtype Hierarchy–NumPy dtype Hierarchy for Python, Scalar Types–Dates and times, Numeric types–Numeric types, Strings–Strings, Booleans–Booleans, Type casting–Type casting, None–None, Dates and times–Dates and times boolean data type, Booleans–Booleans dates and times, Dates and times–Dates and times None data type, None–None numeric data types, Numeric types–Numeric types str data type, Strings–Strings type casting in, Type casting–Type casting for time series data, Date and Time Data Types and Tools–Converting between string and datetime, Converting between string and datetime–Converting between string and datetime converting between string and datetime, Converting between string and datetime–Converting between string and datetime nested, Nested dtypes and Multidimensional Fields–Nested dtypes and Multidimensional Fields data wrangling, Combining and Merging Data Sets–Combining Data with Overlap, Database-style DataFrame Merges–Database-style DataFrame Merges, Merging on Index–Merging on Index, Concatenating Along an Axis–Concatenating Along an Axis, Combining Data with Overlap–Combining Data with Overlap, Reshaping with Hierarchical Indexing–Reshaping with Hierarchical Indexing, Pivoting “long” to “wide” Format–Pivoting “long” to “wide” Format, Data Transformation–Computing Indicator/Dummy Variables, Removing Duplicates–Removing Duplicates, Transforming Data Using a Function or Mapping–Transforming Data Using a Function or Mapping, Replacing Values–Replacing Values, Renaming Axis Indexes–Renaming Axis Indexes, Discretization and Binning–Discretization and Binning, Detecting and Filtering Outliers–Detecting and Filtering Outliers, Permutation and Random Sampling–Permutation and Random Sampling, Computing Indicator/Dummy Variables–Computing Indicator/Dummy Variables, String Manipulation–Vectorized string functions in pandas, String Object Methods–String Object Methods, Regular expressions–Regular expressions, Vectorized string functions in pandas–Vectorized string functions in pandas, Example: USDA Food Database–Example: USDA Food Database manipulating strings, String Manipulation–Vectorized string functions in pandas, String Object Methods–String Object Methods, Regular expressions–Regular expressions, Vectorized string functions in pandas–Vectorized string functions in pandas methods for, String Object Methods–String Object Methods vectorized string methods, Vectorized string functions in pandas–Vectorized string functions in pandas with regular expressions, Regular expressions–Regular expressions merging data, Combining and Merging Data Sets–Combining Data with Overlap, Database-style DataFrame Merges–Database-style DataFrame Merges, Merging on Index–Merging on Index, Concatenating Along an Axis–Concatenating Along an Axis, Combining Data with Overlap–Combining Data with Overlap combining data with overlap, Combining Data with Overlap–Combining Data with Overlap concatenating along axis, Concatenating Along an Axis–Concatenating Along an Axis DataFrame merges, Database-style DataFrame Merges–Database-style DataFrame Merges on index, Merging on Index–Merging on Index pivoting, Pivoting “long” to “wide” Format–Pivoting “long” to “wide” Format reshaping, Reshaping with Hierarchical Indexing–Reshaping with Hierarchical Indexing transforming data, Data Transformation–Computing Indicator/Dummy Variables, Removing Duplicates–Removing Duplicates, Transforming Data Using a Function or Mapping–Transforming Data Using a Function or Mapping, Replacing Values–Replacing Values, Renaming Axis Indexes–Renaming Axis Indexes, Discretization and Binning–Discretization and Binning, Detecting and Filtering Outliers–Detecting and Filtering Outliers, Permutation and Random Sampling–Permutation and Random Sampling, Computing Indicator/Dummy Variables–Computing Indicator/Dummy Variables discretization, Discretization and Binning–Discretization and Binning dummy variables, Computing Indicator/Dummy Variables–Computing Indicator/Dummy Variables filtering outliers, Detecting and Filtering Outliers–Detecting and Filtering Outliers mapping, Transforming Data Using a Function or Mapping–Transforming Data Using a Function or Mapping permutation, Permutation and Random Sampling–Permutation and Random Sampling removing duplicates, Removing Duplicates–Removing Duplicates renaming axis indexes, Renaming Axis Indexes–Renaming Axis Indexes replacing values, Replacing Values–Replacing Values USDA food database example, Example: USDA Food Database–Example: USDA Food Database databases, Interacting with Databases–Storing and Loading Data in MongoDB reading and writing to, Interacting with Databases–Storing and Loading Data in MongoDB DataFrame data structure, Counting Time Zones with pandas, MovieLens 1M Data Set, Introduction to pandas Data Structures, DataFrame–DataFrame, Operations between DataFrame and Series–Operations between DataFrame and Series, Using a DataFrame’s Columns–Using a DataFrame’s Columns, Database-style DataFrame Merges–Database-style DataFrame Merges arithmetic operations between Series and, Operations between DataFrame and Series–Operations between DataFrame and Series hierarchical indexing using, Using a DataFrame’s Columns–Using a DataFrame’s