Amazon Mechanical Turk

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pages: 346 words: 97,330

Ghost Work: How to Stop Silicon Valley From Building a New Global Underclass by Mary L. Gray, Siddharth Suri

Affordable Care Act / Obamacare, Amazon Mechanical Turk, augmented reality, autonomous vehicles, barriers to entry, basic income, big-box store, bitcoin, blue-collar work, business process, business process outsourcing, call centre, Capital in the Twenty-First Century by Thomas Piketty, cloud computing, collaborative consumption, collective bargaining, computer vision, corporate social responsibility, crowdsourcing, data is the new oil, deindustrialization, deskilling, don't be evil, Donald Trump, Elon Musk, employer provided health coverage, en.wikipedia.org, equal pay for equal work, Erik Brynjolfsson, financial independence, Frank Levy and Richard Murnane: The New Division of Labor, future of work, gig economy, glass ceiling, global supply chain, hiring and firing, ImageNet competition, industrial robot, informal economy, information asymmetry, Jeff Bezos, job automation, knowledge economy, low skilled workers, low-wage service sector, market friction, Mars Rover, natural language processing, new economy, passive income, pattern recognition, post-materialism, post-work, race to the bottom, Rana Plaza, recommendation engine, ride hailing / ride sharing, Ronald Coase, Second Machine Age, sentiment analysis, sharing economy, Shoshana Zuboff, side project, Silicon Valley, Silicon Valley startup, Skype, software as a service, speech recognition, spinning jenny, Stephen Hawking, The Future of Employment, The Nature of the Firm, transaction costs, two-sided market, union organizing, universal basic income, Vilfredo Pareto, women in the workforce, Works Progress Administration, Y Combinator

He worked around the clock to support those who had become dependent on him and his contacts. Then the thing Riyaz feared most happened. He got the following email: I am sorry but your Amazon Mechanical Turk account was closed due to a violation of our Participation Agreement and cannot be reopened. Any funds that were remaining on the account are forfeited, and we will not be able to provide any additional insight or action. You may review the Participation Agreement/Conditions of Use at this URL: http://www.mturk.com/mturk/conditionsofuse Thank you for trying Amazon Mechanical Turk. Best regards, Laverne P.S. We value your feedback, please rate my response using the link below. Amazon Mechanical Turk Please note: this e-mail was sent from an address that cannot accept incoming e-mail. To contact us again, select the Contact Us link related to your inquiry below.

United Nations Development Programme, Global Dimensions of Human Development, Human Development Report (New York: Oxford University Press, 1992). [back] 19. Jesse Chandler, Pam Mueller, and Gabriele Paolacci, “Nonnaïveté Among Amazon Mechanical Turk Workers: Consequences and Solutions for Behavioral Researchers,” Behavior Research Methods 46, no. 1 (March 2014): 112–30, https://doi.org/10.3758/s13428-013-0365-7. [back] 20. Stewart et al., “The Average Laboratory Samples a Population of 7,300 Amazon Mechanical Turk Workers,” Judgment and Decision Making 10, no. 5 (2015): 13; Karën Fort, Gilles Adda, and K. Bretonnel Cohen, “Amazon Mechanical Turk: Gold Mine or Coal Mine?,” Computational Linguistics 37, no. 2 (2011): 413–20. [back] 21. Ruth Schwartz Cowan, More Work for Mother: The Ironies of Household Technology from the Open Hearth to the Microwave, 2nd ed.

And for the past three years, she’s made most of her income working on Amazon’s Mechanical Turk. Before moving back to her hometown, Joan had a full-time job as a technical writer. She drafted and copyedited, among other things, manuals for filing for unemployment insurance in the state of Texas. At first, Joan lived off the money she’d cashed out of her 401(k) plan. But as her mom’s health worsened, Joan looked for work she could do from home. On-demand work seemed like a good fit. Joan turned a spare bedroom into a home office, crowding the small room with a weathered brown chair, computer desk, and large monitor. Then she started searching the internet for work that she could do online. Joan can’t remember how she first found out about Amazon Mechanical Turk, but she suspects that she learned about it on Reddit.


pages: 207 words: 59,298

The Gig Economy: A Critical Introduction by Jamie Woodcock, Mark Graham

Airbnb, Amazon Mechanical Turk, autonomous vehicles, barriers to entry, British Empire, business process, business process outsourcing, call centre, collective bargaining, commoditize, corporate social responsibility, crowdsourcing, David Graeber, deindustrialization, disintermediation, en.wikipedia.org, full employment, future of work, gender pay gap, gig economy, global value chain, informal economy, information asymmetry, inventory management, Jaron Lanier, Jeff Bezos, job automation, knowledge economy, Lyft, mass immigration, means of production, Network effects, new economy, Panopticon Jeremy Bentham, planetary scale, precariat, rent-seeking, RFID, ride hailing / ride sharing, Ronald Reagan, self-driving car, sentiment analysis, sharing economy, Silicon Valley, Silicon Valley ideology, TaskRabbit, The Future of Employment, transaction costs, Travis Kalanick, two-sided market, Uber and Lyft, Uber for X, uber lyft, union organizing, women in the workforce, working poor, young professional

The second kind of work we focus on is ‘cloudwork’. This refers to online freelancing, as well as shorter digital tasks called microwork. Online freelancing involves work that can be completed remotely, like web development, graphic design and writing that happen on platforms like UpWork or Freelancer. Microwork, on the other hand, involves much shorter tasks like image recognition and transcription that are typical on platforms such as Amazon Mechanical Turk. Both forms of work are organized digitally over the internet, with workers completing tasks remotely for the requesting organizations or individuals. Workers live all over the world, doing work that can come from anywhere. The use of digital tools in gig work also makes many jobs increasingly invisible. While some platforms bring workers into contact with customers, others are obscured behind apps and websites.

At the opposite end is cloudwork (microwork), in which there are very low levels of temporality and geographic stickiness: the jobs are of very short duration and can be completed from anywhere with an internet connection. As with online freelancing, which exhibits slightly more geographical stickiness, as well as the potential for longer job duration, platforms provide a way for a client to connect with a worker and set their own rates and conditions, following the model of Upwork or Amazon Mechanical Turk. The platform hosts the requests for work and the response of prospective workers. Geographically tethered platform work requires workers to be in a particular place. This means the platform exerts more control, often involving many of the same controls that a traditional waged employer would deploy. Across both cloudwork types and geographically tethered work, platforms present themselves as different to traditional waged employment.

These tasks were used by clients to ‘post bulk tasks’, which are split up into small fragments for individual workers to complete. Figure 3(a) The availability of cloudwork Source: https://geonet.oii.ox.ac.uk/blog/mapping-the-availability-of-online-labour-in-2019/ Figure 3(b) The location of cloudworkers on the five largest English-language platforms Source: https://geonet.oii.ox.ac.uk/blog/mapping-the-availability-of-online-labour-in-2019/ Amazon’s Mechanical Turk – the world’s most well-known microwork platform – refers to these tasks as ‘artificial artificial intelligence’. These are tasks that usually rely on a distinctly human ability to interpret things (for instance image recognition or sentiment analysis). These are tasks that might, in theory, be performed by AI, but are cheaper and/or quicker to simply outsource to human workers. For some types of task, it may not be a simple case of humans or artificial intelligence, but rather human microworkers embedded into otherwise automated systems through application programming interfaces (APIs).


pages: 491 words: 77,650

Humans as a Service: The Promise and Perils of Work in the Gig Economy by Jeremias Prassl

3D printing, Affordable Care Act / Obamacare, Airbnb, Amazon Mechanical Turk, Andrei Shleifer, autonomous vehicles, barriers to entry, call centre, cashless society, Clayton Christensen, collaborative consumption, collaborative economy, collective bargaining, creative destruction, crowdsourcing, disruptive innovation, Donald Trump, Erik Brynjolfsson, full employment, future of work, George Akerlof, gig economy, global supply chain, hiring and firing, income inequality, information asymmetry, invisible hand, Jeff Bezos, job automation, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, Kickstarter, low skilled workers, Lyft, Mahatma Gandhi, Mark Zuckerberg, market friction, means of production, moral hazard, Network effects, new economy, obamacare, pattern recognition, platform as a service, Productivity paradox, race to the bottom, regulatory arbitrage, remote working, ride hailing / ride sharing, Robert Gordon, Ronald Coase, Rosa Parks, Second Machine Age, secular stagnation, self-driving car, shareholder value, sharing economy, Silicon Valley, Silicon Valley ideology, Simon Singh, software as a service, Steve Jobs, TaskRabbit, The Future of Employment, The Market for Lemons, The Nature of the Firm, The Rise and Fall of American Growth, transaction costs, transportation-network company, Travis Kalanick, two tier labour market, two-sided market, Uber and Lyft, Uber for X, uber lyft, union organizing, working-age population

Doug H, ‘Fired from Uber: why drivers get deactivated, and how to get reacti- vated’, Ride Sharing Driver (21 April 2016), http://www.ridesharingdriver.com/ fired-uber-drivers-get-deactivated-and-reactivated/, archived at https://perma.cc/ 3MQL-4TWD 58. Amazon MTurk, ‘Amazon Mechanical Turk participation agreement’, clause 11, http://www.mturk.com/mturk/conditionsofuse, archived at https://perma. cc/6XKA-6QFL; Dynamo, ‘MTurk suspensions’, http://www.wearedynamo. org/suspensions, archived at https://perma.cc/SH8S-VAHW 59. John Arlidge, ‘We want it all now—but at what price?’, Sunday Times Magazine (10 July 2016), 13. 60. Mariano Mamertino of economics consultancy Indeed, as cited in REC, Gig Economy: The Uberisation of Work (REC 2016), 52. * * * 164 Notes 61. Caroline O’Donovan, ‘Changes to Amazon’s Mechanical Turk platform could cost workers’, BuzzFeed News (23 June 2015), http://www.buzzfeed.com/caro- lineodonovan/changes-to-amazons-mechanical-turk-platform-could-cost- worke?utm_term=.cvjLONY4q0#.ruxM6v1r5a, archived at https://perma.

More recently, the introduction of so-called route-based pricing in certain locations has drawn considerable media attention: Eric Newcomer, ‘Uber starts charging what you’re willing to pay’, Bloomberg (19 May 2017), https:// www.bloomberg.com/news/articles/2017–05–19/uber-s-future-may-rely on-predicting-how-much-you-re-willing-to-pay, archived at https://perma. cc/4J3M-WKXM 37. ‘The “X” rejection and feedback on HITs’, Turk Requesters (30 January 2015), http://turkrequesters.blogspot.co.uk/2015/01/the-x-rejection-and-feedback- on-hits.html, archived at https://perma.cc/A2BK-XT6L; Amazon MTurk, ‘Amazon Mechanical Turk participation agreement’, clause 3(f), http://www. mturk.com/mturk/conditionsofuse, archived at https://perma.cc/6XKA-6QFL; see also Julian Dobson, ‘Mechanical Turk: Amazon’s new underclass’, Huffington Post (21 April 2013), http://www.huffingtonpost.com/julian-dobson/mechanical- turk-amazons-underclass_b_2687431.html, archived at https://perma.cc/9GGZ- 5PL5 (‘There’s no appeal if you think you’ve been exploited or scammed’). 38. Amazon MTurk, ‘Worker web site FAQs’, http://www.mturk.com/mturk/ help?helpPage=worker#how_paid, archived at https://perma.cc/U9TL-MC6K 39.

This tallies with research commissioned by the World Bank, which estimates that a typical online freelancer on Elance-oDesk (now Upwork) or Freelancer.com will work 20–40 hours per week and earn US$200– 750 per month, whilst only ‘a small subset of highly skilled workers . . . can earn up to $3000 per month’: Siou Chew Kuek, Cecilia Paradi-Guilford, Toks Fayomi, Soari Imaizumi, and Panos Ipeirotis, ‘The Global Opportunity in Online Outsourcing’ (World Bank 2015), 42, http://www.ipeirotis.com/wp-content/ uploads/2015/05/The-World-Bank-The-Global-Opportunity-in-Online- Outsourcing.pdf, archived at https://perma.cc/2AGP-TME6 42. Amazon MTurk, ‘Amazon Mechanical Turk pricing’, https://requester.mturk. com/pricing, archived at https://perma.cc/58T4-BUE7; Panagiotis Ipeirotis, ‘Analyzing the Amazon Mechanical Turk marketplace’ (2010) 17(2) XRDS 16, http://dl.acm.org/citation.cfm?id=1869094, archived at https://perma.cc/ 8C4M-74M8 43. Ibid., 19; Paul Hitlin, Research in the Crowdsourcing Age: A Case Study (Pew Research Center 2016), 8, http://assets.pewresearch.org/wp-content/uploads/ sites/14/2016/07/PI_2016.07.11_Mechanical-Turk_FINAL.pdf, archived at https://perma.cc/38NZ-97C4 44.


pages: 285 words: 86,853

What Algorithms Want: Imagination in the Age of Computing by Ed Finn

Airbnb, Albert Einstein, algorithmic trading, Amazon Mechanical Turk, Amazon Web Services, bitcoin, blockchain, Chuck Templeton: OpenTable:, Claude Shannon: information theory, commoditize, Credit Default Swap, crowdsourcing, cryptocurrency, disruptive innovation, Donald Knuth, Douglas Engelbart, Douglas Engelbart, Elon Musk, factory automation, fiat currency, Filter Bubble, Flash crash, game design, Google Glasses, Google X / Alphabet X, High speed trading, hiring and firing, invisible hand, Isaac Newton, iterative process, Jaron Lanier, Jeff Bezos, job automation, John Conway, John Markoff, Just-in-time delivery, Kickstarter, late fees, lifelogging, Loebner Prize, Lyft, Mother of all demos, Nate Silver, natural language processing, Netflix Prize, new economy, Nicholas Carr, Norbert Wiener, PageRank, peer-to-peer, Peter Thiel, Ray Kurzweil, recommendation engine, Republic of Letters, ride hailing / ride sharing, Satoshi Nakamoto, self-driving car, sharing economy, Silicon Valley, Silicon Valley ideology, Silicon Valley startup, social graph, software studies, speech recognition, statistical model, Steve Jobs, Steven Levy, Stewart Brand, supply-chain management, TaskRabbit, technological singularity, technoutopianism, The Coming Technological Singularity, the scientific method, The Signal and the Noise by Nate Silver, The Structural Transformation of the Public Sphere, The Wealth of Nations by Adam Smith, transaction costs, traveling salesman, Turing machine, Turing test, Uber and Lyft, Uber for X, uber lyft, urban planning, Vannevar Bush, Vernor Vinge, wage slave

Bogost, Unit Operations; this sampling of tasks was offered on the site on August 15, 2014. 49. Ipeirotis, “Analyzing the Amazon Mechanical Turk Marketplace,” 21. 50. “Mechanical Turk Concepts.” 51. Riskin, “Machines in the Garden.” 52. Ibid., 27. 53. Zuniga, “Kasparov Tries New Strategy to Thwart Computer Opponent.” 54. Finley, “Did a Computer Bug Help Deep Blue Beat Kasparov? | WIRED.” 55. Silver, The Signal and the Noise, 288. 56. Isaacson, “‘Smarter Than You Think,’ by Clive Thompson.” 57. Ipeirotis, “Analyzing the Amazon Mechanical Turk Marketplace,” 21. 58. Glanz, “Data Centers Waste Vast Amounts of Energy, Belying Industry Image.” 59. Cooper, Ipeirotis, and Suri, “The Computer Is the New Sewing Machine: Benefits and Perils of Crowdsourcing”; “Amazon Mechanical Turk.” 60. Limer, “My Brief and Curious Life As a Mechanical Turk.” 61.

Bitcoin Wiki, July 20, 2015. https://en.bitcoin.it/wiki/Controlled_supply. Cooper, Matt, Panagiotis G. Ipeirotis, and Siddharth Suri. “The Computer Is the New Sewing Machine: Benefits and Perils of Crowdsourcing.” Presented at the WWW 2011, Hyderabad, India, March 28, 2011. http://www.ipeirotis.com/wp-content/uploads/2012/01/p325.pdf. Cushing, Ellen. “Amazon Mechanical Turk: The Digital Sweatshop.” Utne, January/February 2013. http://www.utne.com/science-and-technology/amazon-mechanical-turk-zm0z13jfzlin.aspx. D’Alembert, Jean Le Rond. Preliminary Discourse. In Encyclopedia of Diderot & d’Alembert—Collaborative Translation Project. Translated by Richard N. Schwab and Walter E. Rex. Ann Arbor: Michigan Publishing, University of Michigan Library, 2009. http://hdl.handle.net/2027/spo.did2222.0001.083. Darnton, Robert.

Understanding Comics: The Invisible Art. Reprint ed. New York: William Morrow Paperbacks, 1994. McCulloch, Warren S., and Walter Pitts. “A Logical Calculus of the Ideas Immanent in Nervous Activity.” Bulletin of Mathematical Biophysics 5 (4) (December 1943): 115–133. doi:10.1007/BF02478259. “Mechanical Turk Concepts.” In Amazon Mechanical Turk Requester UI Guide, API Version 2014-08-15. Amazon. Accessed May 21, 2015. http://docs.aws.amazon.com/AWSMechTurk/latest/RequesterUI/mechanical-turk-concepts.html. Metz, Cade. “Google’s AI Takes Historic Match against Go Champ with Third Straight Win.” WIRED, March 12, 2016. http://www.wired.com/2016/03/third-straight-win-googles-ai-claims-victory-historic-match-go-champ. Meyers, Peter J. “Knowledge Graph 2.0: Now Featuring Your Knowledge.” Moz, March 25, 2014. http://moz.com/blog/knowledge-graph-2-now-featuring-your-knowledge.


pages: 350 words: 98,077

Artificial Intelligence: A Guide for Thinking Humans by Melanie Mitchell

Ada Lovelace, AI winter, Amazon Mechanical Turk, Apple's 1984 Super Bowl advert, artificial general intelligence, autonomous vehicles, Bernie Sanders, Claude Shannon: information theory, cognitive dissonance, computer age, computer vision, dark matter, Douglas Hofstadter, Elon Musk, en.wikipedia.org, Gödel, Escher, Bach, I think there is a world market for maybe five computers, ImageNet competition, Jaron Lanier, job automation, John Markoff, John von Neumann, Kevin Kelly, Kickstarter, license plate recognition, Mark Zuckerberg, natural language processing, Norbert Wiener, ought to be enough for anybody, pattern recognition, performance metric, RAND corporation, Ray Kurzweil, recommendation engine, ride hailing / ride sharing, Rodney Brooks, self-driving car, sentiment analysis, Silicon Valley, Singularitarianism, Skype, speech recognition, Stephen Hawking, Steve Jobs, Steve Wozniak, Steven Pinker, strong AI, superintelligent machines, theory of mind, There's no reason for any individual to have a computer in his home - Ken Olsen, Turing test, Vernor Vinge, Watson beat the top human players on Jeopardy!

Li soon figured out that at the rate they were going, it would take ninety years to complete the task.4 Li and her collaborators brainstormed about possible ways to automate this work, but of course the problem of deciding if a photo is an instance of a particular noun is the task of object recognition itself! And computers were nowhere near to being reliable at this task, which was the whole reason for constructing ImageNet in the first place. The group was at an impasse, until Li, by chance, stumbled upon a three-year-old website that could deliver the human smarts that ImageNet required. The website had the strange name Amazon Mechanical Turk. Mechanical Turk According to Amazon, its Mechanical Turk service is “a marketplace for work that requires human intelligence.” The service connects requesters, people who need a task accomplished that is hard for computers, with workers, people who are willing to lend their human intelligence to a requester’s task, for a small fee (for example, labeling the objects in a photo, for ten cents per photo). Hundreds of thousands of workers have signed up, from all over the world.

In the case of image captioning, each training example consists of an image paired with a caption. The images were downloaded from repositories such as Flickr.com, and the captions for these images were produced by humans—namely, Amazon Mechanical Turk workers, who were hired by Google for this study. Because captions can be so variable, each image was given a caption by five different people. Thus, each image appears in the training set five times, each time paired with a different caption. Figure 40 shows a sample training image and the captions given by the Mechanical Turk workers. FIGURE 39: Sketch of Google’s automated image-captioning system FIGURE 40: Sample training image with captions given by Amazon Mechanical Turk workers The Show and Tell decoder network was trained on about eighty thousand image-caption pairs. Figure 41 gives a few examples of captions that the trained Show and Tell system generated on test images—that is, images that were not in its training set.

Mechanical Turk is the embodiment of Marvin Minsky’s “Easy things are hard” dictum: the human workers are hired to perform the “easy” tasks that are currently too hard for computers. The name Mechanical Turk comes from a famous eighteenth-century AI hoax: the original Mechanical Turk was a chess-playing “intelligent machine,” which secretly hid a human who controlled a puppet (the “Turk,” dressed like an Ottoman sultan) that made the moves. Evidently, it fooled many prominent people of the time, including Napoleon Bonaparte. Amazon’s service, while not meant to fool anyone, is, like the original Mechanical Turk, “Artificial Artificial Intelligence.”5 Fei-Fei Li realized that if her group paid tens of thousands of workers on Mechanical Turk to sort out irrelevant images for each of the WordNet terms, the whole data set could be completed within a few years at a relatively low cost. In a mere two years, more than three million images were labeled with corresponding WordNet nouns to form the ImageNet data set.


pages: 246 words: 68,392

Gigged: The End of the Job and the Future of Work by Sarah Kessler

Affordable Care Act / Obamacare, Airbnb, Amazon Mechanical Turk, basic income, bitcoin, blockchain, business cycle, call centre, cognitive dissonance, collective bargaining, crowdsourcing, David Attenborough, Donald Trump, East Village, Elon Musk, financial independence, future of work, game design, gig economy, income inequality, information asymmetry, Jeff Bezos, job automation, law of one price, Lyft, Mark Zuckerberg, market clearing, minimum wage unemployment, new economy, payday loans, post-work, profit maximization, QR code, race to the bottom, ride hailing / ride sharing, Second Machine Age, self-driving car, shareholder value, sharing economy, Silicon Valley, Snapchat, TaskRabbit, Travis Kalanick, Uber and Lyft, Uber for X, uber lyft, union organizing, universal basic income, working-age population, Works Progress Administration, Y Combinator

In this case, Mechanical Turk was Amazon’s way of finding thousands of examples of each color so that it could train its algorithms to automatically sort searches for “blue shoes” and “gray sweaters.” Improving technology in this way was one reason that Amazon had created Mechanical Turk. Another reason was to compensate for technology’s shortcomings with human intelligence. Amazon created one of its first applications that used Mechanical Turk in the days when people could email via cell phones, but couldn’t yet access the internet. The idea was that people on their “mobile email” could send questions, such as “Where is the best restaurant near me?” and receive an answer almost immediately. It seemed like magic, but workers like Kristy were at the other end, Googling and answering for a penny per question. Amazon had not launched the Mechanical Turk platform with a promise to create jobs, the way that Uber had early on bragged about adding “20,000 new driver jobs” to the economy every month.

Only If You Pay Me More: Field Experiments Support Compensating Wage Differentials Theory. Working paper. October 2015. http://static1.squarespace.com/static/53c31c5ce4b053fc7d131b18/t/56405d98e4b07bcd9d9704a1/1447058840358/Portner+-+compensating+wage+differentials.pdf. 23   Salehi et al. We Are Dynamo. 24   Harris, Mark. Amazon Mechanical Turk Workers Protest: “I Am a Human Being, Not an Algorithm.” The Guardian. December 3, 2014. https://www.theguardian.com/technology/2014/dec/03/amazon-mechanical-turk-workers-protest-jeff-bezos. 25   Katz, Miranda. Amazon’s Turker Crowd Has Had Enough. Wired. August 23, 2017. https://www.wired.com/story/amazons-turker-crowd-has-had-enough/. 26   The traditional unions that once helped create the American middle class have nowhere near as much influence today as they once did.

Amazon had not launched the Mechanical Turk platform with a promise to create jobs, the way that Uber had early on bragged about adding “20,000 new driver jobs” to the economy every month. Rather, it had built the website as a way to integrate human intelligence with code—as a service for programmers. TechCrunch’s founder wrote shortly after the product launched that. “Amazon’s new Mechanical Turk product is brilliant because it will help application developers overcome certain types of problems (resulting in the possibility for new kinds of applications) and somewhat scary because I can’t get the Matrix-we-are-all-plugged-into-a-machine vision out of my head.” He called the workers who would be doing the work “Volunteers.”3 Early characterizations of Mechanical “Turkers” often portrayed them as people who were playing a game or passing the time while they watched television, which echoed the way that staffing agencies had portrayed temporary workers in the 1950s and 60s.


pages: 502 words: 107,510

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

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

Each of these methods can be performed within the MATTER cycle—they still require coming up with an annotation goal, finding a specification, and defining guidelines for how the annotation will be applied, but the guidelines here aren’t the traditional approach of writing an instruction manual and having the annotators read and apply what they learn. Amazon’s Mechanical Turk One approach to crowdsourcing is this: rather than hire a small number of annotators to annotate a corpus at relatively high wages, the annotation task is divided into very small tasks, which are then distributed over a large number of people for very small amounts of money per task. The most widely used resource for this at the moment is Amazon’s Mechanical Turk (MTurk), where researchers (or businesses) create Human Intelligence Tasks (HITs) which are then posted on something like a job board, and Turkers (as the workers are called) have the option to take on a task, and get paid for completing it.

“Annotating expressions of opinions and emotions in language.” 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.”

representative sampling, importance of, The Ideal Corpus: Representative and Balanced resources for existing, Background Research–NLP Challenges revising distributions/content of, Corpus Distributions and Content size considerations with, The Size of Your Corpus size, comparing with other corpora, Existing Corpora TimeML, building for, and evolution of, Building the Corpus crowdsourcing (of annotation tasks), The Infrastructure of an Annotation Project, Crowdsourcing Annotation–User-Generated Content, Amazon’s Mechanical Turk, Games with a Purpose (GWAP)–Games with a Purpose (GWAP), User-Generated Content Games with a Purpose (GWAP), Games with a Purpose (GWAP)–Games with a Purpose (GWAP) Mechanical Turk (MTurk), Amazon’s Mechanical Turk user-generated content, User-Generated Content D DARPA (Defense Advanced Research Projects Agency), Related Research Data Category Registry (DCR), Annotation format standards data preperation for annotation, Preparing Your Data for Annotation–Writing the Annotation Guidelines, Metadata, Preprocessed Data, Splitting Up the Files for Annotation metadata and the potential for bias in, Metadata preprocessed data, advantages/concerns with, Preprocessed Data splitting files for annotation/testing, Splitting Up the Files for Annotation data sparseness problem, Naïve Bayes Learning dataset, Assembling Your Dataset (see corpus, corpora) DCR (Data Category Registry), Annotation format standards decision tree, Classification decision tree learning, Decision Tree Learning–Decision Tree Learning development corpus, Train and Test the Algorithms over the Corpus development-test set, Train and Test the Algorithms over the Corpus directed acyclic graph (DAG), Kinds of Annotation distributed method of annotation, The Infrastructure of an Annotation Project document annotation, Model the Phenomenon document classification, What Is Natural Language Processing?


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Ours to Hack and to Own: The Rise of Platform Cooperativism, a New Vision for the Future of Work and a Fairer Internet by Trebor Scholz, Nathan Schneider

1960s counterculture, activist fund / activist shareholder / activist investor, Airbnb, Amazon Mechanical Turk, barriers to entry, basic income, bitcoin, blockchain, Build a better mousetrap, Burning Man, capital controls, citizen journalism, collaborative economy, collaborative editing, collective bargaining, commoditize, conceptual framework, crowdsourcing, cryptocurrency, Debian, deskilling, disintermediation, distributed ledger, Ethereum, ethereum blockchain, future of work, gig economy, Google bus, hiring and firing, income inequality, information asymmetry, Internet of things, Jacob Appelbaum, Jeff Bezos, job automation, Julian Assange, Kickstarter, lake wobegon effect, low skilled workers, Lyft, Mark Zuckerberg, means of production, minimum viable product, moral hazard, Network effects, new economy, offshore financial centre, openstreetmap, peer-to-peer, post-work, profit maximization, race to the bottom, ride hailing / ride sharing, SETI@home, shareholder value, sharing economy, Shoshana Zuboff, Silicon Valley, smart cities, smart contracts, Snapchat, TaskRabbit, technoutopianism, transaction costs, Travis Kalanick, Uber for X, uber lyft, union organizing, universal basic income, Whole Earth Catalog, WikiLeaks, women in the workforce, Zipcar

Gone are those old associations of town meetings and voting booths; gone are co-ownership, co-governance, and accountability. Words are the tools of my trade as a writer, so I like to have a handle on what they mean. We rely on them so much. They connect us to each other; they remind us what we’re capable of. And I hope that the Internet can help us make our definitions of democracy more ambitious, rather than redefining it out of existence. In late 2014 I was reporting a story about Amazon’s Mechanical Turk platform, a website where users can find entirely online piece-work—jobs that might take between seconds and hours, like transcribing a receipt, providing feedback on an ad, or taking a sociological survey. I went to Trebor Scholz’s Digital Labor conference in New York, which included real-life Mechanical Turkers. One was a wife whose husband lost his job, for instance; another was a former cable technician.