Columns merging data with, Database-style DataFrame Merges–Database-style DataFrame Merges dates and times, Index Objects, Reading and Writing Data in Text Format, Date and Time Data Types and Tools, Date and Time Data Types and Tools, Converting between string and datetime–Converting between string and datetime, Converting between string and datetime, Generating Date Ranges–Generating Date Ranges, Generating Date Ranges, Generating Date Ranges, Generating Date Ranges, Scalar Types, Dates and times–Dates and times, Dates and times (see also time series data) data types for, Date and Time Data Types and Tools, Dates and times–Dates and times date ranges, Generating Date Ranges–Generating Date Ranges datetime type, Converting between string and datetime–Converting between string and datetime, Scalar Types, Dates and times DatetimeIndex Index object, Index Objects dateutil package, Converting between string and datetime date_parser argument, Reading and Writing Data in Text Format date_range function, Generating Date Ranges, Generating Date Ranges, Generating Date Ranges dayfirst argument, Reading and Writing Data in Text Format debug function, Other ways to make use of the debugger, Other ways to make use of the debugger debugger, IPython, Interactive Debugger–Other ways to make use of the debugger in IPython, Interactive Debugger–Other ways to make use of the debugger def keyword, Functions defaults, Profiles and Configuration, Default values–Default values profiles, Profiles and Configuration values for dicts, Default values–Default values del keyword, Input and Output Variables, DataFrame, Dict delete method, Index Objects delimited formats, Manually Working with Delimited Formats–Manually Working with Delimited Formats density plots, Histograms and Density Plots–Histograms and Density Plots describe method, Summarizing and Computing Descriptive Statistics, Summarizing and Computing Descriptive Statistics, Plotting Maps: Visualizing Haiti Earthquake Crisis Data, Apply: General split-apply-combine design tips, Code Design Tips–Overcome a fear of longer files, Keep relevant objects and data alive–Keep relevant objects and data alive, Flat is better than nested–Flat is better than nested, Overcome a fear of longer files–Overcome a fear of longer files flat is better than nested, Flat is better than nested–Flat is better than nested keeping relevant objects and data alive, Keep relevant objects and data alive–Keep relevant objects and data alive overcoming fear of longer files, Overcome a fear of longer files–Overcome a fear of longer files det function, Linear Algebra development tools in IPython, Software Development Tools–Profiling a Function Line-by-Line, Interactive Debugger–Other ways to make use of the debugger, Timing Code: %time and %timeit–Timing Code: %time and %timeit, Basic Profiling: %prun and %run -p–Basic Profiling: %prun and %run -p, Profiling a Function Line-by-Line–Profiling a Function Line-by-Line debugger, Interactive Debugger–Other ways to make use of the debugger profiling code, Basic Profiling: %prun and %run -p–Basic Profiling: %prun and %run -p profiling function line-by-line, Profiling a Function Line-by-Line–Profiling a Function Line-by-Line timing code, Timing Code: %time and %timeit–Timing Code: %time and %timeit diag function, Linear Algebra dicts, Interacting with the Operating System, Grouping with Dicts and Series–Grouping with Dicts and Series, Dict–Valid dict key types, Creating dicts from sequences–Creating dicts from sequences, Default values–Default values, Valid dict key types–Valid dict key types, List, Set, and Dict Comprehensions–Nested list comprehensions creating, Creating dicts from sequences–Creating dicts from sequences default values for, Default values–Default values dict comprehensions, List, Set, and Dict Comprehensions–Nested list comprehensions grouping on, Grouping with Dicts and Series–Grouping with Dicts and Series keys for, Valid dict key types–Valid dict key types returning system environment variables as, Interacting with the Operating System diff method, Index Objects, Summarizing and Computing Descriptive Statistics difference method, Set digitize function, numpy.searchsorted: Finding elements in a Sorted Array directories, Interacting with the Operating System, Directory Bookmark System–Directory Bookmark System bookmarking in IPython, Directory Bookmark System–Directory Bookmark System changing, commands for, Interacting with the Operating System discretization, Discretization and Binning–Discretization and Binning div method, Arithmetic methods with fill values divide function, Universal Functions: Fast Element-wise Array Functions .dmg file, Apple OS X donation statistics, Donation Statistics by Occupation and Employer–Donation Statistics by Occupation and Employer, Donation Statistics by State–Donation Statistics by State by occupation and employer, Donation Statistics by Occupation and Employer–Donation Statistics by Occupation and Employer by state, Donation Statistics by State–Donation Statistics by State dot function, Linear Algebra, Linear Algebra, NumPy Matrix Class doublequote option, Manually Working with Delimited Formats downsampling, Resampling and Frequency