Initially, at these events, discussions focused on the Italian Workerists, immaterial labor, and “playbor.” Artists like Burak Arikan, Alex Rivera, Stephanie Rothenberg, and Dmytri Kleiner played pioneering roles in alerting the public to these issues. Later, debates became more concerned with “crowd fleecing,” the exploitation of thousands of invisible workers in crowdsourcing systems like Amazon Mechanical Turk or content moderation farms in the Philippines. Over the past few years, the search for concrete alternatives for a better future of work has become more dynamic. The theory of platform cooperativism has two main tenets: communal ownership and democratic governance. It is bringing together 135 years of worker self-management, the roughly 170 years of the cooperative movement, and commons-based peer production with the compensated digital economy.

“Just like domestic workers were tucked away in people’s houses, digital laborers remain invisible, tucked away in between algorithms,” said Trebor Scholz in his opening talk at the Platform Cooperativism conference. This observation resonated with me, because I worked for many years with homecare workers and their allies in the disability rights movement, who have the slogan “Invisible No More.” One of the big differences between domestic workers and platform workers (especially online-only platforms like Amazon’s Mechanical Turk) is that the domestic workers have word of mouth, and references, and do work that is geographically located in a specific place. Most of us employed in traditional jobs have things like resumes, coworkers that we can rely on for references, networks of people who will tell us about jobs, and other advantages that help when we’re looking for new work. I personally have changed jobs twice in the past two years, and both times I took my reputation with me—through word of mouth, through work-related networks, and yes, through LinkedIn recommendations.


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

activist fund / activist shareholder / activist investor, Airbnb, algorithmic trading, Amazon Mechanical Turk, Andrew Keen, bank run, banking crisis, barriers to entry, bitcoin, blockchain, Burning Man, business process, buy and hold, 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, corporate raider, creative destruction, crowdsourcing, cryptocurrency, disintermediation, diversified portfolio, Elon Musk, Erik Brynjolfsson, Ethereum, 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, Marc Andreessen, Mark Zuckerberg, market bubble, market fundamentalism, Marshall McLuhan, means of production, medical bankruptcy, minimum viable product, Mitch Kapor, 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, The Future of Employment, trade route, transportation-network company, Turing test, Uber and Lyft, Uber for X, uber lyft, unpaid internship, Y Combinator, young professional, zero-sum game, Zipcar

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. Workers log into one of the platforms from home or an Internet café and then choose from a series of tasks on offer. They might be paid three cents each time they identify the subject of a photo, transcribe a sentence from a video lecture, or list the items in a scanned receipt. These are invariably mundane tasks—the sorts of data entry that wouldn’t even exist were so many business processes not already tied to computer databases, and ones that will certainly be carried out by computers themselves sooner than later.

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. The other answer—one I’ve argued myself—is for displaced workers to learn code.

Amazon then leveraged its monopoly in books and free shipping to develop monopolies in other verticals, beginning with home electronics (bankrupting Circuit City and Best Buy), and then every other link in the physical and virtual fulfillment chain, from shoes and food to music and videos. Finally, Amazon flips into personhood by reversing the traditional relationship between people and machines. Amazon’s patented recommendation engines attempt to drive our human selection process. Amazon Mechanical Turks gave computers the ability to mete out repetitive tasks to legions of human drones. The computers did the thinking and choosing; the people pointed and clicked as they were instructed or induced to do. Neither Amazon nor its founder, Jeff Bezos, is slipping to new lows here. The company is simply operating true to the core program of corporatism, expressed through new digital means. Amazingly, as of this writing, anyway, Amazon itself operates at a loss.


Speaking Code: Coding as Aesthetic and Political Expression by Geoff Cox, Alex McLean

4chan, Amazon Mechanical Turk, augmented reality, bash_history, bitcoin, cloud computing, computer age, computer vision, crowdsourcing, dematerialisation, Donald Knuth, Douglas Hofstadter, en.wikipedia.org, Everything should be made as simple as possible, finite state, Gödel, Escher, Bach, Jacques de Vaucanson, Larry Wall, late capitalism, means of production, natural language processing, new economy, Norbert Wiener, Occupy movement, packet switching, peer-to-peer, Richard Stallman, Ronald Coase, Slavoj Žižek, social software, social web, software studies, speech recognition, stem cell, Stewart Brand, The Nature of the Firm, Turing machine, Turing test, Vilfredo Pareto, We are Anonymous. We are Legion, We are the 99%, WikiLeaks

In orthodox Marxism, the capitalist mode of production simultaneously produces and reproduces the antagonistic social relations between labor and capital contained within the site of production. But labor is no longer simply contained by 48 Chapter 2 Figure 2.3 Amazon Mechanical Turk’s homepage (2011). Screenshot. the factory walls, as part of a process that Marx termed “real subsumption” (in Grundrisse) to conceptualize the way class exploitation is subsumed into the wider social realm.36 This is clearly more evident under contemporary conditions than it was in the mid-nineteenth century, as the process of subsumption is now assisted by informational technologies and networked intelligence. Amazon’s Mechanical Turk is a case in point. Intriguingly named after Kempelen’s automaton, it is an online marketplace for precarious work, running since 2005. It does not hide the labor of the worker but celebrates its immaterial character.

Networked communication technologies play a significant role in these processes of subjectification as they relate to general intellect, forming networked intelligence.47 With this concept (an elaboration of subsumption), already Marx had predicted that the productive forces of the intellect, of human knowledge and skills, would be incorporated into capital itself. The crucial issue, both then and now, is that general intellect Code Working 51 unleashes contradictions by combining technical knowledge and the social cooperation of bodies. The concept is somewhat materialized in the procedures of Amazon’s Mechanical Turk and more generally in coding cultures, where connectivity is reflected in the open-source and free software movements as an example of how technical expertise and socialized labor can be shared and recombined effectively. Such ways of working with software are arguably more robust and less bug-ridden as a result of collective development, but the contradictions are also evident, as this approach becomes the orthodoxy in the release of proprietary software development too.

The spread and speed of communications contributes to “psychopathology” according to Berardi, as collective intelligence is no longer able to adequately process the complexity of information being generated and we have forgotten the lyrics and rhythms that once bound communities together (as in the singing of folk songs). Happiness is exemplified by the public performance of songs. “For Marx, the privileged example of really free working—happiness itself—is ‘composition,’ the construction of the communist score . . . communism whose song will free the space in which it resonates, and spreads.”118 A further example is Aaron Koblin and Daniel Massey’s artwork Bicycle Built for Two Thousand (2009), using Amazon’s Mechanical Turk crowdsourcing web service as mentioned earlier in the chapter. This time over two thousand recorded voices are collected and assembled into the song “Daisy Bell,” the same song that was used in the first example of musical speech synthesis in 1962 (which made the IBM 7094 the first computer to sing a song).119 Yet the comparison between the computer-synthesized vocals and the one created with distributed humans is not very encouraging, as both have been effectively synthesized.


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Superminds: The Surprising Power of People and Computers Thinking Together by Thomas W. Malone

agricultural Revolution, Airbnb, Albert Einstein, Amazon Mechanical Turk, Apple's 1984 Super Bowl advert, Asperger Syndrome, Baxter: Rethink Robotics, bitcoin, blockchain, business process, call centre, clean water, creative destruction, crowdsourcing, Donald Trump, Douglas Engelbart, Douglas Engelbart, drone strike, Elon Musk, en.wikipedia.org, Erik Brynjolfsson, experimental economics, Exxon Valdez, future of work, Galaxy Zoo, gig economy, happiness index / gross national happiness, industrial robot, Internet of things, invention of the telegraph, inventory management, invisible hand, Jeff Rulifson, jimmy wales, job automation, John Markoff, Joi Ito, Joseph Schumpeter, Kenneth Arrow, knowledge worker, longitudinal study, Lyft, Marshall McLuhan, Occupy movement, Pareto efficiency, pattern recognition, prediction markets, price mechanism, Ray Kurzweil, Rodney Brooks, Ronald Coase, Second Machine Age, self-driving car, Silicon Valley, slashdot, social intelligence, Stephen Hawking, Steve Jobs, Steven Pinker, Stewart Brand, technological singularity, The Nature of the Firm, The Wealth of Nations by Adam Smith, The Wisdom of Crowds, theory of mind, Tim Cook: Apple, transaction costs, Travis Kalanick, Uber for X, uber lyft, Vernor Vinge, Vilfredo Pareto, Watson beat the top human players on Jeopardy!

Some have discovered a particular talent for putting together software components that others have written. Some specialize in fixing bugs in other people’s code. In the great tradition of division of labor, this hyperspecialization pays off. Topcoder can often provide its clients with development work comparable in quality to what they would get through more traditional means, but at as little as 25 percent of the cost. Microtasks on Amazon Mechanical Turk Amazon’s Mechanical Turk service is an even more extreme example of hyperspecialization. It’s a kind of online labor market, but instead of finding people to do programming tasks that might take hours or days, Mechanical Turk finds people to do microtasks, which might take only a few minutes and earn them only a few pennies. The name Mechanical Turk comes from a famous chess-playing machine that defeated chess players in courts all over Europe during the 18th century (see the image below).2 The machine was eventually revealed to be a hoax, however.

Gray and Siddharth Suri, “The Humans Behind the AI Curtain,” Harvard Business Review, January 9, 2017, https://hbr.org/2017/01/the-humans-working-behind-the-ai-curtain. 4. Jonathan Zittrain, “The Internet Creates a New Kind of Sweatshop,” Newsweek, December 7, 2009, http://www.newsweek.com/internet-creates-new-kind-sweatshop-75751; Fiona Graham, “Crowdsourcing Work: Labour on Demand or Digital Sweatshop?” BBC News, October 22, 2010, http://www.bbc.com/news/business-11600902; Ellen Cushing, “Amazon Mechanical Turk: The Digital Sweatshop,” Utne Reader, January/February 2013, http://www.utne.com/science-and-technology/amazon-mechanical-turk-zm0z13jfzlin. 5. Miranda Katz, “Amazon’s Turker Crowd Has Had Enough,” Wired, August 23, 2017, https://www.wired.com/story/amazons-turker-crowd-has-had-enough. 6. This comparison was suggested by David Nordfors, “The Untapped $140 Trillion Innovation for Jobs Market,” TechCrunch, February 21, 2015, https://techcrunch.com/2015/02/21/the-untapped-140-trillion-innovation-for-jobs-market. 7.

I think it’s likely that there will be many more examples of machines playing the role of managers in the future. For instance, the CrowdForge system, developed by my friends Aniket Kittur, Robert Kraut, and their colleagues at Carnegie Mellon University, uses online workers to write documents like encyclopedia articles.7 We’ll call the online workers Turkers because they are recruited from an Amazon service called Mechanical Turk, which we’ll see in more detail later. The process begins with the system asking Turkers to come up with an outline for a document—say, an encyclopedia article about New York City. An outline for such an article might, for example, include sections for attractions, a brief history, and so forth (see the following chart).8 For each section in the outline, the system then asks other Turkers to find facts that might be relevant for that section.


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Rage Inside the Machine: The Prejudice of Algorithms, and How to Stop the Internet Making Bigots of Us All by Robert Elliott Smith

Ada Lovelace, affirmative action, AI winter, Alfred Russel Wallace, Amazon Mechanical Turk, animal electricity, autonomous vehicles, Black Swan, British Empire, cellular automata, citizen journalism, Claude Shannon: information theory, combinatorial explosion, corporate personhood, correlation coefficient, crowdsourcing, Daniel Kahneman / Amos Tversky, desegregation, discovery of DNA, Douglas Hofstadter, Elon Musk, Fellow of the Royal Society, feminist movement, Filter Bubble, Flash crash, Gerolamo Cardano, gig economy, Gödel, Escher, Bach, invention of the wheel, invisible hand, Jacquard loom, Jacques de Vaucanson, John Harrison: Longitude, John von Neumann, Kenneth Arrow, low skilled workers, Mark Zuckerberg, mass immigration, meta analysis, meta-analysis, mutually assured destruction, natural language processing, new economy, On the Economy of Machinery and Manufactures, p-value, pattern recognition, Paul Samuelson, performance metric, Pierre-Simon Laplace, precariat, profit maximization, profit motive, Silicon Valley, social intelligence, statistical model, Stephen Hawking, stochastic process, telemarketer, The Bell Curve by Richard Herrnstein and Charles Murray, The Future of Employment, the scientific method, The Wealth of Nations by Adam Smith, The Wisdom of Crowds, theory of mind, Thomas Bayes, Thomas Malthus, traveling salesman, Turing machine, Turing test, twin studies, Vilfredo Pareto, Von Neumann architecture, women in the workforce

But what happens when we can’t actually see what’s going on, much like the trick Vaucanson played on the public with the hidden guise of his Digesting Duck, or the fraud committed by von Kempelen with the chess master hidden inside his chess playing Turk? Without a hint of irony, in 2005 Amazon launched a crowdsourcing Internet marketplace called Amazon Mechanical Turk, the object of which is to crowdsource human intelligence to undertake micro-tasks that computers are currently unable to do. Amazon’s Mechanical Turk is a sort of post-irony imitation of its eighteenth-century predecessor. It is accessed through the Internet through an API (application programming interface), precisely as if its internal operations were those of Internet software. Employers can use this interface to formally specify a simple task called a Human Intelligence Task (or HIT).

Seattle Times, www.seattletimes.com/business/amazon/amazon-has-patented-a-system-that-would-put-workers-in-a-cage-on-top-of-a-robot/ 5Ayhan Aytes, 2013, Return of the Crowds: Mechanical Turk and Neoliberal States of Exception. In Trebor Sholtz (ed.) Digital Labor: The Internet as Playground and Factory. New York: Routledge, https://ayhanaytes.files.wordpress.com/2014/06/returnofthecrowds_aytes.pdf 6Alana Semuels, 2018, The Internet Is Enabling a New Kind of Poorly Paid Hell. The Atlantic, www.theatlantic.com/business/archive/2018/01/amazon-mechanical-turk/551192/ 7Sarah Butler, 2017, How Deliveroo’s ‘Dark Kitchens’ Are Catering from Car Parks. Guardian, www.theguardian.com/business/2017/oct/28/deliveroo-dark-kitchens-pop-up-feeding-the-city-london 8John Harris, 2018, Are Dark Kitchens the Satanic Mills of Our Era? Guardian, www.theguardian.com/commentisfree/2018/oct/09/dark-kitchens-satanic-mills-deliveroo 9Kate Crawford and Vladan Joler, 2018, Anatomy of an AI System: The Amazon Echo as an Anatomical Map of Human Labor, Data and Planetary Resources.

Penguin. 4Disagreements over these matters would actually prompt Galvani’s colleague, Alessandro Volta, to create the first real battery, and with it the modern idea of electricity. 5W. Bernardi, 2001, The Controversy Over Animal Electricity in 18th-Century Italy: Galvani, Volta, and Others. Revue D’histoire des Sciences, 54: 53–70, www.edumed.org.br/cursos/neurociencia/controversy-bernardi.pdf INDEX abacus, abaci, here, here, here, here ACLU, here Albright, Jonathan, here Alexa. See Amazon’s Echo AlphaGo, here, here, here Amazon, here, here, here Amazon Mechanical Turk, here Amazon’s Echo, here American Eugenics Records Office, here American Study Group, here antibodies, here, here antigens, here, here Aristotle, here, here, here, here, here Arrow, Kenneth, here associationism, here, here astragalus, astragali, here, here, here automata, here, here, here, here Aytes, Ayhan, here Babbage, Charles, here, here, here, here, here, here, here, here, here, here, here Babbage Effect, here, here, here Babbage’s Engines, here, here, here, here, here, here, here, here Bacon, Francis, here Bayes, Thomas, here Bayesian inference, here Bayesian reasoning, here, here Bayes’ rule, here Bedford College for Women, here Bell Curve, here, here, here, here, here, here, here, here, here, here, here, here Bell Laboratories, here Bernoulli, Jacob, here, here Binet, Alfred, here, here, here binomial distribution, here black swans, here, here, here Blackwell, Antoinette Brown, here Bloomfield, Leonard, here Box, George, here, here, here Brexit, here, here, here, here brittleness, here, here, here, here, here, here Bryan, William Jennings, here Bryon, Lord, here, here Buolamwini, Joy, here Burks, Arthur, here Byron, Lord, here, here, here, here Cajal, Santiago Ramon y, here Cambridge Analytica, here, here Campbell, Joseph, here Cardano, Gerolamo, here, here, here, here, here Cardwell, Chris, here Carroll, Galen, here Cattell, Raymond, here Central Limit Theorem.


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

active measures, affirmative action, Albert Einstein, Amazon Mechanical Turk, Black Swan, business cycle, butterfly effect, Carmen Reinhart, Cass Sunstein, clockwork universe, cognitive dissonance, coherent worldview, 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, George Santayana, happiness index / gross national happiness, high batting average, hindsight bias, illegal immigration, industrial cluster, 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, Laplace demon, 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, Pierre-Simon Laplace, planetary scale, prediction markets, pre–internet, RAND corporation, random walk, RFID, school choice, Silicon Valley, social intelligence, 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

colleague Winter Mason and I conducted a series of Web-based experiments in which subjects were paid at different rates to perform a variety of simple repetitive tasks, like placing a series of photographs of moving traffic into the correct temporal sequence, or uncovering words hidden in a rectangular grid of letters. All our participants were recruited from a website called Amazon’s Mechanical Turk, which Amazon launched in 2005 as a way to identify duplicate listings among its own inventory. Nowadays, Mechanical Turk is used by hundreds of businesses looking to “crowd-source” a wide range of tasks, from labeling objects in an image to characterizing the sentiment of a newspaper article or deciding which of two explanations is clearer. However, it is also an extremely effective way to recruit subjects for psychology experiments—much as psychologists have done over the years by posting flyers around college campuses—except that because workers (or “turkers”) are usually paid on the order of a few cents per task, it can be done for a fraction of the usual cost.21 In total, our experiments involved hundreds of participants who completed tens of thousands of tasks.

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. Unsure what to call your next book? Rather than tossing around ideas with your editor, you can run a quick poll on Mechanical Turk and get a thousand opinions in a matter of hours, for about $10—or better yet, have the “turkers” come up with the suggestions as well as voting on them.

Communication technologies, like e-mail, cell phones, and instant messaging now implicitly trace out social networks among billions of individuals, along with the flow of information among them. Online communities such as Facebook, Twitter, Wikipedia, and World of Warcraft facilitate interactions among people in ways that both promote new kinds of social activity and also record it. Crowdsourcing sites like Amazon’s Mechanical Turk are increasingly being used as “virtual labs” in which researchers can run psychological and behavioral experiments.12 And Web search, online media, and electronic commerce are generating ever-increasing insight into the intentions and actions of people everywhere. The capability to observe the actions and interactions of potentially billions of people presents some serious issues about the rights and privacy of individuals, and so we must proceed with caution.13 Nevertheless, these technologies also exhibit enormous scientific potential, allowing us for the first time in history to observe, in high fidelity, the real-time behavior of large groups, and even societies as a whole.


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Designing Social Interfaces by Christian Crumlish, Erin Malone

A Pattern Language, Amazon Mechanical Turk, anti-pattern, barriers to entry, c2.com, carbon footprint, cloud computing, collaborative editing, creative destruction, crowdsourcing, en.wikipedia.org, Firefox, game design, ghettoisation, Howard Rheingold, hypertext link, if you build it, they will come, Merlin Mann, Nate Silver, Network effects, Potemkin village, recommendation engine, RFC: Request For Comment, semantic web, SETI@home, Skype, slashdot, social graph, social software, social web, source of truth, stealth mode startup, Stewart Brand, telepresence, The Wisdom of Crowds, web application

. • Keep track of tasks that have been claimed but not completed by their deadline, so that they may be returned to the general pool and reassigned. • Ideally, offer a dashboard view for management of the project. • Where appropriate, incorporate a mechanism for compensation for the participants (Figure 12-19). Download at WoweBook.Com Collaboration 329 Figure 12-19. Tasks for Amazon’s Mechanical Turk all come with price tags, so it’s easy to decide if you’re willing to do the work for the payment offered. Why Crowdsourcing breaks large jobs into pieces that can be tackled with a much lower commitment threshold, taking advantage of the loose ties in social networks. As seen on Amazon Mechanical Turk (http://www.mturk.com/mturk/welcome) Assignment Zero (http://zero.newassignment.net/) The ESP Game (http://www.cs.cmu.edu/~biglou/ESP.pdf) iStockphoto (http://istockphoto.com) ReCAPTCHA (http://recaptcha.net/) SETI@home (http://setiathome.ssl.berkeley.edu/) Threadless (http://threadless.com) Download at WoweBook.Com 330 Chapter 12: Barnraising Further Reading “Berners-Lee on the read/write web,” BBC News, August 9, 2005, http://news.bbc.co.uk/2/ hi/technology/4132752.stm Cross Cultural Collaboration, http://crossculturalcollaboration.pbwiki.com/ “Deriving Process-driven Collaborative Editing Pattern from Collaborative Learning Flow Patterns,” by Olivera Marjanovic, Hala Skaf-Molli, Pascal Molli, and Claude Godart, http://www.ifets.info/journals/10_1/12.pdf “Edit This Page,” by Dave Winer, http://www.scripting.com/davenet/1999/05/24/editThisPage.html Edit This Page PHP, http://sourceforge.net/projects/editthispagephp/ Paylancers blog, http://paylancers.blogspot.com/ The Power of Many, http://thepowerofmany.com Regulating Prominence: A Design Pattern for Co-Located Collaboration (http://www.ida.liu.se/~matar/coop04arvola-web.pdf) “The Rise of Crowdsourcing,” by Jeff Howe, Wired 14.06, http://www.wired.com/wired/archive/14.06/crowds.html “The Simplest Thing That Could Possibly Work,” by Bill Venners, http://www.artima.com/intv/simplest.html Universal Edit Button, http://universaleditbutton.org/Universal_Edit_Button Wiki Design Principles, http://c2.com/cgi/wiki?

Related patterns “Learn from Games” on page 36 “Ongoing Sharing” on page 239 Chapter 17 As seen on WikiWikiWeb (http://c2.com/cgi/wiki) Crowdsourcing What Some jobs are too big for the immediate group of engaged collaborators to manage on its own. The community will benefit if the interface provides a way to break a large project into smaller pieces and engage and give incentives to a wider group of people (or “crowd”) to tackle those smaller pieces (Figure 12-15). Download at WoweBook.Com 326 Chapter 12: Barnraising Figure 12-15. Amazon’s Mechanical Turk plays matchmaker to people looking for distributed help in solving problems or answering questions, and other people willing to do said work for a fee. Use when Use this pattern when you wish to enable your active core community members to engage with the wider set of people participating in your social environment and get their help accomplishing ambitious projects that would not be possible with fewer people.

Use when Use this pattern when you wish to enable your active core community members to engage with the wider set of people participating in your social environment and get their help accomplishing ambitious projects that would not be possible with fewer people. How • Provide a method for splitting up a project into individual tasks so that each task may be advertised individually. Also, provide a venue for announcing crowdsourced projects. • Give community members a way to “shop for,” review, and claim individual tasks for the project (Figures 12-16, 12-17, and 12-18). Download at WoweBook.Com Collaboration 327 Figure 12-16. At Amazon’s Mechanical Turk, one can easily sign up and start reviewing human intelligence tasks (HITs) before deciding whether to do any of the work for the offered pay. Figure 12-17. When designing a t-shirt for Threadless, you can volunteer to have others critique your design for you, and then iterate the design based on the feedback. Download at WoweBook.Com 328 Chapter 12: Barnraising Figure 12-18. Anyone can sign up to start reviewing existing designs at Threadless


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The Corruption of Capitalism: Why Rentiers Thrive and Work Does Not Pay by Guy Standing

3D printing, Airbnb, Albert Einstein, Amazon Mechanical Turk, Asian financial crisis, asset-backed security, bank run, banking crisis, basic income, Ben Bernanke: helicopter money, Bernie Sanders, Big bang: deregulation of the City of London, bilateral investment treaty, Bonfire of the Vanities, Boris Johnson, Bretton Woods, business cycle, Capital in the Twenty-First Century by Thomas Piketty, carried interest, cashless society, central bank independence, centre right, Clayton Christensen, collapse of Lehman Brothers, collective bargaining, credit crunch, crony capitalism, crowdsourcing, debt deflation, declining real wages, deindustrialization, disruptive innovation, Doha Development Round, Donald Trump, Double Irish / Dutch Sandwich, ending welfare as we know it, eurozone crisis, falling living standards, financial deregulation, financial innovation, Firefox, first-past-the-post, future of work, gig economy, Goldman Sachs: Vampire Squid, Growth in a Time of Debt, housing crisis, income inequality, information retrieval, intangible asset, invention of the steam engine, investor state dispute settlement, James Watt: steam engine, job automation, John Maynard Keynes: technological unemployment, labour market flexibility, light touch regulation, Long Term Capital Management, lump of labour, Lyft, manufacturing employment, Mark Zuckerberg, market clearing, Martin Wolf, means of production, mini-job, Mont Pelerin Society, moral hazard, mortgage debt, mortgage tax deduction, Neil Kinnock, non-tariff barriers, North Sea oil, Northern Rock, nudge unit, Occupy movement, offshore financial centre, oil shale / tar sands, open economy, openstreetmap, patent troll, payday loans, peer-to-peer lending, plutocrats, Plutocrats, Ponzi scheme, precariat, quantitative easing, remote working, rent control, rent-seeking, ride hailing / ride sharing, Right to Buy, Robert Gordon, Ronald Coase, Ronald Reagan, Sam Altman, savings glut, Second Machine Age, secular stagnation, sharing economy, Silicon Valley, Silicon Valley startup, Simon Kuznets, sovereign wealth fund, Stephen Hawking, Steve Ballmer, structural adjustment programs, TaskRabbit, The Chicago School, The Future of Employment, the payments system, The Rise and Fall of American Growth, Thomas Malthus, Thorstein Veblen, too big to fail, Travis Kalanick, Uber and Lyft, Uber for X, uber lyft, Y Combinator, zero-sum game, Zipcar

Many in the precariat are over-qualified for the jobs they must accept; they also have a high ratio of unpaid ‘work’ to labour – looking and applying for jobs, training and retraining, queuing and form-filling, networking or just waiting around. They also rely mainly on money wages, which are often inadequate, volatile and unpredictable.38 They lack access to rights-based state benefits and are losing civil, cultural, social, economic and political rights, making them supplicants if they need help to survive. The precariat is growing all over the world, accelerated by the likes of Uber, TaskRabbit and Amazon Mechanical Turk discussed in Chapter 6. It is in turmoil, reflected in the confusion over perceived class membership. For instance, more Americans today see themselves as in the lower classes. In 2000, according to Gallup polls, 63 per cent saw themselves as middle-class and 33 per cent as lower-class. In 2015, 51 per cent saw themselves as middle-class and 48 per cent as lower-class. Similar trends have been reported elsewhere.

Rather, they are labour brokers, often taking 20 per cent (sometimes more) from all transactions. ‘Crowdwork’ platforms also act as labour brokers, providing a digital labour exchange through which organisations (‘requesters’) post online tasks, split into small, sometimes micro tasks, which workers (‘taskers’) then bid for. The platforms charge 10 per cent or more per transaction. The pioneer in micro-tasking was Amazon Mechanical Turk (AMT), set up by Amazon in 2005, but there are now dozens of crowdwork platforms, among the biggest being Upwork, PeoplePerHour and CrowdFlower. Clickworker, based in Germany, boasts 700,000 ‘clickworkers’ in 136 countries and big-name clients such as Honda and PayPal. Lancers, a Japanese platform, had 420,000 registered workers in 2015 and the Japanese crowd-labour industry body aims to increase the number of crowdworkers to 10 million by 2018 and 20 million by 2023.6 The platforms have grown astonishingly rapidly.

Standing, Basic Income: A Transformative Policy for India (London and New Delhi: Bloomsbury, 2015). 23 Atkinson, 2015, op. cit., p. 219. * ‘The invisible precariat – We are breaking the silence’. INDEX A Mechanical Age 1 Abbott, Arnold 1 AET (Academy Enterprise Trust) 1 agnotology 1 Airbnb 1, 2, 3, 4, 5, 6, 7 Alaska Permanent Fund 1 Allergan 1 allotments 1 Alperovitz, Gar 1 Altman, Sam 1 Amazon 1, 2, 3, 4 American Medical Association 1, 2 Amey 1 AMT (Amazon Mechanical Turk) 1, 2 Apple 1, 2, 3, 4, 5, 6, 7, 8 Arab Spring 1, 2 ASBOs (Anti-Social Behaviour Orders) 1 ASMS (Association of Salaried Medical Specialists) 1 Astor, Lord 1 Atkinson, Tony 1, 2, 3 Atlas Network 1 Auboin, Roger 1 austerity 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 automation 1, 2 Axelrod, David 1 Bahramipour, Bob 1 ‘bailouts’ 1, 2 Baker, Howard 1 Baker, Philip 1 Ballmer, Steve 1 Banco Espírito Santo 1 Bank of America 1, 2 Bank of England 1, 2, 3, 4, 5, 6, 7, 8, 9 Bank of Japan 1 banking systems and austerity 1 ‘bailouts’ 1, 2 and British Disease 1 and debt 1, 2, 3, 4, 5 and democracy 1, 2, 3, 4, 5, 6, 7 and ‘helicopter money’ 1 independence of central banks 1, 2 quantitative easing 1, 2, 3, 4, 5, 6 and rise of rentiers 1 trade and investment treaties 1 Barclay, David 1 Barclay, Frederick 1 basic income systems 1 Bayh–Dole Act (1980) 1 BBC (British Broadcasting Corporation) 1, 2 Benyon, Richard 1 BEPS (base erosion and profit shifting) 1 Bernanke, Ben 1 Berne Convention for the Protection of Literary and Artistic Works (1886) 1, 2 Berners-Lee, Tim 1, 2 Bernstein, Michael 1 Beveridge, William 1 BIEN (Basic Income European (later ‘Earth’) Network) 1 Bieńkowska, Elżbieta 1 Biewald, Lukas 1 Big Bang (1986) 1 Bilderberg Group 1 Billionaires Report (2015) 1 BIS (Bank for International Settlements) 1 BITs (bilateral investment treaties) 1 BlaBlaCar 1 BlackRock 1 Blair, Cherie 1 Blair, Tony 1, 2, 3, 4, 5, 6, 7 BNP Paribas 1 Born This Way foundation 1 Boston Tea Party 1 Bourdieu, Pierre 1 branding 1 Bretton Woods system 1, 2, 3 ‘Brexit’ debate/campaign 1, 2 Bridgepoint Capital 1, 2 British Disease 1, 2 British Rail 1 Broadbent, Ben 1 Brown, Gordon 1, 2, 3, 4 Brzezinski, Zbigniew 1 Buffett, Warren 1, 2 ‘build-to-rent’ projects 1 Burke, Edmund 1 Burns, Arthur 1 bus services 1 Bush, George H.


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

23andMe, 4chan, A Declaration of the Independence of Cyberspace, Airbnb, airport security, Amazon Mechanical Turk, augmented reality, basic income, Brian Krebs, California gold rush, call centre, cloud computing, cognitive dissonance, commoditize, correlation does not imply causation, Credit Default Swap, crowdsourcing, don't be evil, drone strike, 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, lifelogging, Lyft, Mark Zuckerberg, Mars Rover, Marshall McLuhan, mass incarceration, meta analysis, meta-analysis, Minecraft, move fast and break things, 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 intelligence, social web, sorting algorithm, Steve Ballmer, Steve Jobs, Steven Levy, TaskRabbit, technoutopianism, telemarketer, transportation-network company, Travis Kalanick, Turing test, Uber and Lyft, Uber for X, uber lyft, universal basic income, unpaid internship, women in the workforce, Y Combinator, Zipcar

Oct. 31, 2013. experianplc.com/investor-centre.aspx. 216 “detail about behaviors and proclivities”: Woodrow Hartzog and Evan Selinger. “Big Data in Small Hands.” 66 Stanford Law Review Online 81. Sept. 3, 2013. stanfordlawreview.org/online/privacy-and-big-data/big-data-small-hands. 219 Nandini Balial background and Rabbit experience: Author interviews with Nandini Balial. July and August 2014. 226 Mechanical Turk earnings: Jeremy Wilson. “My Grueling Day as an Amazon Mechanical Turk.” Kernel. Aug. 28, 2013. kernelmag.com/features/report/4732/my-gruelling-day-as-an-amazon-mechanical-turk. 228 “a cloud-computing cross”: Quentin Hardy. “Elance Pairs Hunt for Temp Work with Cloud Computing.” Bits, a blog on NYTimes.com. Sept. 24, 2013. bits.blogs.nytimes.com/2013/09/24/elance-pairs-hunt-for-temp-work-with-cloud-computing. 228 Mechanical Turk survey: Panos Ipeirotis. “Demographics of Mechanical Turk.” Stern School of Business.

Occasionally a job requires someone to go out into the physical world to confirm that a restaurant is still open or to photograph a store display so that the multinational company paying for it knows that it (and thousands of other displays like it, scattered around the country or the world) is set up properly. Usually, a would-be worker signs up, enters some information, and allows the site to connect to her social-media profiles in order to confirm her identity. Jobs then start to come down the pipe—some services allow workers to bid for jobs, with the lowest price usually winning out—and the worker goes off and performs the task for a few cents or a few dollars. Amazon’s Mechanical Turk, with its optimistically named “Human Intelligence Tasks,” offers some of the most menial work: copying receipts, drawing triangles, mimicking facial expressions, clicking on random URLs—all of it presented with as little contextual/explanatory information as possible. A Mechanical Turk worker might be kept busy, he might even be mildly entertained, but he would be lucky to earn minimum wage.

Twitter’s fleet of Mechanical Turk workers are accomplishing much the same sleight of hand, providing the illusion of seamless, automated competency, concealing the fact that company is relying on cheap, remote labor. As Ayhan Aytes describes it, “In both cases, the performance of the workers who animate the artifice is obscured by the spectacle of the machine.” Amazon calls this “artificial artificial intelligence.” In an added dose of perverse irony, Twitter’s Mechanical Turk workers are, in all likelihood, helping to train the machine-learning algorithms that Twitter hopes will eventually replace them. As with a number of other menial tasks common to the micro-work field, the human is there to complete the smallest unit of work that can’t be done by a computer. But the data gleaned from these human workers will be used to inform the future generation of automated systems that will replace human workers or shunt them to even smaller bits of work.


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Doing Data Science: Straight Talk From the Frontline by Cathy O'Neil, Rachel Schutt

Amazon Mechanical Turk, augmented reality, Augustin-Louis Cauchy, barriers to entry, Bayesian statistics, bioinformatics, computer vision, correlation does not imply causation, crowdsourcing, distributed generation, Edward Snowden, Emanuel Derman, fault tolerance, Filter Bubble, finite state, Firefox, game design, Google Glasses, index card, information retrieval, iterative process, John Harrison: Longitude, Khan Academy, Kickstarter, Mars Rover, Nate Silver, natural language processing, Netflix Prize, p-value, pattern recognition, performance metric, personalized medicine, pull request, recommendation engine, rent-seeking, selection bias, Silicon Valley, speech recognition, statistical model, stochastic process, text mining, the scientific method, The Wisdom of Crowds, Watson beat the top human players on Jeopardy!, X Prize

It is only under certain conditions (independence of the individuals rather than group-think where a group of people talking to each other can influence each other into wildly incorrect solutions), where groups of people can arrive at the correct solution. And only certain problems are well-suited to this approach. Amazon Mechanical Turk is an online crowdsourcing service where humans are given tasks. For example, there might be a set of images that need to be labeled as “happy” or “sad.” These labels could then be used as the basis of a training set for a supervised learning problem. An algorithm could then be trained on these human-labeled images to automatically label new images. So the central idea of Mechanical Turk is to have humans do fairly routine tasks to help machines, with the goal of the machines then automating tasks to help the humans! Any researcher with a task they need automated can use Amazon Mechanical Turk as long as they provide compensation for the humans. And any human can sign up and be part of the crowdsourcing service, although there are some quality control issues—if the researcher realizes the human is just labeling every other image as “happy” and not actually looking at the images, then the human won’t be used anymore for labeling.

linear regression, Linear Regression–Exercise machine learning, Machine Learning Algorithms, Other Examples of MapReduce models vs., Linear Regression Allstate, Their Customers alternating k-stars, A Second Example of Random Graphs: The Exponential Random Graph Model alternating least squares, Alternating Least Squares Amazon, Why Now?, Amazon Case Study: Big Spenders recommendation engines and, Recommendation Engines: Building a User-Facing Data Product at Scale Amazon Mechanical Turk, Background: Crowdsourcing ambient analytics, Data Visualization at Square Amstat News, The Current Landscape (with a Little History) analytical applications Hadoop, So How to Get Started with Hadoop? MapReduce, So How to Get Started with Hadoop? Anderson, Chris, Modeling Apache Hive, Cloudera Apache Software Foundation, Cloudera APIs, warnings about, Scraping the Web: APIs and Other Tools area under the cumulative lift curve, Evaluation area under the curve (AUC), How to Be a Good Modeler goodness of, Research Experiment (Observational Medical Outcomes Partnership) Artificial Artificial Intelligence, Background: Crowdsourcing Artificial Intelligence (AI), Machine Learning Algorithms ASA, The Current Landscape (with a Little History) association algorithms, Being an Ethical Data Scientist associations, Linear Regression assumptions, Populations and Samples of Big Data explicit, Machine Learning Algorithms attributes, predicting, Beyond Nearest Neighbor: Machine Learning Classification autocorrelation, A Baby Model–A Baby Model automated statistician thought experiment, Thought Experiment: Automated Statistician averages, The Gold Standard: Randomized Clinical Trials Avro, Back to Josh: Workflow B backward elimination, Selecting an algorithm bagging, Random Forests base, The Dimensionality Problem base rates, The Underlying Math Basic Machine Learning Algorithm Exercise, Exercise: Basic Machine Learning Algorithms–Sample R code: K-NN on the housing dataset Bayesian Information Criterion (BIC), Selection criterion, Beyond Nearest Neighbor: Machine Learning Classification Beautiful Soup, Scraping the Web: APIs and Other Tools Before Us is the Salesman’s House (Thorp/Hansen), eBay Transactions and Books–eBay Transactions and Books Bell Labs, Exploratory Data Analysis Bernoulli model, Jake’s Exercise: Naive Bayes for Article Classification Bernoulli network, A First Example of Random Graphs: The Erdos-Renyi Model betweenness, Centrality Measures bias-variance, Random Forests biases, Populations and Samples, Populations and Samples of Big Data Big Data, Big Data and Data Science Hype, Why Now?


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Machine, Platform, Crowd: Harnessing Our Digital Future by Andrew McAfee, Erik Brynjolfsson

"Robert Solow", 3D printing, additive manufacturing, AI winter, Airbnb, airline deregulation, airport security, Albert Einstein, Amazon Mechanical Turk, Amazon Web Services, artificial general intelligence, augmented reality, autonomous vehicles, backtesting, barriers to entry, bitcoin, blockchain, British Empire, business cycle, business process, carbon footprint, Cass Sunstein, centralized clearinghouse, Chris Urmson, cloud computing, cognitive bias, commoditize, complexity theory, computer age, creative destruction, crony capitalism, crowdsourcing, cryptocurrency, Daniel Kahneman / Amos Tversky, Dean Kamen, discovery of DNA, disintermediation, disruptive innovation, distributed ledger, double helix, Elon Musk, en.wikipedia.org, Erik Brynjolfsson, Ethereum, ethereum blockchain, everywhere but in the productivity statistics, family office, fiat currency, financial innovation, George Akerlof, global supply chain, Hernando de Soto, hive mind, information asymmetry, Internet of things, inventory management, iterative process, Jean Tirole, Jeff Bezos, jimmy wales, John Markoff, joint-stock company, Joseph Schumpeter, Kickstarter, law of one price, longitudinal study, Lyft, Machine translation of "The spirit is willing, but the flesh is weak." to Russian and back, Marc Andreessen, Mark Zuckerberg, meta analysis, meta-analysis, Mitch Kapor, moral hazard, multi-sided market, Myron Scholes, natural language processing, Network effects, new economy, Norbert Wiener, Oculus Rift, PageRank, pattern recognition, peer-to-peer lending, performance metric, plutocrats, Plutocrats, precision agriculture, prediction markets, pre–internet, price stability, principal–agent problem, Ray Kurzweil, Renaissance Technologies, Richard Stallman, ride hailing / ride sharing, risk tolerance, Ronald Coase, Satoshi Nakamoto, Second Machine Age, self-driving car, sharing economy, Silicon Valley, Skype, slashdot, smart contracts, Snapchat, speech recognition, statistical model, Steve Ballmer, Steve Jobs, Steven Pinker, supply-chain management, TaskRabbit, Ted Nelson, The Market for Lemons, The Nature of the Firm, Thomas Davenport, Thomas L Friedman, too big to fail, transaction costs, transportation-network company, traveling salesman, Travis Kalanick, two-sided market, Uber and Lyft, Uber for X, uber lyft, ubercab, Watson beat the top human players on Jeopardy!, winner-take-all economy, yield management, zero day

Lakhani, “Marginality and Problem-Solving Effectiveness in Broadcast Search,” Organization Science, February 22, 2010, http://pubsonline.informs.org/doi/abs/10.1287/orsc.1090.0491. 260 Amazon’s Mechanical Turk: Jason Pontin, “Artificial Intelligence, with Help from the Humans,” New York Times, March 25, 2007, http://www.nytimes.com/2007/03/25/business/yourmoney/25Stream.html. 260 transcribing text from business cards into a spreadsheet: Jeremy Wilson, “My Gruelling Day as an Amazon Mechanical Turk,” Kernel, August 28, 2013, http://kernelmag.dailydot.com/features/report/4732/my-gruelling-day-as-an-amazon-mechanical-turk. 260 “programming design pattern”: Michael Bernstein et al., “Soylent: A Word Processor with a Crowd Inside,” 2010, http://courses.cse.tamu.edu/caverlee/csce438/readings/soylent.pdf. 260 people who identify as designers: Topcoder, “Topcoder Is Different,” accessed February 8, 2017, https://www.topcoder.com/member-onboarding/topcoder-is-different. 261 Kaggle: Kaggle, accessed March 10, 2017, https://www.kaggle.com. 261 officiating at a wedding: JamieV2014, “Task of the Week: Perform My Marriage,” TaskRabbit (blog), March 26, 2014, https://blog.taskrabbit.com/2014/03/26/task-of-the-week-perform-my-marriage. 261 delivering ice cream cake: LauraTaskRabbit, “Task of the Week: Deliver Ice Cream Cake to My Grandpa,” TaskRabbit (blog), November 18, 2014, https://blog.taskrabbit.com/2014/11/18/task-of-the-week-deliver-ice-cream-cake-to-my-grandpa. 261 waiting in line at the Apple Store: JamieV2014, “We’re First in Line at the Apple Store,” TaskRabbit (blog), September 17, 2012, https://blog.taskrabbit.com/2012/09/17/were-first-in-line-at-the-apple-store. 261 The TV show Veronica Mars: IMDb, s. v.

This work is still in its early stages, but we’ve already seen many intriguing ways for the core and the crowd to come together. Getting work done. As we’ve seen with Wikipedia and Linux, the crowd can come together to build things of great value, especially if a set of principles like openness and noncredentialism is followed. Some organizations are putting these principles into practice in order to offer what might be called crowd construction as a service to companies. One of the earliest examples was Amazon’s Mechanical Turk, which started as an internal effort to find and eliminate duplicate product pages and was released for outside use in November 2005. Today, the crowd of “Turkers” is used for a wide variety of tasks, such as transcribing text from business cards into a spreadsheet, answering surveys for psychology research, and labeling images for input into AI programs. Refinements to the basic Mechanical Turk platform include find-fix-verify, a “programming design pattern” developed by MIT’s Michael Bernstein and colleagues that lets Turkers self-select into either doing a task or spotting and fixing errors.

., 222–23 lack of assets owned by, 6–7 limits to effects on hotel industry, 221–23 network effects, 193 as O2O platform, 186 peer reviews, 209–10 rapid growth of, 9 as two-sided network, 214 value proposition compared to Uber, 222 Airline Deregulation Act, 181n airlines, revenue management by, 181–82 air travel, virtualization in, 89 Akerlof, George, 207, 210 albums, recorded music, 145 algorithms; See also data-driven decision making bias in systems, 51–53 and Cambrian Explosion of robotics, 95–96 comparing human decisions to, 56 O2O platforms and, 193 Quantopian and, 267–70 superiority to System 1 reasoning, 38–41 “algo traders,” 268; See also automated investing Alibaba, 6–8 Alipay, 174 AlphaGo, 4–6, 14, 74, 80 Alter, Lloyd, 90 Amazon automatic price changes, 47 bar code reader app, 162 data-driven product recommendations, 47 development of Web Services, 142–43 Mechanical Turk, 260 as stack, 295 warehouse robotics, 103 Amazon EC2, 143 Amazon Go, 90–91 Amazon S3, 143 Amazon Web Services (AWS), 75, 142–43 American Airlines (AA), 182 amino acid creation, 271–72 analog copies, digital copies vs., 136 “Anatomy of a Large-Scale Hypertextual Web Search Engine, The” (Page and Brin), 233 Anderson, Chris, 98–100 Anderson, Tim, 94 Andreessen, Marc on crowdfunding, 262–63 and Netscape, 34 as self-described “solutionist,” 297 on Teespring, 263–64 Android Blackberry vs., 168 contribution to Google revenue/profits, 204 iOS vs., 166–67 Angry Birds, 159–61 anonymity, digital currency and, 279–80 Antikythera mechanism, 66 APIs (application programming interfaces), 79 apophenia, 44n apparel, 186–88 Apple; See also iPhone acquiring innovation by acquiring companies, 265 and industrywide smartphone profits, 204 leveraging of platforms by, 331 Postmates and, 173, 185 profitability (2015), 204 revenue from paid apps, 164 “Rip, Mix, Burn” slogan, 144n as stack, 295 application programming interfaces (APIs), 79 AppNexus, 139 apps; See also platforms for banking, 89–90 demand curve and, 157–61 iPhone, 151–53 App Store, 158 Apter, Zach, 183 Aral, Sinan, 33 Archilochus, 60–61 architecture, computer-designed, 118 Aristophanes, 200 Arnaout, Ramy, 253 Arthur, Brian, 47–48 artificial general intelligence (AGI), 71 artificial hands, 272–75 artificial intelligence; See also machine learning current state of, 74–76 defined, 67 early attempts, 67–74 implications for future, 329–30 rule-based, 69–72 statistical pattern recognition and, 72–74 Art of Thinking Clearly, The (Dobelli), 43 arts, digital creativity in, 117–18 Ashenfelter, Orley, 38–39 ASICs (application-specific integrated circuits), 287 assets and incentives, 316 leveraging with O2O platforms, 196–97 replacement by platforms, 6–10 asymmetries of information, 206–10 asymptoting, 96 Atkeson, Andrew, 21 ATMs, 89 AT&T, 96, 130 August (smart door lock), 163 Austin, Texas, 223 Australia, 100 Authorize.Net, 171 Autodesk, 114–16, 119, 120 automated investing, 266–70 automation, effect on employment/wages, 332–33 automobiles, See cars Autor, David, 72, 101 background checks, 208, 209 back-office work, 82–83 BackRub, 233 Baidu, 192 Bakos, Yannis, 147n Bakunin, Mikhail, 278 Ballmer, Steve, 151–52 bandwagon effect, 217 banking, virtualization and, 89–90, 92 Bank of England, 280n bank tellers, 92 Barksdale, Jim, 145–46 barriers to entry, 96, 220 Bass, Carl, 106–7, 119–20 B2B (business-to-business) services, 188–90 Beastmode 2.0 Royale Chukkah, 290 Behance, 261 behavioral economics, 35, 43 Bell, Kristen, 261, 262 Benioff, Mark, 84–85 Benjamin, Robert, 311 Benson, Buster, 43–44 Berlin, Isiah, 60n Berners-Lee, Tim, 33, 34n, 138, 233 Bernstein, Michael, 260 Bertsimas, Dimitris, 39 Bezos, Jeff, 132, 142 bias of Airbnb hosts, 209–10 in algorithmic systems, 51–53 digital design’s freedom from, 116 management’s need to acknowledge, 323–24 and second-machine-age companies, 325 big data and Cambrian Explosion of robotics, 95 and credit scores, 46 and machine learning, 75–76 biology, computational, 116–17 Bird, Andrew, 121 Bitcoin, 279–88 China’s dominance of mining, 306–7 failure mode of, 317 fluctuation of value, 288 ledger for, 280–87 as model for larger economy, 296–97 recent troubles with, 305–7 and solutionism, 297 “Bitcoin: A Peer-to-Peer Electronic Cash System” (Nakamoto), 279 BlaBlaCar, 190–91, 197, 208 BlackBerry, 168, 203 Blitstein, Ryan, 117 blockchain as challenge to stacks, 298 and contracts, 291–95 development and deployment, 283–87 failure of, 317 and solutionism, 297 value as ledger beyond Bitcoin, 288–91 Blockchain Revolution (Tapscott and Tapscott), 298 Bloomberg Markets, 267 BMO Capital Markets, 204n Bobadilla-Suarez, Sebastian, 58n–59n Bock, Laszlo, 56–58 bonds, 131, 134 bonuses, credit card, 216 Bordeaux wines, 38–39 Boudreau, Kevin, 252–54 Bowie, David, 131, 134, 148 Bowie bonds, 131, 134 brand building, 210–11 Brat, Ilan, 12 Bredeche, Jean, 267 Brin, Sergey, 233 Broward County, Florida, 40 Brown, Joshua, 81–82 Brusson, Nicolas, 190 Burr, Donald, 177 Bush, Vannevar, 33 business conference venues, 189 Business Insider, 179 business processes, robotics and, 88–89 business process reengineering, 32–35 business travelers, lodging needs of, 222–23 Busque, Leah, 265 Buterin, Vitalik, 304–5 Byrne, Patrick, 290 Cairncross, Francis, 137 California, 208; See also specific cities Calo, Ryan, 52 Cambrian Explosion, 94–98 Cameron, Oliver, 324 Camp, Garrett, 200 capacity, perishing inventory and, 181 Card, David, 40 Care.com, 261 cars automated race car design, 114–16 autonomous, 17, 81–82 decline in ownership of, 197 cash, Bitcoin as equivalent to, 279 Casio QV-10 digital camera, 131 Caves, Richard, 23 Caviar, 186 CDs (compact discs), 145 cell phones, 129–30, 134–35; See also iPhone; smartphones Census Bureau, US, 42 central bankers, 305 centrally planned economies, 235–37 Chabris, Chris, 3 Chambers, Ephraim, 246 Champy, James, 32, 34–35, 37, 59 Chandler, Alfred, 309n Chase, 162 Chase Paymentech, 171 check-deposit app, 162 children, language learning by, 67–69 China Alibaba in, 7–8 concentration of Bitcoin wealth in, 306–7 and failure mode of Bitcoin, 317 mobile O2O platforms, 191–92 online payment service problems, 172 robotics in restaurants, 93 Shanghai Tower design, 118 Xiaomi, 203 Chipotle, 185 Choudary, Sangeet, 148 Christensen, Clay, 22, 264 Churchill, Winston, 301 Civil Aeronautics Board, US, 181n Civis Analytics, 50–51 Clash of Clans, 218 classified advertising revenue, 130, 132, 139 ClassPass, 205, 210 and economics of perishing inventory, 180–81 future of, 319–20 and problems with Unlimited offerings, 178–80, 184 and revenue management, 181–84 user experience, 211 ClassPass Unlimited, 178–79 Clear Channel, 135 clinical prediction, 41 Clinton, Hillary, 51 clothing, 186–88 cloud computing AI research, 75 APIs and, 79 Cambrian Explosion of robotics, 96–97 platform business, 195–96 coaches, 122–23, 334 Coase, Ronald, 309–13 cognitive biases, 43–46; See also bias Cohen, Steven, 270 Coles, John, 273–74 Collison, John, 171 Collison, Patrick, 171–74 Colton, Simon, 117 Columbia Record Club, 131 commoditization, 220–21 common sense, 54–55, 71, 81 companies continued dominance of, 311–12 continued relevance of, 301–27 DAO as alternative to, 301–5 decreasing life spans of, 330 economics of, 309–12 future of, 319–26 leading past the standard partnership, 323–26 management’s importance in, 320–23 markets vs., 310–11 as response to inherent incompleteness of contracts, 314–17 solutionism’s alternatives to, 297–99 TCE and, 312–15 and technologies of disruption, 307–9 Compass Fund, 267 complements (complementary goods) defined, 156 effect on supply/demand curves, 157–60 free, perfect, instant, 160–63 as key to successful platforms, 169 and open platforms, 164 platforms and, 151–68 and revenue management, 183–84 Stripe and, 173 complexity theory, 237 Composite Fund (D.


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Data Science for Business: What You Need to Know About Data Mining and Data-Analytic Thinking by Foster Provost, Tom Fawcett

Albert Einstein, Amazon Mechanical Turk, big data - Walmart - Pop Tarts, bioinformatics, business process, call centre, chief data officer, Claude Shannon: information theory, computer vision, conceptual framework, correlation does not imply causation, crowdsourcing, data acquisition, David Brooks, en.wikipedia.org, Erik Brynjolfsson, Gini coefficient, information retrieval, intangible asset, iterative process, Johann Wolfgang von Goethe, Louis Pasteur, Menlo Park, Nate Silver, Netflix Prize, new economy, p-value, pattern recognition, placebo effect, price discrimination, recommendation engine, Ronald Coase, selection bias, Silicon Valley, Skype, speech recognition, Steve Jobs, supply-chain management, text mining, The Signal and the Noise by Nate Silver, Thomas Bayes, transaction costs, WikiLeaks

However, if this problem is important enough[85] then we should consider investing in labeled training data to see whether we can build a model to identify pages containing hate speech. Cloud labor changes the economics of investing in data in our example of getting labeled training data. We can engage very inexpensive labor via the Internet to invest in data in various ways. For example, we can have workers on Amazon Mechanical Turk label pages as objectionable or not, providing us with target labels, much more cheaply than hiring even student workers. The rate of completion, when done by a trained intern, was 250 websites per hour, at a cost of $15/hr. When posted on Amazon Mechanical Turk, the labeling rate went up to 2,500 websites per hour and the overall cost remained the same. (Ipeirotis et al., 2010) The problem is that you get what you pay for, and low cost sometimes means low quality. There has been a surge of research over the past half decade on the problems of maintaining quality while taking advantage of cloud labor.

Through the book we have discussed in increasing complexity the notion of investing in data. If we apply our general framework of considering the costs and benefits in data science projects explicitly, it leads us to new thinking about investing in data. Final Example: From Crowd-Sourcing to Cloud-Sourcing The connectivity between businesses and “consumers” brought about by the Internet has changed the economics of labor. Web-based systems like Amazon’s Mechanical Turk and oDesk (among others) facilitate a type of crowd-sourcing that might be called “cloud labor”—harnessing via the Internet a vast pool of independent contractors. One sort of cloud labor that is particularly relevant to data science is “micro-outsourcing”: the outsourcing of large numbers of very small, well-defined tasks. Micro-outsourcing is particularly relevant to data science, because it changes the economics, as well as the practicalities, of investing in data.[84] As one example, recall the requirements for applying supervised modeling.

The merge/purge problem for large databases. SIGMOD Rec., 24, 127–138. Hill, S., Provost, F., & Volinsky, C. (2006). Network-based marketing: Identifying likely adopters via consumer networks. Statistical Science, 21 (2), 256–276. Holte, R. C. (1993). Very simple classification rules perform well on most commonly used datasets. Machine Learning, 11, 63–91. Ipeirotis, P., Provost, F., & Wang, J. (2010). Quality management on Amazon Mechanical Turk. In Proceedings of the 2010 ACM SIGKDD Workshop on Human Computation, pp. 64-67. ACM. Jackson, M. (1989). Michael Jackson’s Malt Whisky Companion: a Connoisseur’s Guide to the Malt Whiskies of Scotland. Dorling Kindersley, London. Japkowicz, N., & Stephen, S. (2002). The class imbalance problem: A systematic study. Intelligent Data Analysis, 6 (5), 429–450. Japkowicz, N., & Shah, M. (2011).


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Thinking Machines: The Inside Story of Artificial Intelligence and Our Race to Build the Future by Luke Dormehl

Ada Lovelace, agricultural Revolution, AI winter, Albert Einstein, Alexey Pajitnov wrote Tetris, algorithmic trading, Amazon Mechanical Turk, Apple II, artificial general intelligence, Automated Insights, autonomous vehicles, book scanning, borderless world, call centre, cellular automata, Claude Shannon: information theory, cloud computing, computer vision, correlation does not imply causation, crowdsourcing, drone strike, Elon Musk, Flash crash, friendly AI, game design, global village, Google X / Alphabet X, hive mind, industrial robot, information retrieval, Internet of things, iterative process, Jaron Lanier, John Markoff, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, John von Neumann, Kickstarter, Kodak vs Instagram, Law of Accelerating Returns, life extension, Loebner Prize, Marc Andreessen, Mark Zuckerberg, Menlo Park, natural language processing, Norbert Wiener, out of africa, PageRank, pattern recognition, Ray Kurzweil, recommendation engine, remote working, RFID, self-driving car, Silicon Valley, Skype, smart cities, Smart Cities: Big Data, Civic Hackers, and the Quest for a New Utopia, social intelligence, speech recognition, Stephen Hawking, Steve Jobs, Steve Wozniak, Steven Pinker, strong AI, superintelligent machines, technological singularity, The Coming Technological Singularity, The Future of Employment, Tim Cook: Apple, too big to fail, Turing machine, Turing test, Vernor Vinge, Watson beat the top human players on Jeopardy!

., ‘Actual Causes of Death in the United States, 2000’, American Medical Association, 2004: csdp.org/research/1238.pdf 17 http://arstechnica.com/gaming/2015/07/pewdiepie-responds-to-haters-over-his-4–5-million-youtube-earnings/ 18 http://uk.ign.com/articles/2013/10/09/gta-5-currently-holds-seven-guinness-world-records 19 Gaudiosi, John, ‘New Reports Forecast Global Video Games Industry Will Reach $82 Billion by 2017’, Forbes, 18 July 2012: http://www.forbes.com/sites/johngaudiosi/2012/07/18/new-reports-forecasts-global-video-game-industry-will-reach-82-billion-by-2017/ 20 http://www.pwc.co.uk/en_uk/uk/assets/pdf/ukeo-regional-march-2015.pdf 21 ‘Artificial Artificial Intelligence’, The Economist, 8 June 2006: economist.com/node/7001738?story_id=7001738 22 Chen, Edwin, ‘Improving Twitter Search with Real-Time Human Computation’, 8 January 2013: blog.echen.me/2013/01/08/improving-twitter-search-with-real-time-human-computation/ 23 forums.aws.amazon.com/thread.jspa?threadID=58891 24 Cushing, Ellen, ‘Amazon Mechanical Turk: The Digital Sweatshop’, East Bay Express, Jan/Feb 2013: utne.com/science-and-technology/amazon-mechanical-turk-zm0z13jfzlin.aspx 25 Conley, Neil and Braegelmann, Tom, ‘Decision of the German Federal Supreme Court no. I ZR 112/06’, Journal of the Copyright Society, Vol. 56, 2009: http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1504982 26 Lanier, Jaron, Who Owns the Future? (New York: Simon & Schuster, 2013). 27 Love, Julia, ‘Apple Ups Its AI Experts Hiring, But Faces Obstacles … ’, Reuters, 7 September 2015: venturebeat.com/2015/09/07/apple-ups-its-a-i-hiring-but-faces-obstacles-to-making-phones-smarter/ 28 Dredge, Stuart, ‘Apple Music Interview’, Guardian, 9 June 2015: theguardian.com/technology/2015/jun/09/apple-music-interview-jimmy-iovine-eddy-cue 29 Dormehl, Luke, ‘New Apple Patents Hint at a Headphone, Music Revolution’, Cult of Mac, 29 May 2014: cultofmac.com/281353/apple-focus-reinventing-headphones/ 30 Moss, Caroline, ‘Meet the Guy Who Makes $1,000 an Hour Tutoring Kids of Fortune 500 CEOs Over Skype’, Business Insider, 26 August 2014: businessinsider.com/anthony-green-tutoring-2014–8?


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Curation Nation by Rosenbaum, Steven

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

The idea is to offer freelancers relatively low pay to create content but to let them choose the topics that interest them so that they can work on their own preferred subjects and on their own schedules. The need to access human skills on demand was what convinced the folks at Amazon to create a service known as Mechanical Turk. The name Mechanical Turk is based on a “robot” that dates back to 1769, when a nobleman astonished Europe by building a mechanical chess-playing automaton that was able to beat human opponents. The Turk toured Europe and overcame brilliant challengers such as Benjamin Franklin and Napoleon Bonaparte. The secret behind the Mechanical Turk was a human chess master cleverly concealed inside the cabinet. It was a trick. Today Amazon’s Mechanical Turk is founded on the premise that there are still many things that human beings can do that computers can’t. For example, Amazon needed to scrub through its entire collection of JPEG CD covers to make sure that the image of the Rolling Stones was the correct image on the site’s item page.

Happily, almost all of them agreed to be interviewed for this project. Many of those interviews were conducted in person, and rather than take notes, the conversations were recorded and then transcribed. The rest of the interviews were conducted via Skype, and those too were transcribed. In both cases the transcriptions were turned around almost magically by a team of online workers known as Turkers, who are members of an Amazon service called Mechanical Turk. I talk more about Mechanical Turk in chapter 6, so I won’t repeat the details here. Suffice it to say that the ability to have a Skype interview at 5 p.m. and have a transcript in your in box at 9 a.m. the next morning is for this author an awe-inspiring experience. The world moves quickly now. I didn’t want to weight things down in the text with footnotes and endnotes and such; in many cases when I quote people, their words are coming directly from interviews I conducted with them.

dailyfinance.com, April 13, 2010. http://www.dailyfinance.com/story/who-knows-you-better-your-credit-card-company-or-your-spouse/19436105 Conclusion http://www.comscore.com INDEX About.com Abrams, Dan Abrams, Floyd Abu Dhabi Media Accidental curation Acheson, Lila Bell Addis, Steve Addis/Creson AdSense Advertising AdSense fees affiliated marketing changes in consumer conversations and on curated networks micronets and nature of commerce and sponsorships trends in (See also Brands and branding) Advertising Age Adweek Affiliated marketing Affiliate Summit Aggregation balance of power and criticism of curation versus Flipboard multimedia reaggregation video aggregators All Things Digital Alvey, Brian Amazon Mechanical Turk American Association of Museums Anderson, Chris AOL Armstrong, Tim Arora, Samir Arrington, Michael Artist Direct Associated Content Associated Press Atari AT&T AVC.Blogspot.com Avid editing equipment Axel Springer Baer, Jay Baltimore Museum of Art Bankoff, Jim Barnett, Rob BBC Beckland, Jamie Berra, Yogi Bhargava, Rohit Bicycling magazine Big Apple Circus Biondi, Frank Bionic journalism Bit.ly BitTorrent Blau, Andrew Blippy Blip.tv Blogger.com Blogging BlogHer Blogmaverick.com Bloomberg Company Blurry-edged privacy Boing Boing Bough, Bonin Boyle, Susan Brands and branding adaptation in changes in consumer conversations and content creation and content strategy and public relations in.


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

"Robert Solow", Amazon Mechanical Turk, Any sufficiently advanced technology is indistinguishable from magic, autonomous vehicles, business cycle, business process, call centre, combinatorial explosion, corporate governance, creative destruction, 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, intangible asset, job automation, John Markoff, John Maynard Keynes: technological unemployment, Joseph Schumpeter, Khan Academy, Kickstarter, knowledge worker, Loebner Prize, low skilled workers, minimum wage unemployment, patent troll, pattern recognition, Paul Samuelson, 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!, wealth creators, winner-take-all economy, zero-sum game

New platforms leverage technology to create marketplaces that address the employment crisis by bringing together machines and human skills in new and unexpected ways: eBay and Amazon Marketplace spurred over 600,000 people to earn their livings by dreaming up new, improved, or simply different or cheaper products for a worldwide customer base. The Long Tail of new products offered enormous consumer value and is a rapidly growing segment of the economy. Apple’s App Store and Google’s Android Marketplace make it easy for people with ideas for mobile applications to create and distribute them. Threadless lets people create and sell designs for t-shirts. Amazon’s Mechanical Turk makes it easy to find cheap labor to do a breathtaking array of simple, well-defined tasks. Kickstarter flips this model on its head and helps designers and creative artists find sponsors for their projects. Heartland Robotics provides cheap robots-in-a-box that make it possible for small business people to quickly set up their own highly automated factory, dramatically reducing the costs and increasing the flexibility of manufacturing.

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. This costs over $130 billion per year, which would do much more for growth if allocated to research or education.


pages: 375 words: 88,306

The Sharing Economy: The End of Employment and the Rise of Crowd-Based Capitalism by Arun Sundararajan

additive manufacturing, Airbnb, AltaVista, Amazon Mechanical Turk, autonomous vehicles, barriers to entry, basic income, bitcoin, blockchain, Burning Man, call centre, collaborative consumption, collaborative economy, collective bargaining, commoditize, corporate social responsibility, cryptocurrency, David Graeber, distributed ledger, employer provided health coverage, Erik Brynjolfsson, Ethereum, ethereum blockchain, Frank Levy and Richard Murnane: The New Division of Labor, future of work, George Akerlof, gig economy, housing crisis, Howard Rheingold, information asymmetry, Internet of things, inventory management, invisible hand, job automation, job-hopping, Kickstarter, knowledge worker, Kula ring, Lyft, Marc Andreessen, megacity, minimum wage unemployment, moral hazard, moral panic, Network effects, new economy, Oculus Rift, pattern recognition, peer-to-peer, peer-to-peer lending, peer-to-peer model, peer-to-peer rental, profit motive, purchasing power parity, race to the bottom, recommendation engine, regulatory arbitrage, rent control, Richard Florida, ride hailing / ride sharing, Robert Gordon, Ronald Coase, Ross Ulbricht, Second Machine Age, self-driving car, sharing economy, Silicon Valley, smart contracts, Snapchat, social software, supply-chain management, TaskRabbit, The Nature of the Firm, total factor productivity, transaction costs, transportation-network company, two-sided market, Uber and Lyft, Uber for X, uber lyft, universal basic income, Zipcar

Task Economies In the past, hiring thousands of workers to carry out small tasks wasn’t feasible because of the high administrative costs of such a structure. Today, smaller and smaller tasks can increasingly be outsourced with minimal transaction costs to crowds of workers connected to digital platforms. An early example of this form of “taskification” can be seen in the popular Amazon’s Mechanical Turk, which connects millions of workers around the world to customers who have broken down projects into simple tasks with compensation ranging from a few pennies to a couple of dollars. One might wonder if a platform like Amazon’s Mechanical Turk, which seems to be, like Spare5, largely used for simple tasks like image tagging and survey responses, can make a dent in how the vast majority of the economy’s productive work is done. For example, will we see complex consulting projects or sales activities being broken down and offered on these platforms for people to contribute to in their spare time?

An especially compelling example comes from a recent prototype, built by Devin Fidler of the Institute of the Future, called iCEO, “a virtual management system that automates complex work by dividing it into small, individual tasks.”24 Fidler’s system demonstrates how the complex work we typically associate with senior managers can be instead done by software that parcels tasks to workers on oDesk, Elance, and Amazon’s Mechanical Turk workers. For example, iCEO was given the project of creating a 124-page research report for a Fortune 50 client. As Fidler describes it: We spent a few hours plugging in the parameters of the project, i.e. structuring the flow of tasks, then hit play. For instance, to create an in-depth assessment of how graphene is produced, iCEO asked workers on Amazon’s Mechanical Turk to curate a list of articles on the topic. After duplicates were removed, the list of articles was passed on to a pool of technical analysts from oDesk, who extracted and arranged the articles’ key insights.


pages: 606 words: 157,120

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

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, creative destruction, 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, lifelogging, lone genius, Louis Pasteur, Mark Zuckerberg, market fundamentalism, Marshall McLuhan, moral panic, Narrative Science, Nelson Mandela, Nicholas Carr, packet switching, PageRank, Parag Khanna, Paul Graham, peer-to-peer, 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

Well, this exception is no more: BinCam, a new project from researchers in Britain and Germany, seeks to modernize how we deal with trash by making our bins smarter and—you guessed it—more social. Here is how it works: The bin’s inside lid is equipped with a tiny smartphone that snaps a photo every time someone closes it—all of this, of course, in order to document what exactly you have just thrown away. A team of badly paid humans, recruited through Amazon’s Mechanical Turk system, then evaluates each photo. What is the total number of items in the picture? How many of them are recyclable? How many are food items? After this data is attached to the photo, it’s uploaded to the bin owner’s Facebook account, where it can also be shared with other users. Once such smart bins are installed in multiple households, BinCam creators hope, Facebook can be used to turn recycling into a game-like exciting competition.

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)?

Thus, others have inquired if Britney is a “hot mess,” whether she is “dead” or “ugly,” and—my favorite—whether she is a “three-headed alien” (which, on further investigation, turns out to be the title of a book). Britney Spears is a public figure, and the controversy here seems moot at best. But suppose that an enemy of yours, in a deliberate effort to smear your reputation, starts paying users to search for your name followed by the word “pedophile.” An army of eager contributors, recruited through sites like Craigslist and Amazon’s Mechanical Turk, are now generating enough search volume to make this new query replace a few other, more positive terms associated with your name. Now, everyone who searches for your name is also informed that you might be a pedophile—and, remember, you have no way to appeal, for Google’s algorithms are in charge, and they never get things wrong. It’s hard to say if Bettina Wulff, Germany’s former first lady, has been the victim of a similar crowdsourced hit job, but in September 2012 she sued Google for “autocompleting” searches for her name with terms like “prostitute” and “escort.”


pages: 392 words: 108,745

Talk to Me: How Voice Computing Will Transform the Way We Live, Work, and Think by James Vlahos

Albert Einstein, AltaVista, Amazon Mechanical Turk, Amazon Web Services, augmented reality, Automated Insights, autonomous vehicles, Chuck Templeton: OpenTable:, cloud computing, computer age, Donald Trump, Elon Musk, information retrieval, Internet of things, Jacques de Vaucanson, Jeff Bezos, lateral thinking, Loebner Prize, Machine translation of "The spirit is willing, but the flesh is weak." to Russian and back, Mark Zuckerberg, Menlo Park, natural language processing, PageRank, pattern recognition, Ponzi scheme, randomized controlled trial, Ray Kurzweil, Ronald Reagan, Rubik’s Cube, self-driving car, sentiment analysis, Silicon Valley, Skype, Snapchat, speech recognition, statistical model, Steve Jobs, Steve Wozniak, Steven Levy, Turing test, Watson beat the top human players on Jeopardy!

But Serban and his teammates came up with an ingenious way to judge potential responses on a turn-by-turn level as well. This part of the system began with work that took place off-line from the contest socialbot. Serban and his teammates took several thousand sample user utterances and supplied four possible things that the socialbot could say in response to each one. MILA then had human workers, recruited online via Amazon Mechanical Turk, rank the quality of each potential response from one to five. How appropriate, interesting, and engaging was it? These ratings, in turn, were used to train a neural network in hopes that it would ultimately learn to emulate the humans in their ability to evaluate just what made for a good conversational response. So how did MILA fare with its machine-learning-heavy creation? As a research test bed, the system was a success.

See also Alexa; Alexa Prize competition advertising and, 233, 282–83 ASR and, 41–43, 97 at CES, xv, xvi eavesdropping and, 227–28, 230, 232, 233–34 Fire Phone, 44 founding of, 39 knowledge graphs and, 205 Lab126, 41, 42, 44, 140 partnerships with, 213 platform war and, 7–9, 278–85 SEO and, 209 shopping at, 209, 283–84 voice revolution and platform development, 7, 8–9, 13, 40–45 youth market and, 235 Amazon Echo. See also Alexa; Alexa Prize competition Evi and, 204, 213 Google Home release and, 54 privacy and surveillance and, 222–24, 238 release of, 8, 44–45, 50, 280 sales of, 282 voice search using, 209 Amazon Echo Dot, 226, 282 Amazon Echo Show, 58 Amazon Mechanical Turk, 151 ambient computing, 5 American Psychological Association, 249 Anagram Genius, 198–99 Android operating system and devices, 24, 203 Apple. See also iPhone; Siri ASR and, 98 eavesdropping and, 225, 227, 230, 231 knowledge graphs and, 205 mobile computing and, 3 smart home devices and, 50, 213, 218, 280 virtual assistant development, 16–18, 27, 118 voice revolution and platform development, 7, 8–9, 40, 280–81 Aquinas, Thomas, 65 Aristo, 162–63 Arkin, Ronald, 240 Arkush, Anne, 268 ARPANET, 78 artificial intelligence (AI).


Blueprint: The Evolutionary Origins of a Good Society by Nicholas A. Christakis

agricultural Revolution, Alfred Russel Wallace, Amazon Mechanical Turk, assortative mating, Cass Sunstein, crowdsourcing, David Attenborough, different worldview, disruptive innovation, double helix, epigenetics, experimental economics, experimental subject, invention of agriculture, invention of gunpowder, invention of writing, iterative process, job satisfaction, Joi Ito, joint-stock company, land tenure, Laplace demon, longitudinal study, Mahatma Gandhi, Marc Andreessen, means of production, mental accounting, meta analysis, meta-analysis, microbiome, out of africa, phenotype, Pierre-Simon Laplace, placebo effect, race to the bottom, Ralph Waldo Emerson, replication crisis, Rubik’s Cube, Silicon Valley, social intelligence, social web, stem cell, Steven Pinker, the scientific method, theory of mind, twin studies, ultimatum game, zero-sum game

Having solved its own problem, Amazon started allowing other employers, for a fee, to use the platform to hire workers, turning its invention into a profit center. The service was named Amazon Mechanical Turk, after a chess-playing machine first shown at the Austrian imperial court in the eighteenth century. That machine featured a mechanical man made of wood and wearing a turban, ostensibly driven by clockwork, who could play chess. The automaton was a hoax. It was actually controlled by a chess master of very short stature hidden inside, a human player good enough to beat Napoleon Bonaparte and Benjamin Franklin when they played against him, to their astonishment.1 The Amazon Mechanical Turk system is similar in that it emulates a machine even though, in actuality, humans are under the hood. The system is especially good for work that is easy for humans (like transcribing handwritten documents), but not for computers; therefore, the jobs posted by employers on the platform are known as HITs, for “human-intelligence tasks.”

About twenty thousand people are active at any given time, earning about six dollars per hour performing dozens of tiny chores that typically take a few minutes each. For instance, using this platform, one firm hired fifty thousand people to label the content of fourteen million images in order to create a database to train computers in image recognition.2 After the humans did their work, the real machines could take over. Amazon Mechanical Turk and other crowdsourcing platforms introduced in the past decade have revolutionized science as well as business. Scientists use these platforms to code data (like galaxies in astronomical images, proteins in biochemical images, or ancient ruins beneath jungles in satellite photographs), conduct marketing and scientific surveys, and get subjects for social science experiments. My lab was an early adopter of this platform, beginning our experiments in about 2008.


pages: 368 words: 96,825

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

3D printing, additive manufacturing, Airbnb, Amazon Mechanical Turk, Amazon Web Services, augmented reality, autonomous vehicles, Charles Lindbergh, cloud computing, creative destruction, crowdsourcing, Daniel Kahneman / Amos Tversky, dematerialisation, deskilling, disruptive innovation, Elon Musk, en.wikipedia.org, Exxon Valdez, fear of failure, Firefox, Galaxy Zoo, Google Glasses, Google Hangouts, gravity well, ImageNet competition, industrial robot, Internet of things, Jeff Bezos, John Harrison: Longitude, John Markoff, Jono Bacon, Just-in-time delivery, Kickstarter, Kodak vs Instagram, Law of Accelerating Returns, Lean Startup, life extension, loss aversion, Louis Pasteur, low earth orbit, Mahatma Gandhi, Marc Andreessen, 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, 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, superconnector, technoutopianism, telepresence, telepresence robot, Turing test, urban renewal, web application, X Prize, Y Combinator, zero-sum game

For example, a while back I wanted to determine whether Time magazine cover articles have gotten more negative during the past sixty years. At first I had my executive assistant start in 1945 and group articles into positive, neutral, or negative categories. After a day’s work, she had barely put a dent in the problem. That’s when I decided to turn to the crowd. By offering $0.05 per categorization, I got the entire 65 years’ worth of issues, roughly 3,000 in total, done for under $200. I used Amazon’s site Mechanical Turk (www.mturk.com) to get those magazine covers analyzed. While MTURK isn’t all that useful for more complicated jobs, it is where to go to get simple, quick tasks done fast. Aggregation and classification jobs tend to be popular uses. Aggregate photographs of red trucks, for example, or write product descriptions, or perform sentiment analysis exercises on thousands of Tweets. Requesters (you) post tasks known as HITs (human intelligence tasks) while workers (called providers) browse among existing tasks and complete them for a monetary payment.16 Another microtask site that I’ve previously relied upon (and with great result) is Fiverr (www.fiverr.com), an online marketplace offering microtasks starting at $5.

pagewanted=all&_r=0. 8 “Stats,” Kickstarter, https://www.kickstarter.com/help/stats. 9 Doug Gross, “Google boss: Entire world will be online by 2020,” CNN, April 15, 2013, http://www.cnn.com/2013/04/15/tech/web/eric-schmidt-internet/. 10 “Global entertainment and media outlook 2013–2017,” PricewaterhouseCoopers, 2013, https://www.pwc.com/gx/en/global-entertainment-media-outlook/. 11 Freelancer Case Study based on a series of AIs. 12 Quoted from AI: Matt Barrie. 13 Tongal Case Study based on a series of AIs with James DeJulio. 14 reCAPTCHA and Duolingo Case Study based on a series of AIs with Luis von Ahn. 15 During the completion of this book, a Bay Area startup called Vicarious wrote an AI program able to solve (i.e., read) CAPTCHAs with an accuracy of 90 percent. As mentioned earlier, “crowdsourcing” is an interim solution until such AI comes fully online. This is a relevant example of that point. 16 “FAQ—Overview,” Amazon Mechanical Turk, Amazon.com, Inc., 2014, https://www.mturk.com/mturk/help?helpPage=overview. 17 “What is Fiverr?,” Fiverr.com, 2014, http://support.fiverr.com/hc/en-us/articles/201500776-What-is-Fiverr-. 18 Unless otherwise noted, all Matt Barrie quotes come from a 2013 AI. 19 AIs with Marcus Shingles, 2013–2014. 20 AI with Andrew Vaz. 21 “About Us,” Freelancer.com, 2014, https://www.freelancer.com/info/about.php. 22 AI with Barrie. 23 Ibid. 24 AI with James DeJulio, 2013. 25 AI with Barrie. 26 Ibid. 27 “Vicarious AI passes first Turing Test: CAPTCHA,” Vicarious, October 27, 2013, http://news.vicarious.com/post/65316134613/vicarious-ai-passes-first-turing-test-captcha.


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Live Work Work Work Die: A Journey Into the Savage Heart of Silicon Valley by Corey Pein

23andMe, 4chan, affirmative action, Affordable Care Act / Obamacare, Airbnb, Amazon Mechanical Turk, Anne Wojcicki, artificial general intelligence, bank run, barriers to entry, Benevolent Dictator For Life (BDFL), Bernie Sanders, bitcoin, Build a better mousetrap, California gold rush, cashless society, colonial rule, computer age, cryptocurrency, data is the new oil, disruptive innovation, Donald Trump, Douglas Hofstadter, Elon Musk, Extropian, gig economy, Google bus, Google Glasses, Google X / Alphabet X, hacker house, hive mind, illegal immigration, immigration reform, Internet of things, invisible hand, Isaac Newton, Jeff Bezos, job automation, Kevin Kelly, Khan Academy, Law of Accelerating Returns, Lean Startup, life extension, Lyft, Mahatma Gandhi, Marc Andreessen, Mark Zuckerberg, Menlo Park, minimum viable product, move fast and break things, move fast and break things, mutually assured destruction, obamacare, passive income, patent troll, Paul Graham, peer-to-peer lending, Peter H. Diamandis: Planetary Resources, Peter Thiel, platform as a service, plutocrats, Plutocrats, Ponzi scheme, post-work, Ray Kurzweil, regulatory arbitrage, rent control, RFID, Robert Mercer, rolodex, Ronald Reagan, Ross Ulbricht, Ruby on Rails, Sam Altman, Sand Hill Road, Scientific racism, self-driving car, sharing economy, side project, Silicon Valley, Silicon Valley startup, Singularitarianism, Skype, Snapchat, social software, software as a service, source of truth, South of Market, San Francisco, Startup school, stealth mode startup, Steve Jobs, Steve Wozniak, TaskRabbit, technological singularity, technoutopianism, telepresence, too big to fail, Travis Kalanick, tulip mania, Uber for X, uber lyft, ubercab, upwardly mobile, Vernor Vinge, X Prize, Y Combinator

Under the latest iteration of the American Dream, if you aren’t a billionaire yet, you haven’t tried hard enough. * * * There was no place more appropriate to begin my conquest of the new gig economy than in the proverbial basement—from there, after all, I had nowhere to go but up. The contemporary equivalent of an entry-level job in the corporate mailroom was a work-from-home service called Mechanical Turk, operated by Amazon, the $136 billion online retailer controlled by Jeff Bezos. The idea with Mechanical Turk was to create a digitized assembly line featuring thousands of discrete “Human Intelligence Tasks,” designed to be completed within seconds and commensurately paying pennies. Academic surveys found that many Turkers worked more than thirty hours per week for average wages of under $2 per hour. Yet these workers were considered self-employed small business owners.

Luna is a pseudonym. Mike is a pseudonym. Chapter III: Gigs Make Us Free “entrepreneurialism-in-a-box” Katie Benner, “A Secret of Uber’s Success: Struggling Workers,” October 2, 2014, bloomberg.com. Academic surveys found Panagiotis G. Ipeirotis, “Demographics of Mechanical Turk,” March 2010, New York University; Lilly C. Irani and M. Six Silberman, “Turkopticon: Interrupting Worker Invisibility in Amazon Mechanical Turk,” 2013, UC Irvine. “incredible vision” “Fiverr Secures $15 Million in Second Round Funding from Accel and Bessemer, Grows 600% since 2011,” May 3, 2012, yahoo.com. “making people slaves” Ayala Tsoref, “Brains Behind ‘Micro Jobs’ Sensation Fiverr Have Amazon, eBay in Their Sights,” March 5, 2015, haaretz.com. Rhoda Lee is positively not her real name. He got the idea from a book Mark Anastasi, The Laptop Millionaire (Hoboken: Wiley, 2012).


pages: 502 words: 107,657

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

Albert Einstein, algorithmic trading, Amazon Mechanical Turk, Apple's 1984 Super Bowl advert, backtesting, Black Swan, book scanning, bounce rate, business intelligence, business process, butter production in bangladesh, call centre, Charles Lindbergh, commoditize, computer age, conceptual framework, correlation does not imply causation, crowdsourcing, dark matter, data is the new oil, en.wikipedia.org, Erik Brynjolfsson, Everything should be made as simple as possible, experimental subject, Google Glasses, happiness index / gross national happiness, job satisfaction, Johann Wolfgang von Goethe, lifelogging, Machine translation of "The spirit is willing, but the flesh is weak." to Russian and back, mass immigration, 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, Shai Danziger, 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, Thomas Bayes, Thomas Davenport, Turing test, Watson beat the top human players on Jeopardy!, X Prize, Yogi Berra, zero-sum game

See artificial intelligence (AI) airlines and aviation, predicting in Albee, Edward Albrecht, Katherine algorithmic trading. See black box trading Allen, Woody Allstate AlphaGenius Amazon.com employee security access needs machine learning and predictive models Mechanical Turk personalized recommendations sarcasm in reviews American Civil Liberties Union (ACLU) American Public University System Ansari X Prize Anxiety Index calculating as ensemble model measuring in blogs Apollo 11 Apple, Inc. Apple Mac Apple Siri Argonne National Laboratory Arizona Petrified Forest National Park Arizona State University artificial intelligence (AI) about Amazon.com Mechanical Turk mind-reading technology possibility of, the Watson computer and Asimov, Isaac astronomy AT&T Research BellKor Netflix Prize teams Australia Austria automobile insurance crashes, predicting credit scores and accidents driver inatentiveness, predicting fraud predictions for Averitt aviation incidents Aviva Insurance (UK) AWK computer language B backtesting.

A small human chess expert who did not suffer from claustrophobia (chess is a long game) hid inside the desk, viewing the board from underneath and manipulating the mannequin’s arm. Napoleon Bonaparte and Benjamin Franklin had the pleasure of losing to this wonder of innovation—I mean, this crouching, uncomfortable imposter. In the modern-day equivalent, human workers perform low-level tasks for the Amazon Mechanical Turk, a crowdsourcing website by Amazon.com that coordinates hundreds of thousands of workers to do “things that human beings can [still] do much more effectively than computers, such as identifying objects in a photo . . . [or] transcribing audio recordings.” Its slogan is “Artificial Artificial Intelligence.” (This reminds me of the vegetarian restaurant with “mock mock duck” on the menu—I swear, it tastes exactly like mock duck.)


pages: 463 words: 105,197

Radical Markets: Uprooting Capitalism and Democracy for a Just Society by Eric Posner, E. Weyl

3D printing, activist fund / activist shareholder / activist investor, Affordable Care Act / Obamacare, Airbnb, Amazon Mechanical Turk, anti-communist, augmented reality, basic income, Berlin Wall, Bernie Sanders, Branko Milanovic, business process, buy and hold, carbon footprint, Cass Sunstein, Clayton Christensen, cloud computing, collective bargaining, commoditize, Corn Laws, corporate governance, crowdsourcing, cryptocurrency, Donald Trump, Elon Musk, endowment effect, Erik Brynjolfsson, Ethereum, feminist movement, financial deregulation, Francis Fukuyama: the end of history, full employment, George Akerlof, global supply chain, guest worker program, hydraulic fracturing, Hyperloop, illegal immigration, immigration reform, income inequality, income per capita, index fund, informal economy, information asymmetry, invisible hand, Jane Jacobs, Jaron Lanier, Jean Tirole, Joseph Schumpeter, Kenneth Arrow, labor-force participation, laissez-faire capitalism, Landlord’s Game, liberal capitalism, low skilled workers, Lyft, market bubble, market design, market friction, market fundamentalism, mass immigration, negative equity, Network effects, obamacare, offshore financial centre, open borders, Pareto efficiency, passive investing, patent troll, Paul Samuelson, performance metric, plutocrats, Plutocrats, pre–internet, random walk, randomized controlled trial, Ray Kurzweil, recommendation engine, rent-seeking, Richard Thaler, ride hailing / ride sharing, risk tolerance, road to serfdom, Robert Shiller, Robert Shiller, Ronald Coase, Rory Sutherland, Second Machine Age, second-price auction, self-driving car, shareholder value, sharing economy, Silicon Valley, Skype, special economic zone, spectrum auction, speech recognition, statistical model, stem cell, telepresence, Thales and the olive presses, Thales of Miletus, The Death and Life of Great American Cities, The Future of Employment, The Market for Lemons, The Nature of the Firm, The Rise and Fall of American Growth, The Wealth of Nations by Adam Smith, Thorstein Veblen, trade route, transaction costs, trickle-down economics, Uber and Lyft, uber lyft, universal basic income, urban planning, Vanguard fund, women in the workforce, Zipcar

Technofeudalism Why, then, do siren servers not voluntarily pay their users to supply the high-quality data that would allow them to develop the best services? If data production is labor, why doesn’t a market for data work emerge as a part of the broader labor market? In fact, we have seen tentative first signs of markets for high-quality, labeled data. Many researchers and some companies use Amazon’s Mechanical Turk (mTurk) marketplace to pay online workers to label and clean data sets, and to participate in social-science experiments. This is not entirely new. Television ratings are still determined by Nielsen, which pays households a small fee to record their viewing. Notice, however, that the buyers of data in these settings are for the most part not the siren servers we have been discussing. Instead, they are smaller companies, academic researchers, and financial firms with no direct access to data.

Apparently from the abolitionist Wendell Phillips in 1853. See http://www.bartleby.com/73/1073.html. Chapter 5. Data as Labor 1. Jaron Lanier, Who Owns the Future? (Simon & Schuster, 2013). 2. While Lanier’s work provided the direct inspiration for our work, the themes he raises appeared roughly simultaneously in other scholarship. See, for example, Lilly C. Irani & M. Six Silberman, Turkopticon: Interrupting Worker Invisibility in Amazon Mechanical Turk, CHI’13 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (2013), and Trebor Scholz, ed., Digital Labor: The Internet as Playground and Factory (Routledge, 2013). 3. Imanol Arrieta-Ibarra, Leonard Goff, Diego Jiménez-Hernández, Jaron Lanier & E. Glen Weyl, Should We Treat Data as Labor? Moving Beyond “Free,” American Economic Association Papers and Proceedings (Forthcoming). 4.


pages: 222 words: 70,132

Move Fast and Break Things: How Facebook, Google, and Amazon Cornered Culture and Undermined Democracy by Jonathan Taplin

1960s counterculture, affirmative action, Affordable Care Act / Obamacare, Airbnb, Amazon Mechanical Turk, American Legislative Exchange Council, Apple's 1984 Super Bowl advert, back-to-the-land, barriers to entry, basic income, battle of ideas, big data - Walmart - Pop Tarts, bitcoin, Brewster Kahle, Buckminster Fuller, Burning Man, Clayton Christensen, commoditize, creative destruction, crony capitalism, crowdsourcing, data is the new oil, David Brooks, David Graeber, don't be evil, Donald Trump, Douglas Engelbart, Douglas Engelbart, Dynabook, Edward Snowden, Elon Musk, equal pay for equal work, Erik Brynjolfsson, future of journalism, future of work, George Akerlof, George Gilder, Google bus, Hacker Ethic, Howard Rheingold, income inequality, informal economy, information asymmetry, information retrieval, Internet Archive, Internet of things, invisible hand, Jaron Lanier, Jeff Bezos, job automation, John Markoff, John Maynard Keynes: technological unemployment, John von Neumann, Joseph Schumpeter, Kevin Kelly, Kickstarter, labor-force participation, life extension, Marc Andreessen, Mark Zuckerberg, Menlo Park, Metcalfe’s law, Mother of all demos, move fast and break things, move fast and break things, natural language processing, Network effects, new economy, Norbert Wiener, offshore financial centre, packet switching, Paul Graham, paypal mafia, Peter Thiel, plutocrats, Plutocrats, pre–internet, Ray Kurzweil, recommendation engine, rent-seeking, revision control, Robert Bork, Robert Gordon, Robert Metcalfe, Ronald Reagan, Ross Ulbricht, Sam Altman, Sand Hill Road, secular stagnation, self-driving car, sharing economy, Silicon Valley, Silicon Valley ideology, smart grid, Snapchat, software is eating the world, Steve Jobs, Stewart Brand, technoutopianism, The Chicago School, The Market for Lemons, The Rise and Fall of American Growth, Tim Cook: Apple, trade route, transfer pricing, Travis Kalanick, trickle-down economics, Tyler Cowen: Great Stagnation, universal basic income, unpaid internship, We wanted flying cars, instead we got 140 characters, web application, Whole Earth Catalog, winner-take-all economy, women in the workforce, Y Combinator

Perhaps written from the deck of Perkins’s yacht (one of the world’s largest), the letter was an embarrassment for the other partners at Kleiner Perkins. This sense of class strife in San Francisco could be just a preview of a darker scenario brought about by the robot and artificial-intelligence revolution that Google, Amazon, Facebook, and others are investing in, including the “Uberization” of many tasks. Platforms such as Amazon’s Mechanical Turk allow firms to outsource online piecework, or “crowdwork.” As Mary L. Gray reports in the Los Angeles Times, “Researchers at Oxford University’s Martin Programme on Technology and Employment estimate that nearly 30% of jobs in the U.S. could be organized like this within 20 years. Forget the rise of robots and the distant threat of automation. The immediate issue is the Uber-izing of human labor, fragmenting of jobs into outsourced tasks and dismantling of wages into micropayments.”

Researcher Sara Kingsley at the University of Massachusetts found real problems with the crowdwork model. A direct and limitless supply of labor and tasks should produce a perfectly competitive market; however, data collected from our yearlong study of crowdwork suggests that the reverse is true. Rife with asymmetric information problems, crowdsourcing labor markets are arguably not just imperfect, but imperfect by design. Kingsley found that Amazon could constantly lower the piecework price it paid on Mechanical Turk and that it was continually opening up new low-labor-cost countries, such as India, to the platform. Given that Amazon runs a monopsony book business, it’s no surprise that it might apply the same techniques to other business sectors. But it is not only people working out of their homes doing crowdwork who are going to be threatened. Dan Bindman, writing in the publication Legal Futures, reports that “robots and artificial intelligence (AI) will dominate legal practice within fifteen years, perhaps leading to the ‘structural collapse’ of law firms.”

• The willingness to live an examined life with a core faith or philosophy. If we think about the world techno-utopians are envisioning, it may be hard for the average citizen to have the freedom and autonomy to enjoy meaningful work. Would a life where your daily existence relied on driving four hours a day for Uber, serving as a concierge for your Airbnb guests in the spare room, and spending your evenings doing crowdwork on Amazon’s Mechanical Turk meet Epicurus’s test? And would you have any time to live an “examined” life? Is the goal of tech success freedom, or addiction? 6. The New Camaldoli Hermitage perches 1,300 feet above the Pacific in Big Sur, California, and is void of cellular service, Wi-Fi, and all other electronic conveniences. For my sixty-eighth birthday, inspired by a little book by Pico Iyer, The Art of Stillness: Adventures in Going Nowhere, I gave myself the gift of time and peace at this Benedictine retreat.


pages: 215 words: 55,212

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

Airbnb, Amazon Mechanical Turk, Amazon Web Services, banking crisis, barriers to entry, carbon footprint, Chuck Templeton: OpenTable:, cloud computing, credit crunch, crowdsourcing, diversification, Firefox, fixed income, Google Earth, industrial cluster, Internet of things, Joi Ito, 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

Whether you’re looking for a ride to the airport, a recommendation for good eats, or a dog sitter, FriendlyFavor will help you reach out to your “peeps”—your trusted network of friends, family, and colleagues. And it’s efficient. Instead of sorting through endless e-mail threads, FriendlyFavor sends an appeal to your peeps using your existing e-mail lists and then archives any responses (Think Evite). The Web site also helps you repay the favor with an exchange of services, gift certificates, or charitable donations. Amazon Mechanical Turk: Marketplace for work. https://www.mturk.com crowdSPRING: Offers affordable graphic design and writing services to small businesses by connecting consumers with creative professionals. http://www.crowdspring.com FriendlyFavor: Request tool that enables users to ask, offer, and manage favors online. http://www.friendlyfavor.com Guru: Members find freelancers at Guru’s online service marketplace.


pages: 561 words: 157,589

WTF?: What's the Future and Why It's Up to Us by Tim O'Reilly

4chan, Affordable Care Act / Obamacare, Airbnb, Alvin Roth, Amazon Mechanical Turk, Amazon Web Services, artificial general intelligence, augmented reality, autonomous vehicles, barriers to entry, basic income, Bernie Madoff, Bernie Sanders, Bill Joy: nanobots, bitcoin, blockchain, Bretton Woods, Brewster Kahle, British Empire, business process, call centre, Capital in the Twenty-First Century by Thomas Piketty, Captain Sullenberger Hudson, Chuck Templeton: OpenTable:, Clayton Christensen, clean water, cloud computing, cognitive dissonance, collateralized debt obligation, commoditize, computer vision, corporate governance, corporate raider, creative destruction, crowdsourcing, Danny Hillis, data acquisition, deskilling, DevOps, Donald Davies, Donald Trump, Elon Musk, en.wikipedia.org, Erik Brynjolfsson, Filter Bubble, Firefox, Flash crash, full employment, future of work, George Akerlof, gig economy, glass ceiling, Google Glasses, Gordon Gekko, gravity well, greed is good, Guido van Rossum, High speed trading, hiring and firing, Home mortgage interest deduction, Hyperloop, income inequality, index fund, informal economy, information asymmetry, Internet Archive, Internet of things, invention of movable type, invisible hand, iterative process, Jaron Lanier, Jeff Bezos, jitney, job automation, job satisfaction, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, Kevin Kelly, Khan Academy, Kickstarter, knowledge worker, Kodak vs Instagram, Lao Tzu, Larry Wall, Lean Startup, Leonard Kleinrock, Lyft, Marc Andreessen, Mark Zuckerberg, market fundamentalism, Marshall McLuhan, McMansion, microbiome, microservices, minimum viable product, mortgage tax deduction, move fast and break things, move fast and break things, Network effects, new economy, Nicholas Carr, obamacare, Oculus Rift, packet switching, PageRank, pattern recognition, Paul Buchheit, peer-to-peer, peer-to-peer model, Ponzi scheme, race to the bottom, Ralph Nader, randomized controlled trial, RFC: Request For Comment, Richard Feynman, Richard Stallman, ride hailing / ride sharing, Robert Gordon, Robert Metcalfe, Ronald Coase, Sam Altman, school choice, Second Machine Age, secular stagnation, self-driving car, SETI@home, shareholder value, Silicon Valley, Silicon Valley startup, skunkworks, Skype, smart contracts, Snapchat, Social Responsibility of Business Is to Increase Its Profits, social web, software as a service, software patent, spectrum auction, speech recognition, Stephen Hawking, Steve Ballmer, Steve Jobs, Steven Levy, Stewart Brand, strong AI, TaskRabbit, telepresence, the built environment, The Future of Employment, the map is not the territory, The Nature of the Firm, The Rise and Fall of American Growth, The Wealth of Nations by Adam Smith, Thomas Davenport, transaction costs, transcontinental railway, transportation-network company, Travis Kalanick, trickle-down economics, Uber and Lyft, Uber for X, uber lyft, ubercab, universal basic income, US Airways Flight 1549, VA Linux, Watson beat the top human players on Jeopardy!, We are the 99%, web application, Whole Earth Catalog, winner-take-all economy, women in the workforce, Y Combinator, yellow journalism, zero-sum game, Zipcar

From the point of view of the company offering an online service, software has gone from being a thing to a process, and ultimately, a series of business workflows. The design of those workflows has to be optimized not just for the creators of the software but for the people who will keep them running day-to-day. The key idea is that a company is now a hybrid organism, made up of people and machines. I had made this point too in my 2003 Amazon all-hands talk. I’d told the story of von Kempelen’s Mechanical Turk, the chess-playing automaton that toured Europe in the late eighteenth and early nineteenth centuries, astonishing (and defeating) such luminaries as Napoleon and Benjamin Franklin. The supposed automaton actually had a chess master hidden inside, with a set of lenses to see the board and a set of levers to move the hands of the automaton. I thought this was a marvelous metaphor for the new generation of web applications.

Those inputs were then formatted, curated, and extended by their own staff in the form of editorial reviews, designs, and programming. And that dynamic river of content was managed, day in and day out, by all of the people who worked for Amazon. I remember saying “All of you—programmers, designers, writers, product managers, product buyers, customer service reps—are inside the application.” (For a long time, I wondered whether my telling of this story might have inspired Amazon to create the Amazon Mechanical Turk service, which uses a crowdsourced network of workers to perform small tasks that are hard for computers to do. However, while the service was launched in 2005, the patent for it was filed in 2001 though not issued until 2007, so at best I might have inspired the name. The name given to it in the patent diagrams is “Junta.”) My insight that, on the Internet, programmers were “inside the application” had unfolded gradually over time.

Remember that Google Photos is doing this on demand for the photos of more than 200 million users, photos that it’s never seen before, hundreds of billions of them. This is called supervised learning, because, while Google Photos hasn’t seen your photos before, it has seen a lot of other photos. In particular, it’s seen what’s called a training set. In the training set, the data is labeled. Amazon’s Mechanical Turk, or services like it, are used to send out pictures, one at a time, to thousands of workers who are asked to say what each contains, or to answer a question about some aspect of it (such as its color), or, as in the case of the Google Photos training set, simply to write a caption for it. Amazon calls these microtasks HITs (Human Intelligence Tasks). Each one asks a single question, perhaps even using multiple choice: “What color is the car in this picture?”


pages: 230 words: 61,702

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

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, Panopticon Jeremy Bentham, 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

Here’s how it works: nonprofits and businesses post prize competitions for solutions to challenges. These can run the gamut—from retail product positioning to early detection mechanisms for inflammatory bowel disease. The prizes themselves vary in size, with some topping nearly a million dollars but many being significantly less. InnoCentive is only one example of how crowdsourcing can work, of course. Other famous examples include Amazon’s Mechanical Turk, which allows companies (and scientific researchers) to outsource specific tasks to a huge network of “Turkers” to perform tasks that humans are still better at than computers, such as image identification and translation. Still another is Threadless, an organization that assigns a crowd of T-shirt designers the job of selecting (and creating) new T-shirt designs. Challenge-specific prizes, like those used by InnoCentive, have been useful sources of innovation in scientific research for centuries.

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.” But as Brabham has convincingly argued, the idea of the “amateur crowd” is largely a myth. Turkers working for Amazon are generally highly educated professionals working in areas of the world where financially rewarding employment for those skills is significantly less than elsewhere (hence the attraction of Turk).


pages: 229 words: 61,482

The Gig Economy: The Complete Guide to Getting Better Work, Taking More Time Off, and Financing the Life You Want by Diane Mulcahy

Affordable Care Act / Obamacare, Airbnb, Amazon Mechanical Turk, basic income, Clayton Christensen, cognitive bias, collective bargaining, creative destruction, David Brooks, deliberate practice, diversification, diversified portfolio, fear of failure, financial independence, future of work, gig economy, helicopter parent, Home mortgage interest deduction, housing crisis, job satisfaction, Kickstarter, loss aversion, low skilled workers, Lyft, mass immigration, mental accounting, minimum wage unemployment, mortgage tax deduction, negative equity, passive income, Paul Graham, remote working, risk tolerance, Robert Shiller, Robert Shiller, Silicon Valley, Snapchat, TaskRabbit, Uber and Lyft, uber lyft, universal basic income, wage slave, Y Combinator, Zipcar

More than one-third (37 percent) of workers expect to retire after age 65, compared to 11 percent in 1991.20 More than half of workers age 40+ plan to work into their 70s because they won’t have enough retirement savings to live comfortably.21 Fortunately, the Gig Economy offers retirees more opportunities to work. Granny might not be able to hold a full-time corporate job into her 70s, but now there are many other options for her to work part time, at home, and on her own schedule. She can dog sit on Rover.com, host dinners for paying diners through Feastly or EatWith, or rent a room of her house on Airbnb. She can work remotely on administrative or other small tasks on Upwork or as an Amazon Mechanical Turk. She can drive for Uber a few hours a week or babysit through Care.com. In the Gig Economy, retirees looking to supplement Social Security or an underfunded IRA can more easily than ever find flexible (and even home-based) work to generate incremental income. Even with more options for flexible work, planning to work longer is a risky plan because we don’t fully control when we’ll stop working.


Bulletproof Problem Solving by Charles Conn, Robert McLean

active transport: walking or cycling, Airbnb, Amazon Mechanical Turk, asset allocation, availability heuristic, Bayesian statistics, Black Swan, blockchain, business process, call centre, carbon footprint, cloud computing, correlation does not imply causation, Credit Default Swap, crowdsourcing, David Brooks, Donald Trump, Elon Musk, endowment effect, future of work, Hyperloop, Innovator's Dilemma, inventory management, iterative process, loss aversion, meta analysis, meta-analysis, Nate Silver, nudge unit, Occam's razor, pattern recognition, pets.com, prediction markets, principal–agent problem, RAND corporation, randomized controlled trial, risk tolerance, Silicon Valley, smart contracts, stem cell, the rule of 72, the scientific method, The Signal and the Noise by Nate Silver, time value of money, transfer pricing, Vilfredo Pareto, walkable city, WikiLeaks

Standard statistical software, such as R, Stata, or various Python packages, can easily support regression analyses similar to Evan and David's. EXHIBIT 6.7 In this analysis, the crucial independent variable was the perceived race of delegates. To get the data, Evan and David were entrepreneurial: They matched delegates' last names to a dataset from the US Census that provides, for each last name, a share of Americans with a last name who are nonwhite. They also paid online workers on Amazon's Mechanical Turk (mTurk) marketplace to guess, without further information, the racial background of delegates from their names alone, replicating their view of what voters might be doing in the privacy of the voting booth. This is a form of crowdsourcing, which we'll discuss more below. The actual vote counts, their dependent variable, came from the Illinois State Board of Elections. Knowing where and how to find data, whether from administrative releases from the Census or from mTurk surveys, is itself a vital tool in your analytical arsenal.


pages: 239 words: 80,319

Lurking: How a Person Became a User by Joanne McNeil

4chan, A Declaration of the Independence of Cyberspace, Ada Lovelace, Airbnb, AltaVista, Amazon Mechanical Turk, Burning Man, Chelsea Manning, Chris Wanstrath, citation needed, cloud computing, crowdsourcing, delayed gratification, dematerialisation, don't be evil, Donald Trump, drone strike, Edward Snowden, Elon Musk, feminist movement, Firefox, Google Earth, Google Glasses, Google Hangouts, helicopter parent, Internet Archive, invention of the telephone, Jeff Bezos, jimmy wales, l'esprit de l'escalier, Marc Andreessen, Mark Zuckerberg, Marshall McLuhan, means of production, Menlo Park, moral panic, move fast and break things, move fast and break things, Network effects, packet switching, PageRank, pre–internet, profit motive, QAnon, recommendation engine, Saturday Night Live, Shoshana Zuboff, Silicon Valley, slashdot, Snapchat, social graph, Stephen Hawking, Steve Jobs, Steven Levy, Stewart Brand, technoutopianism, Ted Nelson, Tim Cook: Apple, trade route, Turing complete, We are the 99%, web application, white flight, Whole Earth Catalog

Over the relatively short period of time that the internet has existed, users have been cast as narcissists, if not the cause of the downfall of civilization, as the media spotlights bad actors as representative of the internet populace, eliding the quagmire of company policies that foment abuses and calcify hatred. “Engagement” is the inscrutable basis over which these companies present themselves as commonweal rather than mercenary: these companies—the platforms—show commitment to advertisers before users, while expressing otherwise in corporate communications. “I am a human being, not an algorithm,” Kristy Milland, an Amazon Mechanical Turk worker, once wrote in an email to jeff@amazon.com, describing how she relies on MTurk income to keep her “family safe from foreclosure,” and wishes to be seen on the platform as a “highly skilled laborer,” rather than hidden from requesters like lines of code. She wasn’t speaking as a user, but as a laborer. But even users can be conscripted to these platforms just the same, subject to the whims of Silicon Valley mega-corporations as if they were exploited workers or dispirited constituents.


Hands-On Machine Learning With Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems by Aurelien Geron

Amazon Mechanical Turk, Bayesian statistics, centre right, combinatorial explosion, constrained optimization, correlation coefficient, crowdsourcing, en.wikipedia.org, iterative process, Netflix Prize, NP-complete, optical character recognition, P = NP, p-value, pattern recognition, performance metric, recommendation engine, self-driving car, SpamAssassin, speech recognition, statistical model

This is important to catch not only sudden breakage, but also performance degradation. This is quite common because models tend to “rot” as data evolves over time, unless the models are regularly trained on fresh data. Evaluating your system’s performance will require sampling the system’s predictions and evaluating them. This will generally require a human analysis. These analysts may be field experts, or workers on a crowdsourcing platform (such as Amazon Mechanical Turk or CrowdFlower). Either way, you need to plug the human evaluation pipeline into your system. You should also make sure you evaluate the system’s input data quality. Sometimes performance will degrade slightly because of a poor quality signal (e.g., a malfunctioning sensor sending random values, or another team’s output becoming stale), but it may take a while before your system’s performance degrades enough to trigger an alert.


pages: 380 words: 118,675

The Everything Store: Jeff Bezos and the Age of Amazon by Brad Stone

airport security, Amazon Mechanical Turk, Amazon Web Services, bank run, Bernie Madoff, big-box store, Black Swan, book scanning, Brewster Kahle, buy and hold, call centre, centre right, Chuck Templeton: OpenTable:, Clayton Christensen, cloud computing, collapse of Lehman Brothers, crowdsourcing, cuban missile crisis, Danny Hillis, Douglas Hofstadter, Elon Musk, facts on the ground, game design, housing crisis, invention of movable type, inventory management, James Dyson, Jeff Bezos, John Markoff, Kevin Kelly, Kodak vs Instagram, late fees, loose coupling, low skilled workers, Maui Hawaii, Menlo Park, Network effects, new economy, optical character recognition, pets.com, Ponzi scheme, quantitative hedge fund, recommendation engine, Renaissance Technologies, RFID, Rodney Brooks, search inside the book, shareholder value, Silicon Valley, Silicon Valley startup, six sigma, skunkworks, Skype, statistical arbitrage, Steve Ballmer, Steve Jobs, Steven Levy, Stewart Brand, Thomas L Friedman, Tony Hsieh, Whole Earth Catalog, why are manhole covers round?, zero-sum game

To their surprise, Bezos then actually developed a version of Project Agreya inside Amazon. He renamed it Mechanical Turk, after an eighteenth-century chess-playing automaton that concealed a diminutive man—a chess master—who hid inside and guided the machine’s moves. About two dozen Amazon employees worked on the service from January 2004 to November 2005. It was considered a Jeff project, which meant that the product manager met with Bezos every few weeks and received a constant stream of e-mail from the CEO, usually containing extraordinarily detailed recommendations and frequently arriving late at night. Amazon started using Mechanical Turk internally in 2005 to have humans do things like review Search Inside the Book scans and check product images uploaded to Amazon by customers to ensure they were not pornographic. The company also used Mechanical Turk to match the images with the corresponding commercial establishments in A9’s fledgling Block View tool.

Bezos liked the name for its historical association but agreed to let the communications staff and Mechanical Turk team brainstorm alternatives. They seriously considered Cadabra, an allusion to magic and the original corporate name of Amazon. But in the end, Bezos shrugged off the concerns and said that he personally would bear the responsibility for any backlash. Mechanical Turk quietly launched in November 2005. Now any Internet user could perform what Amazon called human-intelligence tasks, typically earning a few cents per job. Other companies could list jobs on the Mechanical Turk website, with Amazon taking a 10 percent cut of the payments.11 One of the first applications, from a company called Casting Words, paid workers a few cents per minute to listen to and transcribe podcasts. Mechanical Turk gave Bezos another opportunity to demonstrate Amazon’s ability to innovate outside of its core retail business and show off his own curious attempts to crystallize abstract concepts.


pages: 629 words: 142,393

The Future of the Internet: And How to Stop It by Jonathan Zittrain

A Declaration of the Independence of Cyberspace, Amazon Mechanical Turk, Andy Kessler, barriers to entry, book scanning, Brewster Kahle, Burning Man, c2.com, call centre, Cass Sunstein, citizen journalism, Clayton Christensen, clean water, commoditize, corporate governance, Daniel Kahneman / Amos Tversky, disruptive innovation, distributed generation, en.wikipedia.org, Firefox, game design, Hacker Ethic, Howard Rheingold, Hush-A-Phone, illegal immigration, index card, informal economy, Internet Archive, jimmy wales, John Markoff, license plate recognition, loose coupling, mail merge, national security letter, old-boy network, packet switching, peer-to-peer, post-materialism, pre–internet, price discrimination, profit maximization, Ralph Nader, RFC: Request For Comment, RFID, Richard Stallman, Richard Thaler, risk tolerance, Robert Bork, Robert X Cringely, SETI@home, Silicon Valley, Skype, slashdot, software patent, Steve Ballmer, Steve Jobs, Ted Nelson, Telecommunications Act of 1996, The Nature of the Firm, The Wisdom of Crowds, web application, wikimedia commons, zero-sum game

InnoCentive Frequently Asked Questions, http://www.innocentive.com/faqs.php (last visited Sept. 30, 2007) (“If your solution is selected as ‘best’ by the Seeker, prior to receiving a financial award you must transfer your intellectual property rights in the solution.”). 22. Amazon’s Mechanical Turk, http://www.mturk.com/mturk/welcome (last visited Sept. 30, 2007); see also Posting of Elinor Mills to Tech News Blog, Amazon’s Mechanical Turk Lets You Make $$$, Sort Of, http://www.news.com/8301-10784_3-9782813-7.html (Sept. 21, 2007, 12:35 PDT). Index accessibility, 29, 72–73, 77, 93, 131, 188, 232 accountability, 32, 162–63 acoustic separation, 122 adaptability, 71–72, 93, 125 Adler, Michael, 110 advertising industry, 56 affordance theory, 78 amateur innovation, 26, 27 Amazon.com, 214; differential pricing by, 204–5; Mechanical Turk, 246; “mouse droppings,” 217, 219; and user ratings, 146, 147, 151, 215 AMD, Telmex Internet Box, 59 Anderson, Chris, 85 Anderson County, Tennessee, jailcams in, 209–10 anonymity, 33 Answers.com, 145 antiabortion activism, 215 AOL (America Online), 174; adding new features to, 23, 106–7; control exercised by, 3, 7, 57, 81, 82; and dumb terminals, 101–2; and hyperlinks, 89; and PlayMedia, 104; walled gardens of, 29, 89, 254n7 Apache Web server, 192 APIs (application programming interfaces), 124, 184–85, 215 Apple Computers: Apple II personal computers, 1–2, 3; business model of, 17; Dashboard, 272n55; data gathering by, 160; iPhone, 1, 2–3, 5, 101, 106, 182; iPod, 1, 101, 233; iTunes, 105, 121, 197; VisiCalc, 2; word processing software of, 17 appliance model, 17 appliances: consumer information technology in, 13; contingent, 107; intended for individual use, 18; ownership of, 106; regulability of, 107, 125; remote updates of, 106–7; security worries with, 106–7, 123–24, 150; smarter, 107; tethered, 3, 4, 5, 8–9, 59, 101–3, 106, 107.

Our generative technologies need technically skilled people of goodwill to keep them going, and the fledgling generative activities above—blogging, wikis, social networks—need artistically and intellectually skilled people of goodwill to serve as true alternatives to a centralized, industrialized information economy that asks us to identify only as consumers of meaning rather than as makers of it. Peer production alone does not guarantee collaborative meaning making. Services like InnoCentive place five-figure bounties on difficult but modular scientific problems, and ask the public at large to offer solutions.20 But the solutions tendered then become the full property of the institutional bounty hunter.21 Amazon’s Mechanical Turk has created a marketplace for the solving of so-called human intelligence tasks on the other side of the scale: trivial, repetitive tasks like tracing lines around the faces in photographs for a firm that has some reason to need them traced.22 If five years from now children with XOs were using them for hours each day primarily to trace lines at half a penny per trace, it could be a useful economic engine to some and a sweatshop to others—but either way it would not be an activity that is generative at the content layer.


pages: 398 words: 86,855

Bad Data Handbook by Q. Ethan McCallum

Amazon Mechanical Turk, asset allocation, barriers to entry, Benoit Mandelbrot, business intelligence, cellular automata, chief data officer, Chuck Templeton: OpenTable:, cloud computing, cognitive dissonance, combinatorial explosion, commoditize, conceptual framework, database schema, DevOps, en.wikipedia.org, Firefox, Flash crash, Gini coefficient, illegal immigration, iterative process, labor-force participation, loose coupling, natural language processing, Netflix Prize, quantitative trading / quantitative finance, recommendation engine, selection bias, sentiment analysis, statistical model, supply-chain management, survivorship bias, text mining, too big to fail, web application

That let us move high-probability photos to the front of slideshows, rather than just having two categories. Conclusion We’re still using the results of the competition very successfully in our product today. I hope this walk-through gave you an idea of how to work effectively with outside machine-learning experts, whether through a contest like Kaggle or through a more traditional arrangement. * * * [73] “Kaggle: making data science a sport.” (http://www.kaggle.com/) [74] Amazon Mechanical Turk: “Artificial Artificial Intelligence.” (https://www.mturk.com/) [75] scikit-learn: machine learning in Python (http://scikit-learn.org/) Chapter 17. Data Traceability Reid Draper Your software consistently provides impressive music recommendations by combining cultural and audio data. Customers are happy. However, things aren’t always perfect. Sometimes that Beyoncé track is attributed to Beyonce.


pages: 337 words: 86,320

Everybody Lies: Big Data, New Data, and What the Internet Can Tell Us About Who We Really Are by Seth Stephens-Davidowitz

affirmative action, AltaVista, Amazon Mechanical Turk, Asian financial crisis, Bernie Sanders, big data - Walmart - Pop Tarts, Cass Sunstein, computer vision, correlation does not imply causation, crowdsourcing, Daniel Kahneman / Amos Tversky, desegregation, Donald Trump, Edward Glaeser, Filter Bubble, game design, happiness index / gross national happiness, income inequality, Jeff Bezos, John Snow's cholera map, longitudinal study, Mark Zuckerberg, Nate Silver, peer-to-peer lending, Peter Thiel, price discrimination, quantitative hedge fund, Ronald Reagan, Rosa Parks, sentiment analysis, Silicon Valley, statistical model, Steve Jobs, Steven Levy, Steven Pinker, TaskRabbit, The Signal and the Noise by Nate Silver, working poor

47 a food’s being shaped like a phallus: I coded foods as being shaped as a phallus if they were significantly more long than wide and generally round. I counted cucumbers, corn, carrots, eggplant, squash, and bananas. The data and code can be found at sethsd.com. 48 errors collected by Microsoft researchers: The dataset can be downloaded at https://www.microsoft.com/en-us/download/details.aspx?id=52418. The researchers asked users of Amazon Mechanical Turk to describe images. They analyzed the keystroke logs and noted any time someone corrected a word. More details can be found in Yukino Baba and Hisami Suzuki, “How Are Spelling Errors Generated and Corrected? A Study of Corrected and Uncorrected Spelling Errors Using Keystroke Logs,” Proceedings of the Fiftieth Annual Meeting of the Association for Computational Linguistics, 2012. The data, code, and a further description of this research can be found at sethsd.com. 51 Consider all searches of the form “I want to have sex with my”: The full data—warning: graphic—is as follows: “I WANT TO HAVE SEX WITH . . .”


pages: 903 words: 235,753

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

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, basic income, Benevolent Dictator For Life (BDFL), 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, Douglas Engelbart, Edward Snowden, Elon Musk, en.wikipedia.org, Eratosthenes, Ethereum, 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, Intergovernmental Panel on Climate Change (IPCC), intermodal, Internet of things, invisible hand, Jacob Appelbaum, Jaron Lanier, Joan Didion, John Markoff, Joi Ito, Jony Ive, Julian Assange, Khan Academy, liberal capitalism, lifelogging, linked data, Mark Zuckerberg, market fundamentalism, Marshall McLuhan, Masdar, McMansion, means of production, megacity, megastructure, Menlo Park, Minecraft, MITM: man-in-the-middle, Monroe Doctrine, Network effects, new economy, offshore financial centre, oil shale / tar sands, packet switching, PageRank, pattern recognition, peak oil, peer-to-peer, performance metric, personalized medicine, Peter Eisenman, Peter Thiel, phenotype, Philip Mirowski, Pierre-Simon Laplace, place-making, planetary scale, RAND corporation, recommendation engine, reserve currency, RFID, Robert Bork, 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, undersea cable, universal basic income, urban planning, Vernor Vinge, Washington Consensus, web application, Westphalian system, WikiLeaks, working poor, Y Combinator

Similarly, the role for HFT algorithms is indeterminable, even though they do not speak at us they do speak for us, and we can assume that if similar forms of weaponized mathematics become more normative, then the plural and partial nature of any individuated human User subject interest and position may be that much harder to keep straight. In the ongoing technologicization of intelligence, we see cute slippages of position between humans and machines. For example, the original mechanical turk in the eighteenth century was a chess-playing machine, apparently an automaton exhibiting human intelligence, but in fact operated from afar by a human User. Today Amazon Mechanical Turk restages this arrangement, not just for chess but for any menial task the User can devise. Behind the browser are at least half a million “workers” who complete piecemeal tasks for micropayment.47 We see not AIs appearing as if they were human, but humans appearing as if they were AIs. As it's been since Karel Čapek's “universal robots” introduced on the stage in 1921, the robot not only mimics the human, but provides a portrait of the human as an object viewable to itself from the outside, and with the human negotiates an ongoing dance of reciprocal idealization.

If we follow the thread of Alex Rivera's Sleep Dealer (2008), a film in which California's agriculture is served by drone pilot/robot fruit pickers working remotely from behind the sovereign wall separating the United States and Mexico, it is not unreasonable to imagine a further logistic dehumanization of Fresno's on-site population.21 Perhaps the costs of piloting agricultural labor will be held down by global wage arbitrage, pickers in Tijuana competing with pickers in Jakarta and Juneau to provide fast and cheap results. That is, formal national jurisdiction may have far less to do with the economics of Cloud feudalism than with whichever Cloud Polis, enclave platform, or urban camp happens to counts a given worker as one of its Users. The elevation of labor systems like Amazon's Mechanical Turk, TaskRabbit, and Uber to infrastructural scale suggests several paradoxical and even contradictory outcomes, both positive and negative. One of these is well summarized as: “I'm really looking forward to a future in which service employees are leased Google Glass so they can complete courses in for-profit trade schools while simultaneously earning health care vouchers instead of actual currency and Soylent instead of actual food.”22 We should add, however, that the lease terms on that Glass set are conditional on whether the User actually won the bid to pilot-pick avocados.


pages: 116 words: 31,356

Platform Capitalism by Nick Srnicek

3D printing, additive manufacturing, Airbnb, Amazon Mechanical Turk, Amazon Web Services, Capital in the Twenty-First Century by Thomas Piketty, cloud computing, collaborative economy, collective bargaining, deindustrialization, deskilling, disintermediation, future of work, gig economy, Infrastructure as a Service, Internet of things, Jean Tirole, Jeff Bezos, knowledge economy, knowledge worker, liquidity trap, low skilled workers, Lyft, Mark Zuckerberg, means of production, mittelstand, multi-sided market, natural language processing, Network effects, new economy, Oculus Rift, offshore financial centre, pattern recognition, platform as a service, quantitative easing, RFID, ride hailing / ride sharing, Robert Gordon, self-driving car, sharing economy, Shoshana Zuboff, Silicon Valley, Silicon Valley startup, software as a service, TaskRabbit, the built environment, total factor productivity, two-sided market, Uber and Lyft, Uber for X, uber lyft, unconventional monetary instruments, unorthodox policies, Zipcar

As a result, numerous workers were forced to find whatever desperate means they could to survive. In this context, self-employment is not a freely chosen path, but rather a forced imposition. A look at the demographics of lean platform workers seems to support this. Of the workers on TaskRabbit, 70 per cent have Bachelor’s degrees, while 5 per cent have PhDs.76 An International Labour Organization (ILO) survey found that workers on Amazon’s Mechanical Turk (AMT) also tend to be highly educated, 37 per cent using crowd work as their main job.77 And Uber admits that around a third of its drivers in London come from neighbourhoods with unemployment rates of more than 10 per cent.78 In a healthy economy these people would have no need to be microtasking, as they would have proper jobs. While the other platform types have all developed novel elements, is there anything new about lean platforms?


pages: 326 words: 91,559

Everything for Everyone: The Radical Tradition That Is Shaping the Next Economy by Nathan Schneider

1960s counterculture, Affordable Care Act / Obamacare, Airbnb, altcoin, Amazon Mechanical Turk, back-to-the-land, basic income, Berlin Wall, Bernie Sanders, bitcoin, blockchain, Brewster Kahle, Burning Man, Capital in the Twenty-First Century by Thomas Piketty, carbon footprint, Clayton Christensen, collaborative economy, collective bargaining, Community Supported Agriculture, corporate governance, creative destruction, crowdsourcing, cryptocurrency, Debian, disruptive innovation, do-ocracy, Donald Knuth, Donald Trump, Edward Snowden, Elon Musk, Ethereum, ethereum blockchain, Food sovereignty, four colour theorem, future of work, gig economy, Google bus, hydraulic fracturing, Internet Archive, Jeff Bezos, jimmy wales, joint-stock company, Joseph Schumpeter, Julian Assange, Kickstarter, Lyft, M-Pesa, Marc Andreessen, Mark Zuckerberg, Marshall McLuhan, mass immigration, means of production, multi-sided market, new economy, offshore financial centre, old-boy network, Peter H. Diamandis: Planetary Resources, post-work, precariat, premature optimization, pre–internet, profit motive, race to the bottom, Richard Florida, Richard Stallman, ride hailing / ride sharing, Sam Altman, Satoshi Nakamoto, self-driving car, shareholder value, sharing economy, Silicon Valley, Slavoj Žižek, smart contracts, Steve Jobs, Steve Wozniak, Stewart Brand, transaction costs, Turing test, Uber and Lyft, uber lyft, underbanked, undersea cable, universal basic income, Upton Sinclair, Vanguard fund, white flight, Whole Earth Catalog, WikiLeaks, women in the workforce, working poor, Y Combinator, Y2K, Zipcar

Capitalism’s creative destruction may have ravaged our communities for centuries with salvos of individualism, competition, and mistrust, but now it was ready to sell the benefits of community back to us on our smartphones. Without owning any guestrooms of its own, Airbnb was by then more valuable than Hyatt; Zipcar, which rents cars by the hour, had been bought by the international car-rental company Avis Budget. The sharing economy was also changing the way at least some people worked. Online labor brokers such as Amazon’s Mechanical Turk enticed hundreds of thousands of people to take up digital piecework—data entry, transcribing audio, running errands—without expectation of paid leave, health insurance, or even a minimum wage. But it was also alluringly permissionless—no application process, no fixed hours, no managers. Compared to the rest of the global economy, these companies remained small potatoes, but they seemed like portents of a shift that we’d soon be taking for granted before we had the chance to question it.

Because of this—because of us—such platform companies can be among the most valuable in the world with only tens of thousands of formal employees, rather than the hundreds of thousands that a major car manufacturer commands, or Walmart’s millions.13 In between the aristocratic employees and the gleaning peasant users, platforms hire legions of online freelancers for piecework tasks. These people are the leading edge of a growing workforce that is permanently part-time, gig-to-gig—part empowered freelancer, part exile from the rights and benefits that once accompanied employment.14 Their offline lives, too, can start to feel like a kind of piecework. Rochelle LaPlante, once a social worker, began a second career on Amazon’s Mechanical Turk platform in 2012, doing tasks to help support her family, such as moderating offensive images and taking academic surveys. With this came new habits of mind. She told me, “You go to the grocery store and see a candy bar, and you think, Is that worth two surveys?” The piecework mentality is spreading, with little legal restraint, from Amazon’s newer Flex delivery platform to countless other contenders beckoning an underemployed workforce into ephemeral gigs.


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 Mechanical Turk, Andrew Keen, business cycle, 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, moral panic, Network effects, new economy, Nicholas Carr, PageRank, peer-to-peer, 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

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). Amazon’s Mechanical Turk has gone so far as to provide a generalized platform for harnessing people to do tasks that are difficult for computers to perform on their own. But is this really what we mean by collective intelligence? Isn’t one definition of intelligence, after all, that characteristic that allows an organism to learn from and respond to its environment? (Please note that we’re leaving aside entirely the question of self-awareness.

Another striking story we’ve recently heard about a real-time feedback loop is the Houdini system used by the Obama campaign to remove voters from the Get Out the Vote calling list as soon as they had actually voted. Poll watchers in key districts reported in as they saw names crossed off the voter lists; these were then made to “disappear” from the calling lists that were being provided to volunteers. (Hence the name Houdini.) Houdini is Amazon’s Mechanical Turk writ large: one group of volunteers acting as sensors, multiple real-time data queues being synchronized and used to affect the instructions for another group of volunteers being used as actuators in that same system. Businesses must learn to harness real-time data as key signals that inform a far more efficient feedback loop for product development, customer service, and resource allocation. >>> in conclusion: the stuff that matters All of this is in many ways a preamble to what may be the most important part of the Web Squared opportunity.


pages: 401 words: 109,892

The Great Reversal: How America Gave Up on Free Markets by Thomas Philippon

airline deregulation, Amazon Mechanical Turk, Amazon Web Services, Andrei Shleifer, barriers to entry, bitcoin, blockchain, business cycle, business process, buy and hold, Carmen Reinhart, carried interest, central bank independence, commoditize, crack epidemic, cross-subsidies, disruptive innovation, Donald Trump, Erik Brynjolfsson, eurozone crisis, financial deregulation, financial innovation, financial intermediation, gig economy, income inequality, income per capita, index fund, intangible asset, inventory management, Jean Tirole, Jeff Bezos, Kenneth Rogoff, labor-force participation, law of one price, liquidity trap, low cost airline, manufacturing employment, Mark Zuckerberg, market bubble, minimum wage unemployment, money market fund, moral hazard, natural language processing, Network effects, new economy, offshore financial centre, Pareto efficiency, patent troll, Paul Samuelson, price discrimination, profit maximization, purchasing power parity, QWERTY keyboard, rent-seeking, ride hailing / ride sharing, risk-adjusted returns, Robert Bork, Robert Gordon, Ronald Reagan, Second Machine Age, self-driving car, Silicon Valley, Snapchat, spinning jenny, statistical model, Steve Jobs, supply-chain management, Telecommunications Act of 1996, The Chicago School, the payments system, The Rise and Fall of American Growth, The Wealth of Nations by Adam Smith, too big to fail, total factor productivity, transaction costs, Travis Kalanick, Vilfredo Pareto, zero-sum game

In Box 2.2 we showed that national concentration measures can differ from local concentration measures and give a misleading picture of the economy. You might think that local labor market concentration matters less today because of online labor markets. Arindrajit Dube, Jeff Jacobs, Suresh Naidu, and Siddharth Suri (2018) study exactly this issue. They examine one of the largest on-demand labor platforms, Amazon Mechanical Turk. Online platforms make it easier to search for a job, and one might have conjectured that they would lead to near-perfect competition. But the authors find a surprisingly high degree of market power, even in this large and diverse spot-labor market, suggesting that much of the surplus created by this online labor market platform is captured by employers. Restricted Contracts We have already seen how restrictive contracts are used by large hospitals to reduce competition in the health-care market.


pages: 691 words: 203,236

Whiteshift: Populism, Immigration and the Future of White Majorities by Eric Kaufmann

4chan, affirmative action, Amazon Mechanical Turk, anti-communist, anti-globalists, augmented reality, battle of ideas, Berlin Wall, Bernie Sanders, Boris Johnson, British Empire, centre right, Chelsea Manning, cognitive dissonance, complexity theory, corporate governance, correlation does not imply causation, crowdsourcing, Daniel Kahneman / Amos Tversky, David Brooks, deindustrialization, demographic transition, Donald Trump, Elon Musk, en.wikipedia.org, facts on the ground, failed state, Fall of the Berlin Wall, first-past-the-post, Francis Fukuyama: the end of history, Haight Ashbury, illegal immigration, immigration reform, imperial preference, income inequality, knowledge economy, knowledge worker, liberal capitalism, longitudinal study, Lyft, mass immigration, meta analysis, meta-analysis, moral panic, Nate Silver, New Urbanism, Norman Mailer, open borders, phenotype, postnationalism / post nation state, Ralph Waldo Emerson, Republic of Letters, Ronald Reagan, Scientific racism, Silicon Valley, statistical model, Steven Pinker, the built environment, the scientific method, The Wisdom of Crowds, transcontinental railway, twin studies, uber lyft, upwardly mobile, urban sprawl, Washington Consensus, white flight, working-age population, World Values Survey, young professional

I take Beane’s approach, trying to stick wherever possible to multivariate models based on representative surveys of individuals. Data doesn’t have to be quantitative to be valid – it might consist of large numbers of interviews, or accounts based on historical documents – but, in order to make causal claims, information needs to be as representative as possible. Where I don’t have large-scale representative data I run small opt-in surveys on Amazon’s Mechanical Turk (MTurk) or Prolific Academic, which aren’t too expensive, contain enough cases to compare between groups and are widely used by academics. These aren’t as good as mass surveys but are better than anecdotes and impressions. There isn’t the space in these pages to present everything, so I encourage you to visit this book’s companion website.8 We hear a lot about populism, and some analysts encompass its left, right, Western, Eastern and non-European variants.9 I’m less ambitious.

All of which may reflect the historic blending of white icons with national imagery symbolized in monuments like Mount Rushmore or on the American dollar. Not only this, but even within white America, despite all the melting, the WASP remains the all-American archetype. In 1982, a survey asked Americans to rate the contributions of ethnic groups and discovered that the English were highest ranked, followed by the Irish, Jews and Germans, with non-European groups lower down.62 In a convenience sample across three surveys on Amazon Mechanical Turk (MTurk) between 19 March and 1 April 2017, I asked 467 Americans, ‘All surnames are equally American, but if someone from another country asked you what a characteristic American surname was, which of the following would you choose?’ Answers were (rotated): Browning, Graziano, Hernandez, Schultz and Wong. Eighty-one per cent of those who gave a response chose Browning, the Anglo surname, including 86 per cent of Clinton voters, 78 per cent of Trump voters, 86 per cent of African-Americans, 85 per cent of Hispanics and 80 per cent of whites.


pages: 179 words: 43,441

The Fourth Industrial Revolution by Klaus Schwab

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, commoditize, conceptual framework, continuous integration, crowdsourcing, digital twin, disintermediation, disruptive innovation, 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, mass immigration, 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, Sam Altman, 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, supercomputer in your pocket, TaskRabbit, The Future of Employment, The Spirit Level, total factor productivity, transaction costs, Uber and Lyft, uber lyft, Watson beat the top human players on Jeopardy!, WikiLeaks, winner-take-all economy, women in the workforce, working-age population, Y Combinator, Zipcar

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.


pages: 525 words: 116,295

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

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, drone strike, 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, John Markoff, Julian Assange, Khan Academy, Kickstarter, knowledge economy, Law of Accelerating Returns, market fundamentalism, means of production, MITM: man-in-the-middle, mobile money, mutually assured destruction, Naomi Klein, Nelson Mandela, offshore financial centre, Parag Khanna, peer-to-peer, peer-to-peer lending, personalized medicine, Peter Singer: altruism, Ray Kurzweil, RFID, Robert Bork, 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

Skilled young adults in Uruguay will find themselves competing for certain types of jobs against their counterparts in Orange County. Of course, just as not all jobs can or will be automated in the future, not every job can be conducted from a distance—but more can than you might think. And for those living on a few dollars per day, there will be endless opportunities to increase their earnings. In fact, Amazon Mechanical Turk, which is a digital task-distribution platform, offers a present-day example of a company outsourcing small tasks that can be performed for a few cents by anyone with an Internet connection. As the quality of virtual interactions continues to improve, a range of vocations can expand the platform’s client base; you might retain a lawyer from one continent and use a Realtor from another. Globalization’s critics will decry this erosion of local monopolies, but it should be embraced, because this is how our societies will move forward and continue to innovate.


pages: 254 words: 79,052

Evil by Design: Interaction Design to Lead Us Into Temptation by Chris Nodder

4chan, affirmative action, Amazon Mechanical Turk, cognitive dissonance, crowdsourcing, Daniel Kahneman / Amos Tversky, Donald Trump, en.wikipedia.org, endowment effect, game design, haute couture, jimmy wales, Jony Ive, Kickstarter, late fees, loss aversion, Mark Zuckerberg, meta analysis, meta-analysis, Milgram experiment, Netflix Prize, Nick Leeson, Occupy movement, pets.com, price anchoring, recommendation engine, Rory Sutherland, Silicon Valley, Stanford prison experiment, stealth mode startup, Steve Jobs, telemarketer, Tim Cook: Apple, trickle-down economics, upwardly mobile

Increase the perceived value of the reward by making it harder to achieve, but keep it sufficiently attainable so that the right number of customers will act. Use language such as “winning” or “award” rather than “coupon” to make it clear that effort was involved in attaining the prize. Consider a small reward rather than a big one Customers will be forced to create justifications, which increase the perceived value of the reward. Amazon.com’s Mechanical Turk is an online marketplace where individuals get paid to perform small tasks that computers aren’t good at, such as making preference choices, composing descriptive sentences, searching for an item in an image, transcribing audio, or extracting meaning from phrases. These tasks are called Human Intelligence Tasks or HITs. Anyone can set up a HIT, using Amazon.com’s platform to advertise and host the tasks, and anyone can work on HITs; although, some require workers to take a simple test first, or to meet certain demographic criteria.

That is just slightly more than half the federal minimum wage. But despite this low payout, providers (who tend to refer to themselves as Turkers) keep coming back. One commenter, posting on Turkernation.com says, “I am spending way too much time on turking, kinda like when I used to play WoW. Do you guys find it addictive? The payout is like a score, and as you get qualifications, it's like getting levels. It's like I'm playing a game.” Amazon.com’s Mechanical Turk—in this HIT, you’ll earn six cents for checking the classification of a set of products on the site. Why do people commit so much time to something that—even for experienced Turkers—pays out so little? For some people, there are good reasons: unemployment, ability to work from home in micro-shifts between other tasks such as child minding, or the ability to work from work—either students during dull lectures, or others at their regular workplace using their work Internet access.


pages: 422 words: 131,666

Life Inc.: How the World Became a Corporation and How to Take It Back by Douglas Rushkoff

addicted to oil, affirmative action, Amazon Mechanical Turk, anti-globalists, banks create money, big-box store, Bretton Woods, car-free, Charles Lindbergh, colonial exploitation, Community Supported Agriculture, complexity theory, computer age, corporate governance, credit crunch, currency manipulation / currency intervention, David Ricardo: comparative advantage, death of newspapers, don't be evil, Donald Trump, double entry bookkeeping, easy for humans, difficult for computers, financial innovation, Firefox, full employment, global village, Google Earth, greed is good, Howard Rheingold, income per capita, invention of the printing press, invisible hand, Jane Jacobs, John Nash: game theory, joint-stock company, Kevin Kelly, Kickstarter, laissez-faire capitalism, loss aversion, market bubble, market design, Marshall McLuhan, Milgram experiment, moral hazard, mutually assured destruction, Naomi Klein, negative equity, new economy, New Urbanism, Norbert Wiener, peak oil, peer-to-peer, place-making, placebo effect, Ponzi scheme, price mechanism, price stability, principal–agent problem, private military company, profit maximization, profit motive, race to the bottom, RAND corporation, rent-seeking, RFID, road to serfdom, Ronald Reagan, short selling, Silicon Valley, Simon Kuznets, social software, Steve Jobs, Telecommunications Act of 1996, telemarketer, The Wealth of Nations by Adam Smith, Thomas L Friedman, too big to fail, trade route, trickle-down economics, union organizing, urban decay, urban planning, urban renewal, Vannevar Bush, Victor Gruen, white flight, working poor, Works Progress Administration, Y2K, young professional, zero-sum game

A central-office computer monitors exactly who is where and when, opening doors for those who have clearance. While implantation isn’t yet mandatory for existing laborers, the additional and convenient access to sensitive materials it affords makes voluntary implantation a plus for worker recognition and advancement. Increasingly, we find ourselves working on behalf of our computers rather than the other way around. The Amazon Mechanical Turks program gives people the opportunity to work as assistants to computers. Earning pennies per task, users perform hundreds or thousands of routine operations for corporate computers that don’t want to waste their cycles. There are credits available for everything from finding the address numbers in photos of houses (three cents a pop) to matching Web-page URLs with the product that is supposed to appear on them (a whopping nickel each).


pages: 190 words: 53,409

Success and Luck: Good Fortune and the Myth of Meritocracy by Robert H. Frank

2013 Report for America's Infrastructure - American Society of Civil Engineers - 19 March 2013, Amazon Mechanical Turk, American Society of Civil Engineers: Report Card, attribution theory, availability heuristic, Branko Milanovic, Capital in the Twenty-First Century by Thomas Piketty, carried interest, Daniel Kahneman / Amos Tversky, David Brooks, deliberate practice, en.wikipedia.org, endowment effect, experimental subject, framing effect, full employment, hindsight bias, If something cannot go on forever, it will stop - Herbert Stein's Law, income inequality, invisible hand, labor-force participation, lake wobegon effect, loss aversion, minimum wage unemployment, Network effects, Paul Samuelson, Report Card for America’s Infrastructure, Richard Thaler, Rod Stewart played at Stephen Schwarzman birthday party, Ronald Reagan, Rory Sutherland, selection bias, side project, sovereign wealth fund, Steve Jobs, The Wealth of Nations by Adam Smith, Tim Cook: Apple, ultimatum game, Vincenzo Peruggia: Mona Lisa, winner-take-all economy

Falsely believing themselves to be more skillful apparently induced a powerful sense of entitlement to claim the lion’s share, while falsely believing themselves to be less skillful had much less of an effect. My very able research assistant Yuezhou Huo designed a simple survey that sheds additional light on how focusing on the importance of external factors can affect people’s willingness to contribute to the common good. She began by asking subjects recruited online from Amazon’s Mechanical Turk worker pool7 to recall a good thing that had recently happened to them. She then asked one group to list external factors beyond their control that contributed to the event, a second group to list personal qualities or things they had done personally, and a control group to simply list reasons that the good thing had happened. Subjects in each group were paid 50 cents for signing up and promised an additional $1 for completing the experiment.


Beautiful Data: The Stories Behind Elegant Data Solutions by Toby Segaran, Jeff Hammerbacher

23andMe, airport security, Amazon Mechanical Turk, bioinformatics, Black Swan, business intelligence, card file, cloud computing, computer vision, correlation coefficient, correlation does not imply causation, crowdsourcing, Daniel Kahneman / Amos Tversky, DARPA: Urban Challenge, data acquisition, database schema, double helix, en.wikipedia.org, epigenetics, fault tolerance, Firefox, Hans Rosling, housing crisis, information retrieval, lake wobegon effect, longitudinal study, Mars Rover, natural language processing, openstreetmap, prediction markets, profit motive, semantic web, sentiment analysis, Simon Singh, social graph, SPARQL, speech recognition, statistical model, supply-chain management, text mining, Vernor Vinge, web application

Motivation Finally, although we’ve talked about concerns over how to make it possible for respondents to use the form, as well as the problems of getting them to trust us enough to keep participating, avoiding scaring them off with a lot of questions, and making sure we didn’t subconsciously influence their answers, we haven’t mentioned perhaps the most important part of any survey: why should the person want to participate at all? For this type of research survey, there is no profit motive to participate, unlike online forums such as Amazon’s Mechanical Turk, in which users complete tasks in their spare time for a few dollars or cents per task. But when there is no explicit profit to be made, how do you convince a person to take the time to answer your questions? Designing Our Solution We’ve talked about some of the pitfalls inherent in a data-collecting project; in the next few sections, we discuss the nuts and bolts of our design, including typography, web browser compatibility, and dynamic form elements.

Our models can be refined in part by attempting to quantify subjective features. When an individual decides whether to lend money to a member of the network, the lender (unlike a bank) takes into account a number of “softer” factors: the borrower’s statement of purpose, the accompanying image, spelling, grammar, and other profile information. To incorporate some of these features into our models, I used human workers (from Amazon’s Mechanical Turk) to code images from Prosper.com members, first for content—whether the image depicts a person, a family, a vehicle, etc.—and then for a “trustworthiness” score: that is, for the answer to the question, “Would you lend money to this person?” 216 CHAPTER THIRTEEN Download at Boykma.Com But the models still fell short: social factors play into loan dynamics in unexpected ways. Contrary to our assumptions, lending decisions aren’t made independently.


pages: 332 words: 97,325

The Launch Pad: Inside Y Combinator, Silicon Valley's Most Exclusive School for Startups by Randall Stross

affirmative action, Airbnb, AltaVista, always be closing, Amazon Mechanical Turk, Amazon Web Services, barriers to entry, Ben Horowitz, Burning Man, business cycle, California gold rush, call centre, cloud computing, crowdsourcing, don't be evil, Elon Musk, high net worth, index fund, inventory management, John Markoff, Justin.tv, Lean Startup, Marc Andreessen, Mark Zuckerberg, medical residency, Menlo Park, Minecraft, minimum viable product, Paul Buchheit, Paul Graham, Peter Thiel, QR code, Richard Feynman, Richard Florida, ride hailing / ride sharing, Sam Altman, Sand Hill Road, side project, Silicon Valley, Silicon Valley startup, Skype, social graph, software is eating the world, South of Market, San Francisco, speech recognition, Stanford marshmallow experiment, Startup school, stealth mode startup, Steve Jobs, Steve Wozniak, Steven Levy, TaskRabbit, transaction costs, Y Combinator

“If you have documents you want to digitize—for example, you take notes in your notebook—that you’d like to have as a PDF, you upload it to our Web site, we’ll chop it up into small pieces, send it to our workers, they’ll digitize the words, send it back to us. We give you a PDF.” “Got it. How did you guys come up with the idea?” Narula explains that they had originally thought they could develop software that would “scrape” the jobs listed on Amazon’s Mechanical Turk service and then have the work done on the cell phones of workers in India. “But once we did our research, we understood it won’t scale,” he says. “How do you guys all know each other?” “The four of us were Berkeley graduate students,” says Kulkarni. “It’s spun out of research that we were doing as part of our graduate work.” “Are you live?” “We’re live with workers. Done about fifty thousand jobs so far,” he says, referring to a pilot project with one corporate client.

Abbott, Ryan, 46, 171, 174, 177, 180, 181 Adidas, 234 Adpop Media, 46–47, 122–23, 129 AeroFS, 231 Airbnb, 4, 43, 88, 95 AirTV, 103–4 circumvention, 177–78 investors seeking next, 207 Kutcher, Ashton, 265n1 marketplace, 179 Sift Science, 210 Vidyard, 103–5, 120 Aisle50, 51–52, 191, 208–9, 223, 233 Akamai, 101 Albertsons, 209 Allen, Paul, 16 AlphaLab, 41 Altair BASIC, 11, 68 AltaVista, 204 Altman, Sam, 220 on buzzwords, 18–19 CampusCred, 111–14 interviewing finalists, 11, 21 Rap Genius, 196–202 Science Exchange, 173 Sift Science, 75–76 speaking style, 114, 115, 196 YC partner, 63, 150 Amarasiriwardena, Thushan, 127–28 Amazon, 126 Interview Street, 213 Mechanical Turk, 89, 90 movie rentals, 106 web services, 32, 101, 131, 132 Andreessen Horowitz, 4, 66, 230 Andreessen, Marc, 1–2, 4, 215, 239 Android, 17, 122, 147, 212 NFC, 157, 158 speech recognition, 210 Andrzejewski, Alexa, 54 angel investors, 28, 86–87, 189–90 AnyAsq, 166–67 Anybots, 12, 27, 40, 63 AOL, 124, 126 AppJet, 64, 204 Apple, 69 App Store, 100, 127 cofounders, 161 headquarters, 251n1 iOS devices, 122, 127–28, 142, 147, 172, 187, 209, 212 Sequoia Capital, 3 Snapjoy, 187 Arrington, Michael, 48–49 The Art of Ass-Kicking blog (Shen), 9 Artix, 25, 27, 29 Ask Me Anything, 166 Auburn University, 29 Auctomatic, 64, 66, 159, 204 Austin, TX, 42 Australia, 17, 238 Ballinger, Brandon, 70–76, 121, 134–38, 209–10 Barbie, 53 Bard College at Simon’s Rock, 52 Beatles, 200 Bechtolsheim, Andy, 86 Bellingham, WA, 101 Benchmark Capital, 5 Berkeley (UC) CampusCred, 20, 111 graduates of, 9, 68, 135, 164 Information, School of, 89, 90 newspaper, 136 students, 20, 52–53, 135 Venture Lab Competition, 53 women in computer science, 53 Bernstam, Tikhon, 122, 166, 185–86, 212, 228, 230–31 Bernstein, Mikael, 213–14 Betaspring, 42 Bible, 127, 197, 199, 200 Bill of Rights, 197 Bing Nursery School, 52 Birmingham, AL, 29, 33, 51, 203, 223 BizPress, 125, 147–48, 192 BlackBerry, 157, 184 Blackwell, Trevor Anybots, 27 interviewing finalists, 10, 11–12, 32–33 Kiko, 16 Viaweb, 25 YC partner, 27, 40, 57, 63 Blank, Steve, 77 Blogger, 57 Blomfield, Tom, 191 Bloomberg, Michael, 227 Bloomberg TV, 55 Blurb.com, 12 BMW, 165 Books On Campus, 164 BoomStartup, 42 Boso, 57–58, 60 Boston, MA, 56 Boston University, 112 Boucher, Ross, 64 Boulder, CO, 41, 43, 53, 130 Box, 54 Boyd, E.


pages: 523 words: 61,179

Human + Machine: Reimagining Work in the Age of AI by Paul R. Daugherty, H. James Wilson

3D printing, AI winter, algorithmic trading, Amazon Mechanical Turk, augmented reality, autonomous vehicles, blockchain, business process, call centre, carbon footprint, cloud computing, computer vision, correlation does not imply causation, crowdsourcing, digital twin, disintermediation, Douglas Hofstadter, en.wikipedia.org, Erik Brynjolfsson, friendly AI, future of work, industrial robot, Internet of things, inventory management, iterative process, Jeff Bezos, job automation, job satisfaction, knowledge worker, Lyft, natural language processing, personalized medicine, precision agriculture, Ray Kurzweil, recommendation engine, RFID, ride hailing / ride sharing, risk tolerance, Rodney Brooks, Second Machine Age, self-driving car, sensor fusion, sentiment analysis, Shoshana Zuboff, Silicon Valley, software as a service, speech recognition, telepresence, telepresence robot, text mining, the scientific method, uber lyft

These same technologists (76 percent) suggest that the top solution is to use some sort of visual output that provides analytics and a dashboard with other metrics.12 It’s a simple solution that can reduce opacity in the system—and keep humans firmly in the loop. Here, the role of the explainer is key. Even if the entire mind of an AI system can’t be known, some insights into its inner workings can be very beneficial. Explainers should understand both what’s useful for people to see in a visualization and what’s important for the system to share. Minimize “Moral Crumple Zones” For services like Uber, Lyft, and Amazon’s Mechanical Turk, AI-based software is augmenting some management roles: it doles out tasks, gives feedback and ratings, and helps people track progress toward goals. AI-enhanced management is a necessary innovation if these companies’ business models are to scale and employ hundreds of thousands of people worldwide. But while management can offload certain activities, it can’t offload underlying responsibility for how they are administered.


pages: 1,331 words: 163,200

Hands-On Machine Learning With Scikit-Learn and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems by Aurélien Géron

Amazon Mechanical Turk, Anton Chekhov, combinatorial explosion, computer vision, constrained optimization, correlation coefficient, crowdsourcing, don't repeat yourself, Elon Musk, en.wikipedia.org, friendly AI, ImageNet competition, information retrieval, iterative process, John von Neumann, Kickstarter, natural language processing, Netflix Prize, NP-complete, optical character recognition, P = NP, p-value, pattern recognition, pull request, recommendation engine, self-driving car, sentiment analysis, SpamAssassin, speech recognition, stochastic process

This is important to catch not only sudden breakage, but also performance degradation. This is quite common because models tend to “rot” as data evolves over time, unless the models are regularly trained on fresh data. Evaluating your system’s performance will require sampling the system’s predictions and evaluating them. This will generally require a human analysis. These analysts may be field experts, or workers on a crowdsourcing platform (such as Amazon Mechanical Turk or CrowdFlower). Either way, you need to plug the human evaluation pipeline into your system. You should also make sure you evaluate the system’s input data quality. Sometimes performance will degrade slightly because of a poor quality signal (e.g., a malfunctioning sensor sending random values, or another team’s output becoming stale), but it may take a while before your system’s performance degrades enough to trigger an alert.


pages: 284 words: 79,265

The Half-Life of Facts: Why Everything We Know Has an Expiration Date by Samuel Arbesman

Albert Einstein, Alfred Russel Wallace, Amazon Mechanical Turk, Andrew Wiles, bioinformatics, British Empire, Cesare Marchetti: Marchetti’s constant, Chelsea Manning, Clayton Christensen, cognitive bias, cognitive dissonance, conceptual framework, David Brooks, demographic transition, double entry bookkeeping, double helix, Galaxy Zoo, guest worker program, Gödel, Escher, Bach, Ignaz Semmelweis: hand washing, index fund, invention of movable type, Isaac Newton, John Harrison: Longitude, Kevin Kelly, life extension, Marc Andreessen, meta analysis, meta-analysis, Milgram experiment, Nicholas Carr, P = NP, p-value, Paul Erdős, Pluto: dwarf planet, publication bias, randomized controlled trial, Richard Feynman, Rodney Brooks, scientific worldview, social graph, social web, text mining, the scientific method, Thomas Kuhn: the structure of scientific revolutions, Thomas Malthus, Tyler Cowen: Great Stagnation

In courts, intent is what matters, and not unconscious muscle memory, so if you do this on a legal document, you’re generally fine. I decided to conduct a simple experiment to actually get a handle on people’s factual inertia. To do this, I used a Web site created by Amazon called Mechanical Turk. The label Mechanical Turk derives from a well-known hoax from the eighteenth and nineteenth centuries. The Turk was a complex device that was displayed all throughout Europe. While appearing to be a chess-playing automaton, the Turk actually had a person in a hidden compartment, controlling the machine. In homage to this, Amazon named its online labor market—a clearinghouse for simple tasks humans can easily perform but computers cannot—Mechanical Turk. These tasks include things like labeling photographs when they are posted, and Turkers, as the laborers are called, will often solve these problems for pennies.


pages: 500 words: 145,005

Misbehaving: The Making of Behavioral Economics by Richard H. Thaler

"Robert Solow", 3Com Palm IPO, Albert Einstein, Alvin Roth, Amazon Mechanical Turk, Andrei Shleifer, Apple's 1984 Super Bowl advert, Atul Gawande, Berlin Wall, Bernie Madoff, Black-Scholes formula, business cycle, capital asset pricing model, Cass Sunstein, Checklist Manifesto, choice architecture, clean water, cognitive dissonance, conceptual framework, constrained optimization, Daniel Kahneman / Amos Tversky, delayed gratification, diversification, diversified portfolio, Edward Glaeser, endowment effect, equity premium, Eugene Fama: efficient market hypothesis, experimental economics, Fall of the Berlin Wall, George Akerlof, hindsight bias, Home mortgage interest deduction, impulse control, index fund, information asymmetry, invisible hand, Jean Tirole, John Nash: game theory, John von Neumann, Kenneth Arrow, Kickstarter, late fees, law of one price, libertarian paternalism, Long Term Capital Management, loss aversion, market clearing, Mason jar, mental accounting, meta analysis, meta-analysis, money market fund, More Guns, Less Crime, mortgage debt, Myron Scholes, Nash equilibrium, Nate Silver, New Journalism, nudge unit, Paul Samuelson, payday loans, Ponzi scheme, presumed consent, pre–internet, principal–agent problem, prisoner's dilemma, profit maximization, random walk, randomized controlled trial, Richard Thaler, Robert Shiller, Robert Shiller, Ronald Coase, Silicon Valley, South Sea Bubble, Stanford marshmallow experiment, statistical model, Steve Jobs, Supply of New York City Cabdrivers, technology bubble, The Chicago School, The Myth of the Rational Market, The Signal and the Noise by Nate Silver, The Wealth of Nations by Adam Smith, Thomas Kuhn: the structure of scientific revolutions, transaction costs, ultimatum game, Vilfredo Pareto, Walter Mischel, zero-sum game

Apparently there was a program that was training the unemployed to be telephone interviewers, whatever that entails, and they needed questions for the trainees to ask. If we faxed a bunch of questions each Monday morning, they would fax us back the responses Thursday night. That gave us Friday and the weekend to figure out what we had learned from the week’s questions and to write some new ones for the following week. Today this sort of research can be done online using services like Amazon’s “Mechanical Turk,” but back then weekly access to a random sample of a few hundred residents of Ontario (and later British Columbia) was an incredible luxury. We were able to try out lots of ideas, get quick feedback, and learn in the best possible way: theory-driven intuition tested by trial and error. Here is an example of the kind of question we were asking: A hardware store has been selling snow shovels for $15.


pages: 685 words: 203,949

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

airport security, Albert Einstein, Amazon Mechanical Turk, Anton Chekhov, Bayesian statistics, 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, longitudinal study, meta analysis, meta-analysis, more computing power than Apollo, Network effects, new economy, Nicholas Carr, optical character recognition, Pareto efficiency, pattern recognition, phenotype, placebo effect, pre–internet, profit motive, randomized controlled trial, Rubik’s Cube, shared worldview, Skype, Snapchat, social intelligence, statistical model, Steve Jobs, supply-chain management, the scientific method, The Wealth of Nations by Adam Smith, The Wisdom of Crowds, theory of mind, Thomas Bayes, Turing test, ultimatum game, zero-sum game

But reCAPTCHAs pair the unknown words with known words; they assume that if you solve the known word, you’re a human, and that your guess on the unknown word is reasonable. When several people agree on the unknown word, it’s considered solved and the information is incorporated into the scan. Amazon’s Mechanical Turk is typically used for tasks that computers aren’t particularly good at but humans would find repetitively dull or boring. A recent cognitive psychology experiment published in Science used Amazon’s Mechanical Turk to find experimental participants. Volunteers (who were paid three dollars each) had to read a story and then take a test that measured their levels of empathy. Empathy requires the ability to switch between different perspectives on the same situation or interaction. This requires using the brain’s daydreaming mode (the task-negative network), and it involves the prefrontal cortex, cingulate, and their connections to the temporoparietal junction.


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

airport security, Alfred Russel Wallace, Amazon Mechanical Turk, Berlin Wall, Black Swan, book scanning, Cass Sunstein, commoditize, 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, Johannes Kepler, 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, 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

“DARPA would have you believe that it’s the brilliance of modern-day social networks that led an MIT-based team to win its red balloon challenge this weekend” when it was just that MIT offered to split the money.16 That objection misses the point: Without the network, the offer of money would have gone nowhere. Indeed, some of the most powerful ways to crowdsource expertise involve paying people. Amazon’s Mechanical Turk, launched in 2005, enables vast numbers of people to work on small, distributed tasks for a small amount of money per transaction. (It’s named after an eighteenth-century chess-playing “machine” that beat almost all comers, including Napoleon and Ben Franklin, by concealing a human chess expert within it.) Businesses have used Mechanical Turk to get thousands of online images labeled, find duplications in yellow-page listings, and rate the relevancy of a search engine’s results.


pages: 389 words: 87,758

No Ordinary Disruption: The Four Global Forces Breaking All the Trends by Richard Dobbs, James Manyika

2013 Report for America's Infrastructure - American Society of Civil Engineers - 19 March 2013, access to a mobile phone, additive manufacturing, Airbnb, Amazon Mechanical Turk, American Society of Civil Engineers: Report Card, autonomous vehicles, Bakken shale, barriers to entry, business cycle, business intelligence, Carmen Reinhart, central bank independence, cloud computing, corporate governance, creative destruction, crowdsourcing, demographic dividend, deskilling, disintermediation, disruptive innovation, distributed generation, Erik Brynjolfsson, financial innovation, first square of the chessboard, first square of the chessboard / second half of the chessboard, Gini coefficient, global supply chain, global village, hydraulic fracturing, illegal immigration, income inequality, index fund, industrial robot, intangible asset, Intergovernmental Panel on Climate Change (IPCC), Internet of things, inventory management, job automation, Just-in-time delivery, Kenneth Rogoff, Kickstarter, knowledge worker, labor-force participation, low skilled workers, Lyft, M-Pesa, mass immigration, megacity, mobile money, Mohammed Bouazizi, Network effects, new economy, New Urbanism, oil shale / tar sands, oil shock, old age dependency ratio, openstreetmap, peer-to-peer lending, pension reform, private sector deleveraging, purchasing power parity, quantitative easing, recommendation engine, Report Card for America’s Infrastructure, RFID, ride hailing / ride sharing, Second Machine Age, self-driving car, sharing economy, Silicon Valley, Silicon Valley startup, Skype, smart cities, Snapchat, sovereign wealth fund, spinning jenny, stem cell, Steve Jobs, supply-chain management, TaskRabbit, The Great Moderation, trade route, transaction costs, Travis Kalanick, uber lyft, urban sprawl, Watson beat the top human players on Jeopardy!, working-age population, Zipcar

In the United States, disaggregating primary care could reduce growth in health-care spending while opening up new jobs for people with less than a four-year college degree—if professional practice regulations can be updated to allow such innovation. This type of shift has already occurred in the legal profession. In the 2000s, jobs for paralegals and legal assistants grew at 2.5 times the rate that jobs for attorneys did, shifting the overall composition of employment in the sector. Disaggregation of more complex tasks can give rise to new businesses and recruiting models. Amazon’s Mechanical Turk is a website where businesses can find workers to do simple tasks such as writing product descriptions or identifying people in photographs. Positions requiring higher skills can be filled on platforms such as InnoCentive’s challenge platform and topcoder, where people compete for software development and digital asset creation work. While disaggregation can help companies improve productivity, cross training and resisting the temptation to overspecialize can add a further edge, given the pace of change in demand and supply of labor.


pages: 343 words: 91,080

Uberland: How Algorithms Are Rewriting the Rules of Work by Alex Rosenblat

"side hustle", Affordable Care Act / Obamacare, Airbnb, Amazon Mechanical Turk, autonomous vehicles, barriers to entry, basic income, big-box store, call centre, cashless society, Cass Sunstein, choice architecture, collaborative economy, collective bargaining, creative destruction, crowdsourcing, disruptive innovation, don't be evil, Donald Trump, en.wikipedia.org, future of work, gender pay gap, gig economy, Google Chrome, income inequality, information asymmetry, Jaron Lanier, job automation, job satisfaction, Lyft, marginal employment, Mark Zuckerberg, move fast and break things, Network effects, new economy, obamacare, performance metric, Peter Thiel, price discrimination, Ralph Waldo Emerson, regulatory arbitrage, ride hailing / ride sharing, self-driving car, sharing economy, Silicon Valley, Silicon Valley ideology, Skype, social software, stealth mode startup, Steve Jobs, strikebreaker, TaskRabbit, Tim Cook: Apple, transportation-network company, Travis Kalanick, Uber and Lyft, Uber for X, uber lyft, union organizing, universal basic income, urban planning, Wolfgang Streeck, Zipcar

Uber drivers are classified as independent contractors in the eyes of the law and termed “driver-partners” in Uber’s official lexicon: these categorizations imply a higher level of autonomy and equity in the company than they have in practice. The company positions drivers as “partners” with messages like “be your own boss and “get paid in fares for driving on your own schedule.” Other digital economy labor platforms, like Amazon’s Mechanical Turk, and sharing economy companies like TaskRabbit, call their workers, respectively, “Turkers” and “Taskers” or “Rabbits” and bill them as entrepreneurs or micropreneurs.46 This careful dance with terminology distances platform employers from the rules and norms of labor law.47 These new platform companies attempt to align themselves with a lineage of “cooperative commerce”48 or acts of mutual help and generosity like hitchhiking, carpooling, and couch surfing.


pages: 606 words: 87,358

The Great Convergence: Information Technology and the New Globalization by Richard Baldwin

"Robert Solow", 3D printing, additive manufacturing, Admiral Zheng, agricultural Revolution, air freight, Amazon Mechanical Turk, Berlin Wall, bilateral investment treaty, Branko Milanovic, buy low sell high, call centre, Columbian Exchange, commoditize, Commodity Super-Cycle, David Ricardo: comparative advantage, deindustrialization, domestication of the camel, Edward Glaeser, endogenous growth, Erik Brynjolfsson, financial intermediation, George Gilder, global supply chain, global value chain, Henri Poincaré, imperial preference, industrial cluster, industrial robot, intangible asset, invention of agriculture, invention of the telegraph, investor state dispute settlement, Isaac Newton, Islamic Golden Age, James Dyson, Kickstarter, knowledge economy, knowledge worker, Lao Tzu, low skilled workers, market fragmentation, mass immigration, Metcalfe’s law, New Economic Geography, out of africa, paper trading, Paul Samuelson, Pax Mongolica, profit motive, rent-seeking, reshoring, Richard Florida, rising living standards, Robert Metcalfe, Second Machine Age, Simon Kuznets, Skype, Snapchat, Stephen Hawking, telepresence, telerobotics, The Wealth of Nations by Adam Smith, trade liberalization, trade route, Washington Consensus

This would be nothing more than an amplification of what is already happening. “Microwork” or “micro-outsourcing” is the ability to get individuals to perform small, disjointed tasks as part of a larger project with all the work taking place over the Web. Virtual presence will make the fractionalization and offshoring much easier to coordinate. Think of it as micro-outsourcing on steroids; for example, something like Amazon’s Mechanical Turk but far more pervasive. Of course, the offshoring of simple, modular services is an old story. All sorts of back-office tasks have been offshored or outsourced already. This could go much further. Leading providers of services ranging from banking to legal advice pay large numbers of expensive people to sit in expensive buildings in expensive cities since in-person interactions matter.


pages: 369 words: 90,630

Mindwise: Why We Misunderstand What Others Think, Believe, Feel, and Want by Nicholas Epley

affirmative action, airport security, Amazon Mechanical Turk, Cass Sunstein, crowdsourcing, cuban missile crisis, drone strike, friendly fire, invisible hand, meta analysis, meta-analysis, Milgram experiment, payday loans, Peter Singer: altruism, pirate software, Richard Thaler, school choice, social intelligence, the scientific method, theory of mind

The next seven lines show the estimated amount of wealth inequality for a variety of different groups, all of whom underestimate the actual amount of inequality. The last seven lines show what these respondents thought was the ideal amount of inequality in the United States; all of them, by large margins, think a more equitable distribution would be more ideal. I thank Mike Norton for sending me these results. 4. I conducted this survey online in the fall of 2012, using Amazon’s Mechanical Turk. This is an online crowdsourcing site that coordinates the use of human intelligence for all sorts of tasks that computers are currently unable to perform. It also allows researchers to conduct survey experiments like this one with a reasonably representative sample of respondents. 5. Ashmore, R., and F. Del Boca (1981). Conceptual approaches to stereotypes and stereotyping. In D. Hamilton (ed.), Cognitive processes in stereotyping and intergroup behavior (pp. 1–35).


pages: 372 words: 89,876

The Connected Company by Dave Gray, Thomas Vander Wal

A Pattern Language, Albert Einstein, Amazon Mechanical Turk, Amazon Web Services, Atul Gawande, Berlin Wall, business cycle, business process, call centre, Clayton Christensen, commoditize, complexity theory, creative destruction, David Heinemeier Hansson, disruptive innovation, en.wikipedia.org, factory automation, Googley, index card, industrial cluster, interchangeable parts, inventory management, Jeff Bezos, John Markoff, Kevin Kelly, loose coupling, low cost airline, market design, minimum viable product, more computing power than Apollo, profit maximization, Richard Florida, Ruby on Rails, self-driving car, shareholder value, side project, Silicon Valley, skunkworks, software as a service, South of Market, San Francisco, Steve Jobs, Steven Levy, Stewart Brand, The Wealth of Nations by Adam Smith, Tony Hsieh, Toyota Production System, Vanguard fund, web application, WikiLeaks, Zipcar

Platforms are support structures that increase the effectiveness of a community. What is a Platform? A platform is a support structure that increases the effectiveness of a community. Some platforms are public. For example, a local farmers’ market or swap meet clusters sellers together so they can attract more buyers. Like local swap meets, eBay and Craigslist provide platforms for people to buy and sell used goods or unique items. Amazon’s Mechanical Turk provides a marketplace for buyers and sellers of human labor at a micro scale—tiny bits of work for tiny bits of money. The Internet is another public platform. So is the Global Positioning System (GPS) that allows you to track your location by satellite. Companies can provide platforms that are more restricted in their use. For example, platforms may be available only to employees.


pages: 484 words: 104,873

Rise of the Robots: Technology and the Threat of a Jobless Future by Martin Ford

"Robert Solow", 3D printing, additive manufacturing, Affordable Care Act / Obamacare, AI winter, algorithmic trading, Amazon Mechanical Turk, artificial general intelligence, assortative mating, autonomous vehicles, banking crisis, basic income, Baxter: Rethink Robotics, Bernie Madoff, Bill Joy: nanobots, business cycle, call centre, Capital in the Twenty-First Century by Thomas Piketty, Chris Urmson, Clayton Christensen, clean water, cloud computing, collateralized debt obligation, commoditize, computer age, creative destruction, debt deflation, deskilling, disruptive innovation, diversified portfolio, Erik Brynjolfsson, factory automation, financial innovation, Flash crash, Fractional reserve banking, Freestyle chess, full employment, Goldman Sachs: Vampire Squid, Gunnar Myrdal, High speed trading, income inequality, indoor plumbing, industrial robot, informal economy, iterative process, Jaron Lanier, job automation, John Markoff, John Maynard Keynes: technological unemployment, John von Neumann, Kenneth Arrow, Khan Academy, knowledge worker, labor-force participation, liquidity trap, low skilled workers, low-wage service sector, Lyft, manufacturing employment, Marc Andreessen, McJob, moral hazard, Narrative Science, Network effects, new economy, Nicholas Carr, Norbert Wiener, obamacare, optical character recognition, passive income, Paul Samuelson, performance metric, Peter Thiel, plutocrats, Plutocrats, post scarcity, precision agriculture, price mechanism, Ray Kurzweil, rent control, rent-seeking, reshoring, RFID, Richard Feynman, Rodney Brooks, Sam Peltzman, secular stagnation, self-driving car, Silicon Valley, Silicon Valley startup, single-payer health, software is eating the world, sovereign wealth fund, speech recognition, Spread Networks laid a new fibre optics cable between New York and Chicago, stealth mode startup, stem cell, Stephen Hawking, Steve Jobs, Steven Levy, Steven Pinker, strong AI, Stuxnet, technological singularity, telepresence, telepresence robot, The Bell Curve by Richard Herrnstein and Charles Murray, The Coming Technological Singularity, The Future of Employment, Thomas L Friedman, too big to fail, Tyler Cowen: Great Stagnation, uber lyft, union organizing, Vernor Vinge, very high income, Watson beat the top human players on Jeopardy!, women in the workforce

* In addition to his work in genetic programming, Koza is the inventor of the scratch-off lottery ticket and the originator of the “constitutional workaround” idea to elect US presidents by popular vote by having the states agree to award electoral-college votes based on the country’s overall popular-vote outcome. * If you find this type of work appealing but lack the requisite legal training, be sure to check out Amazon’sMechanical Turk” service, which offers many similar opportunities. “BinCam,” for example, places cameras in your garbage bin, tracks everything you throw away, and then automatically posts the record to social media. The idea is, apparently, to shame yourself into not wasting food and not forgetting to recycle. As we’ve seen, visual recognition (of types of garbage, in this case) remains a daunting challenge for computers, so people are employed to perform this task.

See artificial intelligence (AI) “AI winters,” 231 Alaska, annual dividend, 268 algorithms acceleration in development of, 71 automated trading, 56, 113–115 increasing efficiency of, 64 machine learning, 89, 93, 100–101, 107–115, 130–131 threat to jobs, xv, 85–86 alien invasion parable, 194–196, 240 “All Can Be Lost: The Risk of Putting Our Knowledge in the Hands of Machines” (Carr), 254 all-payer ceiling, 168–169 all-payer rates, 167–169 Amazon.com, 16–17, 76, 89 artificial intelligence and, 231 cloud computing and, 104–105, 107 delivery model, 190, 190n “Mechanical Turk” service, 125n AMD (Advanced Micro Devices), 70n American Airlines, 179 American Hospital Association, 168 American Motors, 76 Andreesen, Marc, 107 Android, 6, 21, 79, 121 Apple, Inc., 17, 20, 51, 92, 106–107, 279 Apple Watch, 160 apps, difficulty in monetizing, 79 Arai, Noriko, 127–128 Aramco, 68 Ariely, Dan, 47n Arrow, Kenneth, 162, 169 art, machines creating, 111–113 Artificial General Intelligence (AGI), 231–233 dark side of, 238–241 the Singularity and, 233–238 artificial intelligence (AI), xiv arms race and, 232, 239–240 in medicine, 147–153 narrow, 229–230 offshoring and, 118–119 warnings concerning dangers of, 229 See also Artificial General Intelligence (AGI); automation; information technology Artificial Intelligence Laboratory (Stanford University), 6 artificial neural networks, 90–92.


pages: 289

Hustle and Gig: Struggling and Surviving in the Sharing Economy by Alexandrea J. Ravenelle

"side hustle", active transport: walking or cycling, Affordable Care Act / Obamacare, Airbnb, Amazon Mechanical Turk, barriers to entry, basic income, Broken windows theory, call centre, Capital in the Twenty-First Century by Thomas Piketty, cashless society, Clayton Christensen, clean water, collaborative consumption, collective bargaining, creative destruction, crowdsourcing, disruptive innovation, Downton Abbey, East Village, Erik Brynjolfsson, full employment, future of work, gig economy, Howard Zinn, income inequality, informal economy, job automation, low skilled workers, Lyft, minimum wage unemployment, Mitch Kapor, Network effects, new economy, New Urbanism, obamacare, Panopticon Jeremy Bentham, passive income, peer-to-peer, peer-to-peer model, performance metric, precariat, rent control, ride hailing / ride sharing, Ronald Reagan, sharing economy, Silicon Valley, strikebreaker, TaskRabbit, telemarketer, the payments system, Tim Cook: Apple, transaction costs, Travis Kalanick, Triangle Shirtwaist Factory, Uber and Lyft, Uber for X, uber lyft, ubercab, universal basic income, Upton Sinclair, urban planning, very high income, white flight, working poor, Zipcar

Some have suggested that UberPeople.net, the discussion forum for drivers, is a lurking ground for Uber executives or at least monitored by Uber staff. Discussion threads have even been created to “expose Uber employees.”34 Most sharing economy services are a far cry from company towns where workers were paid in script and housed in units owned by the company. One notable exception to this was CrowdFlower, a online platform that allowed for data cleaning and was similar to Amazon’s Mechanical Turk. Although Mechanical Turk has been criticized for paying low wages, sometimes CrowdFlower didn’t even pay workers, instead giving them points for various online reward programs and videogame credits.35 While company towns were most common in the United States in the late 1800s, Uber’s recruiting playbook reaches back much farther. In 2013, Uber offered a partnership with Santander Bank that promised auto loans with a “low weekly payment” that would be “automatically deducted” from drivers’ Uber earnings.


pages: 396 words: 117,149

The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World by Pedro Domingos

Albert Einstein, Amazon Mechanical Turk, Arthur Eddington, basic income, Bayesian statistics, Benoit Mandelbrot, bioinformatics, Black Swan, Brownian motion, cellular automata, Claude Shannon: information theory, combinatorial explosion, computer vision, constrained optimization, correlation does not imply causation, creative destruction, crowdsourcing, Danny Hillis, data is the new oil, double helix, Douglas Hofstadter, Erik Brynjolfsson, experimental subject, Filter Bubble, future of work, global village, Google Glasses, Gödel, Escher, Bach, information retrieval, job automation, John Markoff, John Snow's cholera map, John von Neumann, Joseph Schumpeter, Kevin Kelly, lone genius, mandelbrot fractal, Mark Zuckerberg, Moneyball by Michael Lewis explains big data, Narrative Science, Nate Silver, natural language processing, Netflix Prize, Network effects, NP-complete, off grid, P = NP, PageRank, pattern recognition, phenotype, planetary scale, pre–internet, random walk, Ray Kurzweil, recommendation engine, Richard Feynman, scientific worldview, Second Machine Age, self-driving car, Silicon Valley, social intelligence, speech recognition, Stanford marshmallow experiment, statistical model, Stephen Hawking, Steven Levy, Steven Pinker, superintelligent machines, the scientific method, The Signal and the Noise by Nate Silver, theory of mind, Thomas Bayes, transaction costs, Turing machine, Turing test, Vernor Vinge, Watson beat the top human players on Jeopardy!, white flight, zero-sum game

And it’s the reason why social science research is such an uphill battle: if all you have is a sample of a hundred people, with a dozen measurements apiece, all you can model is some very narrow phenomenon. But even this narrow phenomenon does not exist in isolation; it’s affected by a myriad others, which means you’re still far from understanding it. The good news today is that sciences that were once data-poor are now data-rich. Instead of paying fifty bleary-eyed undergraduates to perform some task in the lab, psychologists can get as many subjects as they want by posting the task on Amazon’s Mechanical Turk. (It makes for a more diverse sample too.) It’s getting hard to remember, but little more than a decade ago sociologists studying social networks lamented that they couldn’t get their hands on a network with more than a few hundred members. Now there’s Facebook, with over a billion. A good chunk of those members post almost blow-by-blow accounts of their lives too; it’s like having a live feed of social life on planet Earth.

See Artificial intelligence (AI) AIDS vaccine, Bayesian networks and, 159–160 Alchemy, 246–259, 309 Markov logic networks and, 246–250 shortcomings, 255–259 tribes of machine learning and, 250–255 alchemy.cs.washington.edu, 250 Algorithms classifiers, 86–87 complexity monster and, 5–6 defined, 1 designing, 4–5 further readings, 298–299 genetic, 122–128 overview, 1–6 structure mapping, 199–200 See also Machine learning; individual algorithms AlphaDog, 21 Amazon, 198, 266, 291 A/B testing and, 227 data gathering, 211, 271, 272 machine learning and, 11, 12 Mechanical Turk, 14 recommendations, 12–13, 42, 184, 268, 286 Analogical reasoning, 179, 197 Analogizers, 51, 53, 54, 172–173 Alchemy and, 253–254 case-based reasoning, 197–200 dimensionality, 186–190 Master Algorithm and, 240–241 nearest-neighbor algorithm, 178–186 similiarity and, 179 support vector machines, 53, 190–196 symbolists vs., 200–202 Analogy, 175–179, 197–200 AND gate, 96 AND operation, 2 Anna Karenina (Tolstoy), 66 Apple, 272 Aristotle, 58, 64, 72, 178, 243 Artificial intelligence (AI) human control of, 282–284 knowledge engineers and, 35–36 machine learning and, 8, 89–90 ASIC (application-specific integrated circuit) design, 49 Asimov, Isaac, 232, 280 Assumptions ill-posed problem and, 64 of learners, 44 learning from finite data and, 24–25 prior, 174 simplifying to reduce number of probabilities, 150 symbolists and, 61–62 Atlantic (magazine), 273–274 AT&T, 272 Attribute selection, 186–187, 188–189 Attribute weights, 189 Auditory cortex, 26 Autoencoder, 116–118 Automation, machine learning and, 10 Automaton, 123 The Average American (O’Keefe), 206 Average member, 206 Axon, 95 Babbage, Charles, 28 Backpropagation (backprop), 52, 104, 107–111, 115, 302 Alchemy and, 252 genetic algorithms vs., 128 neural networks and, 112–114 reinforcement learning and, 222 Bagging, 238 Baldwin, J.


pages: 426 words: 105,423

The 4-Hour Workweek: Escape 9-5, Live Anywhere, and Join the New Rich by Timothy Ferriss

Albert Einstein, Amazon Mechanical Turk, call centre, clean water, Donald Trump, en.wikipedia.org, Firefox, fixed income, follow your passion, game design, global village, Iridium satellite, knowledge worker, late fees, lateral thinking, Maui Hawaii, oil shock, paper trading, Parkinson's law, passive income, peer-to-peer, pre–internet, Ralph Waldo Emerson, remote working, risk tolerance, Ronald Reagan, side project, Silicon Valley, Silicon Valley startup, Skype, Steve Jobs, Vilfredo Pareto, wage slave, William of Occam

FogBugz on Demand: http://www.fogcreek.com/FogBUGZ/IntrotoOnDemand.html. It’s a “bug tracker” aimed at software development companies, but I use it every day for both personal and business tasks. It’s almost like a VA, as you can route your mail through it and it will help you sort it and keep track of it. It has great features to track e-mails, and there’s a free version for two users (me + VA!). —RB CARTER A really useful service is Amazon’s Mechanical Turk. With a small investment in time or money, a business that requires hundreds of people doing small bits of defined work becomes possible for extraordinarily low work-per-unit costs. Examples include the search for Steve Fosset (literally thousands of people looked at satellite photos that would have overwhelmed SAR agencies) and a trouble-ticket business that utilizes qualified labor all over the world (see Amazon.com/webservices).


pages: 402 words: 126,835

The Job: The Future of Work in the Modern Era by Ellen Ruppel Shell

3D printing, affirmative action, Affordable Care Act / Obamacare, Airbnb, airport security, Albert Einstein, Amazon Mechanical Turk, basic income, Baxter: Rethink Robotics, big-box store, blue-collar work, Buckminster Fuller, call centre, Capital in the Twenty-First Century by Thomas Piketty, Clayton Christensen, cloud computing, collective bargaining, computer vision, corporate governance, corporate social responsibility, creative destruction, crowdsourcing, deskilling, disruptive innovation, Donald Trump, Downton Abbey, Elon Musk, Erik Brynjolfsson, factory automation, follow your passion, Frederick Winslow Taylor, future of work, game design, glass ceiling, hiring and firing, immigration reform, income inequality, industrial robot, invisible hand, Jeff Bezos, job automation, job satisfaction, John Markoff, John Maynard Keynes: Economic Possibilities for our Grandchildren, Joseph Schumpeter, Kickstarter, knowledge economy, knowledge worker, Kodak vs Instagram, labor-force participation, low skilled workers, Lyft, manufacturing employment, Marc Andreessen, Mark Zuckerberg, means of production, move fast and break things, move fast and break things, new economy, Norbert Wiener, obamacare, offshore financial centre, Paul Samuelson, precariat, Ralph Waldo Emerson, risk tolerance, Robert Gordon, Robert Shiller, Robert Shiller, Rodney Brooks, Ronald Reagan, Second Machine Age, self-driving car, shareholder value, sharing economy, Silicon Valley, Snapchat, Steve Jobs, The Chicago School, Thomas L Friedman, Thorstein Veblen, Tim Cook: Apple, Uber and Lyft, uber lyft, universal basic income, urban renewal, white picket fence, working poor, Y Combinator, young professional, zero-sum game

So some argue that the future of energy may lie not in large corporations serving investor demands, but in networks of nimble cooperatives responding to the needs of worker-owners who also happen to be customers. Equally promising, and perhaps even more unexpected, is the online “platform cooperative” designed to allow workers to exchange their labor without the interference—and cost—of a middleman. Platform cooperatives rose as an alternative to old-school online labor brokerages like Upwork and Amazon’s Mechanical Turk (MTurk), currently the most popular online work “marketplace.” MTurk is an online platform that employers (or “requesters”) use to “distribute” what Amazon calls “Human Intelligence Tasks,” snippets of work like filling out surveys, tagging photos, transcribing podcasts, or entering data into Excel spreadsheets. Generally, the tasks are broken down into bits that can be completed in a matter of seconds or minutes.

Yet, while demand is growing, satisfaction with the service is not. Requesters complain of workers doing a slipshod job, and workers accuse Amazon of “crowd-fleecing,” preying on a desperate worldwide digital workforce to grab the lion’s share of profits. (As filmmaker Alex Rivera put it in his cult hit Sleep Dealer, “all the work without the worker.”) Amazon’s own website all but confirms this charge, boasting that the company “significantly lowers costs” by “leveraging the skills of Mechanical Turk Workers from around the world.” MIT mathematician and philosopher Norbert Wiener once warned that under capitalism the very job of new technology was to intensify the exploitation of workers. “Crowd-sourced” work marketplaces have certainly contributed to this problem. Many labor advocates and scholars believe that online platforms like MTurk are ripe for disruption, and some have designed alternatives.


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

3D printing, Affordable Care Act / Obamacare, Airbnb, Alvin Roth, 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 cycle, business process, buy low sell high, chief data officer, Chuck Templeton: OpenTable:, clean water, cloud computing, connected car, corporate governance, crowdsourcing, data acquisition, data is the new oil, digital map, discounted cash flows, disintermediation, Edward Glaeser, Elon Musk, en.wikipedia.org, Erik Brynjolfsson, financial innovation, Haber-Bosch Process, High speed trading, information asymmetry, Internet of things, inventory management, invisible hand, Jean Tirole, Jeff Bezos, jimmy wales, John Markoff, Khan Academy, Kickstarter, Lean Startup, Lyft, Marc Andreessen, market design, Metcalfe’s law, 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, Robert Metcalfe, 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, Travis Kalanick, two-sided market, Uber and Lyft, Uber for X, uber lyft, winner-take-all economy, zero-sum game, Zipcar

The division of labor into smaller and smaller units of work, which Adam Smith recognized as a key to the productive capability of organizations almost three centuries ago, is likely to continue, powered by increasingly smart algorithms that are capable of breaking down a complex job into tiny, simple tasks to be handled by hundreds of workers, then reassembling the results into a unified whole. Amazon’s Mechanical Turk already applies this logic to many assignments. The trend toward freelance work, self-employment, contract labor, and nontraditional career paths will also continue to accelerate. The Freelancers Union estimates that one in three American workers already does some freelance work; that percentage is likely to increase in the years to come. Of course, this will be a mixed blessing. Many people who want flexibility and freedom to set their own working hours and conditions—artists, students, travelers, working moms, the semi-retired—will thrive in this new environment.


pages: 501 words: 114,888

The Future Is Faster Than You Think: How Converging Technologies Are Transforming Business, Industries, and Our Lives by Peter H. Diamandis, Steven Kotler

Ada Lovelace, additive manufacturing, Airbnb, Albert Einstein, Amazon Mechanical Turk, augmented reality, autonomous vehicles, barriers to entry, bitcoin, blockchain, blood diamonds, Burning Man, call centre, cashless society, Charles Lindbergh, Clayton Christensen, clean water, cloud computing, Colonization of Mars, computer vision, creative destruction, crowdsourcing, cryptocurrency, Dean Kamen, delayed gratification, dematerialisation, digital twin, disruptive innovation, Edward Glaeser, Edward Lloyd's coffeehouse, Elon Musk, en.wikipedia.org, epigenetics, Erik Brynjolfsson, Ethereum, ethereum blockchain, experimental economics, food miles, game design, Geoffrey West, Santa Fe Institute, gig economy, Google X / Alphabet X, gravity well, hive mind, housing crisis, Hyperloop, indoor plumbing, industrial robot, informal economy, Intergovernmental Panel on Climate Change (IPCC), Internet of things, invention of the telegraph, Isaac Newton, Jaron Lanier, Jeff Bezos, job automation, Joseph Schumpeter, Kevin Kelly, Kickstarter, late fees, Law of Accelerating Returns, life extension, lifelogging, loss aversion, Lyft, M-Pesa, Mary Lou Jepsen, mass immigration, megacity, meta analysis, meta-analysis, microbiome, mobile money, multiplanetary species, Narrative Science, natural language processing, Network effects, new economy, New Urbanism, Oculus Rift, out of africa, packet switching, peer-to-peer lending, Peter H. Diamandis: Planetary Resources, Peter Thiel, QR code, RAND corporation, Ray Kurzweil, RFID, Richard Feynman, Richard Florida, ride hailing / ride sharing, risk tolerance, Satoshi Nakamoto, Second Machine Age, self-driving car, Silicon Valley, Skype, smart cities, smart contracts, smart grid, Snapchat, sovereign wealth fund, special economic zone, stealth mode startup, stem cell, Stephen Hawking, Steve Jobs, Steven Pinker, Stewart Brand, supercomputer in your pocket, supply-chain management, technoutopianism, Tesla Model S, Tim Cook: Apple, transaction costs, Uber and Lyft, uber lyft, unbanked and underbanked, underbanked, urban planning, Watson beat the top human players on Jeopardy!, We wanted flying cars, instead we got 140 characters, X Prize

Airbnb has become the largest “hotel chain” in the world, yet they don’t own a single hotel room. They leverage (that is, rent out) the assets (spare bedrooms) of the crowd. These models also lean on staff-on-demand, which provides a company with the agility needed to adapt to a rapidly changing environment. Sure, this once meant call centers in India, but today it’s everything from micro-task laborers behind Amazon’s Mechanical Turk on the low end to Kaggle’s data scientist-on-demand service on the high end. The Free/Data Economy: This is the platform version of the “bait and hook” model, essentially baiting the customer with free access to a cool service (like Facebook) and then making money off the data gathered about that customer (also like Facebook). It also includes all the developments spurred by the big data revolution, which is allowing us to exploit micro-demographics like never before.


pages: 170 words: 49,193

The People vs Tech: How the Internet Is Killing Democracy (And How We Save It) by Jamie Bartlett

Ada Lovelace, Airbnb, Amazon Mechanical Turk, Andrew Keen, autonomous vehicles, barriers to entry, basic income, Bernie Sanders, bitcoin, blockchain, Boris Johnson, central bank independence, Chelsea Manning, cloud computing, computer vision, creative destruction, cryptocurrency, Daniel Kahneman / Amos Tversky, Dominic Cummings, Donald Trump, Edward Snowden, Elon Musk, Filter Bubble, future of work, gig economy, global village, Google bus, hive mind, Howard Rheingold, information retrieval, Internet of things, Jeff Bezos, job automation, John Maynard Keynes: technological unemployment, Julian Assange, manufacturing employment, Mark Zuckerberg, Marshall McLuhan, Menlo Park, meta analysis, meta-analysis, mittelstand, move fast and break things, move fast and break things, Network effects, Nicholas Carr, off grid, Panopticon Jeremy Bentham, payday loans, Peter Thiel, prediction markets, QR code, ransomware, Ray Kurzweil, recommendation engine, Renaissance Technologies, ride hailing / ride sharing, Robert Mercer, Ross Ulbricht, Sam Altman, Satoshi Nakamoto, Second Machine Age, sharing economy, Silicon Valley, Silicon Valley ideology, Silicon Valley startup, smart cities, smart contracts, smart meter, Snapchat, Stanford prison experiment, Steve Jobs, Steven Levy, strong AI, TaskRabbit, technological singularity, technoutopianism, Ted Kaczynski, the medium is the message, the scientific method, The Spirit Level, The Wealth of Nations by Adam Smith, The Wisdom of Crowds, theory of mind, too big to fail, ultimatum game, universal basic income, WikiLeaks, World Values Survey, Y Combinator

I was told repeatedly in the magical Silicon Valley bubble where everything is possible that unemployed truckers in their fifties could retrain as web-developers and machine learning specialists – a convenient self-delusion that no one really believes. It is far more likely that many truck drivers, without the necessary skills, will drift off to more precarious, piecemeal, low-paid work – perhaps becoming taxi drivers (assuming they still exist) or Amazon warehouse operators or Mechanical Turk labourers who are paid an hourly rate to train software or fill in surveys. Perhaps they could clean the machines that clean the machines that repair the driverless trucks that they once occupied.* Routine and non We should be reasonably confident that AI will result in forward leaps in productivity and overall wealth. The big question is how the spoils of that wealth will be shared out.


pages: 291 words: 81,703

Average Is Over: Powering America Beyond the Age of the Great Stagnation by Tyler Cowen

Amazon Mechanical Turk, Black Swan, brain emulation, Brownian motion, business cycle, Cass Sunstein, choice architecture, complexity theory, computer age, computer vision, computerized trading, cosmological constant, crowdsourcing, dark matter, David Brooks, David Ricardo: comparative advantage, deliberate practice, Drosophila, en.wikipedia.org, endowment effect, epigenetics, Erik Brynjolfsson, eurozone crisis, experimental economics, Flynn Effect, Freestyle chess, full employment, future of work, game design, income inequality, industrial robot, informal economy, Isaac Newton, Johannes Kepler, John Markoff, Khan Academy, labor-force participation, Loebner Prize, low skilled workers, manufacturing employment, Mark Zuckerberg, meta analysis, meta-analysis, microcredit, Myron Scholes, Narrative Science, Netflix Prize, Nicholas Carr, P = NP, pattern recognition, Peter Thiel, randomized controlled trial, Ray Kurzweil, reshoring, Richard Florida, Richard Thaler, Ronald Reagan, Silicon Valley, Skype, statistical model, stem cell, Steve Jobs, Turing test, Tyler Cowen: Great Stagnation, upwardly mobile, Yogi Berra

In the eighteenth and nineteenth centuries, the trick was to sneak a human chess player inside a machine and pretend to have created a technological marvel—a machine that played a good game of chess. This formed the basis of a sensational traveling exhibition called a Mechanical Turk, which hid a human inside—in a nontransparent manner—using principles now associated with magicians. (If you are wondering, the name of Amazon’s current Mechanical Turk service, which combines man and machine to perform programming tasks, is based on this history.) The machine “operated” from 1770 until its destruction by fire in 1854, although it was exposed as a fake at least as early as 1820. It was originally designed to impress Queen Maria Theresa of Austria, and the contraption is said to have defeated both Benjamin Franklin and Napoleon Bonaparte at chess.


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

23andMe, 3D printing, Airbnb, Amazon Mechanical Turk, Amazon Web Services, augmented reality, autonomous vehicles, Baxter: Rethink Robotics, Ben Horowitz, bioinformatics, bitcoin, Black Swan, blockchain, Burning Man, business intelligence, business process, call centre, chief data officer, Chris Wanstrath, Clayton Christensen, clean water, cloud computing, cognitive bias, collaborative consumption, collaborative economy, commoditize, corporate social responsibility, cross-subsidies, crowdsourcing, cryptocurrency, dark matter, Dean Kamen, dematerialisation, discounted cash flows, disruptive innovation, distributed ledger, Edward Snowden, Elon Musk, en.wikipedia.org, Ethereum, ethereum blockchain, game design, Google Glasses, Google Hangouts, Google X / Alphabet X, gravity well, hiring and firing, Hyperloop, industrial robot, Innovator's Dilemma, intangible asset, Internet of things, Iridium satellite, Isaac Newton, Jeff Bezos, Joi Ito, Kevin Kelly, Kickstarter, knowledge worker, Kodak vs Instagram, Law of Accelerating Returns, Lean Startup, life extension, lifelogging, loose coupling, loss aversion, low earth orbit, Lyft, Marc Andreessen, Mark Zuckerberg, market design, means of production, minimum viable product, natural language processing, Netflix Prize, NetJets, Network effects, new economy, Oculus Rift, offshore financial centre, PageRank, pattern recognition, Paul Graham, paypal mafia, peer-to-peer, peer-to-peer model, 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, Travis Kalanick, Tyler Cowen: Great Stagnation, uber lyft, urban planning, WikiLeaks, winner-take-all economy, X Prize, Y Combinator, zero-sum game

When Proctor and Gamble needs to know how and where its merchandise is being placed on Walmart shelves around the world, it can use Gigwalk’s platform to instantly deploy thousands of people who are paid a few dollars to walk into Walmart and check the shelves. Results come in within an hour. Staff-on-demand initiatives similar to Gigwalk are springing up everywhere: oDesk, Roamler, Elance, TaskRabbit and Amazon’s venerable Mechanical Turk are platforms where all levels of work, including highly skilled labor, can be outsourced. These companies, which represent just the first wave of this new business model, optimize the concept of paying for performance to lower customer risk. For talented workers, working on and getting paid for multiple projects is a particularly welcome opportunity. But there’s another angle as well: an increase in the diversity of ideas.


pages: 497 words: 144,283

Connectography: Mapping the Future of Global Civilization by Parag Khanna

"Robert Solow", 1919 Motor Transport Corps convoy, 2013 Report for America's Infrastructure - American Society of Civil Engineers - 19 March 2013, 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, commoditize, complexity theory, continuation of politics by other means, 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, digital map, disruptive innovation, diversification, Doha Development Round, edge city, Edward Snowden, Elon Musk, energy security, Ethereum, ethereum blockchain, European colonialism, eurozone crisis, failed state, Fall of the Berlin Wall, family office, Ferguson, Missouri, financial innovation, financial repression, fixed income, 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 cluster, industrial robot, informal economy, Infrastructure as a Service, interest rate swap, Intergovernmental Panel on Climate Change (IPCC), Internet of things, Isaac Newton, Jane Jacobs, Jaron Lanier, John von Neumann, Julian Assange, Just-in-time delivery, Kevin Kelly, Khyber Pass, Kibera, Kickstarter, LNG terminal, low cost airline, low cost carrier, low earth orbit, manufacturing employment, mass affluent, mass immigration, megacity, Mercator projection, Metcalfe’s law, microcredit, mittelstand, Monroe Doctrine, mutually assured destruction, New Economic Geography, new economy, New Urbanism, off grid, offshore financial centre, oil rush, oil shale / tar sands, oil shock, openstreetmap, out of africa, Panamax, Parag Khanna, Peace of Westphalia, peak oil, Pearl River Delta, Peter Thiel, Philip Mirowski, 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, The inhabitant of London could order by telephone, sipping his morning tea in bed, the various products of the whole earth, Tim Cook: Apple, trade route, transaction costs, UNCLOS, uranium enrichment, urban planning, urban sprawl, WikiLeaks, young professional, zero day

THE GLOBAL DIGITAL WORKFORCE At any given time, my wife and I might be employing a Filipino during a typhoon, an Indian during a power outage, a Ukrainian during a war, a Tunisian during an upheaval—and even once a Malaysian unfortunately named Saddam Hussein—to manage our schedules or do Internet searches. They all work on short-term, delivery-based tasks via Upwork, the largest of the mushrooming number of virtual work portals (alongside Amazon’s Mechanical Turk and Freelancer.​com) that collectively provide at least 100 million people with more income than they would otherwise have. While Silicon Valley technology companies employ fewer workers than their industrial-age counterparts such as General Motors, their global services platforms facilitate portable and digital work for the connected masses whether posting advertisements, verifying addresses, photographing for registries, comparing prices for companies, or performing other basic tasks.


pages: 340 words: 94,464

Randomistas: How Radical Researchers Changed Our World by Andrew Leigh

Albert Einstein, Amazon Mechanical Turk, Anton Chekhov, Atul Gawande, basic income, Black Swan, correlation does not imply causation, crowdsourcing, David Brooks, Donald Trump, ending welfare as we know it, Estimating the Reproducibility of Psychological Science, experimental economics, Flynn Effect, germ theory of disease, Ignaz Semmelweis: hand washing, Indoor air pollution, Isaac Newton, Kickstarter, longitudinal study, loss aversion, Lyft, Marshall McLuhan, meta analysis, meta-analysis, microcredit, Netflix Prize, nudge unit, offshore financial centre, p-value, placebo effect, price mechanism, publication bias, RAND corporation, randomized controlled trial, recommendation engine, Richard Feynman, ride hailing / ride sharing, Robert Metcalfe, Ronald Reagan, statistical model, Steven Pinker, uber lyft, universal basic income, War on Poverty

In a randomised experiment of condom sellers in urban Zambia, a team of researchers compared the effect of bonus pay with social recognition of star employees.43 In that setting, it turns out that the promise of being publicly recognised has twice as large an impact as financial rewards. Who knew that being ‘condom seller of the month’ could be such an incentive? But other kinds of ‘recognition’ can have the opposite effect. In a randomised experiment run on workers on Amazon’s online Mechanical Turk platform, some employees were given feedback about their relative ranking, compared to their co-workers.44 Telling workers their place in the pecking order turned out to reduce productivity. If you’re a boss, these experiments are a reminder that the most productive people in the workplace are bringing in a double dividend. They also suggest that you might want to promote ‘most valued employee’ awards, but sack worker league tables.


pages: 299 words: 92,782

The Success Equation: Untangling Skill and Luck in Business, Sports, and Investing by Michael J. Mauboussin

Amazon Mechanical Turk, Atul Gawande, Benoit Mandelbrot, Black Swan, Checklist Manifesto, Clayton Christensen, cognitive bias, commoditize, Daniel Kahneman / Amos Tversky, David Brooks, deliberate practice, disruptive innovation, Emanuel Derman, fundamental attribution error, Gini coefficient, hindsight bias, hiring and firing, income inequality, Innovator's Dilemma, Long Term Capital Management, loss aversion, Menlo Park, mental accounting, moral hazard, Network effects, prisoner's dilemma, random walk, Richard Thaler, risk-adjusted returns, shareholder value, Simon Singh, six sigma, Steven Pinker, transaction costs, winner-take-all economy, zero-sum game, Zipf's Law

If a prospective reader likes a title, then she might be more likely to open the book and take a look, and that would increase the likelihood that she'd buy it. As we saw in the discussion of the shape of luck, there are many factors that go in to book sales beyond the title. All things being equal, though, a good title is better than a bad one. So I took matters into my own hands and set up a tournament. I used a service from Amazon.com called Mechanical Turk. The site allows you to offer micropayments to people willing to complete a “human intelligence task,” often a question that needs an answer. I asked my editor for her favorite seven titles and added Think Twice, paired them randomly, and offered turkers $0.10 to “select the best title for a book.” The titles that won each round moved on to the next round, just as in a sports tournament.


pages: 265 words: 69,310

pages: 379 words: 109,612

Is the Internet Changing the Way You Think?: The Net's Impact on Our Minds and Future by John Brockman

A Declaration of the Independence of Cyberspace, Albert Einstein, AltaVista, Amazon Mechanical Turk, Asperger Syndrome, availability heuristic, Benoit Mandelbrot, biofilm, Black Swan, British Empire, conceptual framework, corporate governance, Danny Hillis, Douglas Engelbart, Douglas Engelbart, Emanuel Derman, epigenetics, Flynn Effect, Frank Gehry, Google Earth, hive mind, Howard Rheingold, index card, information retrieval, Internet Archive, invention of writing, Jane Jacobs, Jaron Lanier, John Markoff, Kevin Kelly, lifelogging, lone genius, loss aversion, mandelbrot fractal, Marc Andreessen, Marshall McLuhan, Menlo Park, meta analysis, meta-analysis, New Journalism, Nicholas Carr, out of africa, Paul Samuelson, peer-to-peer, Ponzi scheme, pre–internet, Richard Feynman, Rodney Brooks, Ronald Reagan, Schrödinger's Cat, Search for Extraterrestrial Intelligence, SETI@home, Silicon Valley, Skype, slashdot, smart grid, social graph, social software, social web, Stephen Hawking, Steve Wozniak, Steven Pinker, Stewart Brand, Ted Nelson, telepresence, the medium is the message, the scientific method, The Wealth of Nations by Adam Smith, theory of mind, trade route, upwardly mobile, Vernor Vinge, Whole Earth Catalog, X Prize

Nowadays open-source development moves around in the infosphere and is being improved constantly on whatever side of the planet happens to be in sunshine (and often on the other side as well). There is grandeur in this new way of computer life, where the normal sleep-wake cycle is replaced by the constant churning of silicon and mind. But there is much inherent danger in it as well. Take a look at Amazon’s aptly named Mechanical Turk, and you’ll find an alternative Website where largely profitable enterprises in developed countries offer short-term, badly paid computer jobs to the third world’s poor. For a few pennies, they propose a number of thankless assignments ironically called “human intelligence tasks” that require completing forms, categorizing images, or typing handwritten notes—anything computers still cannot do.


pages: 391 words: 123,597

Targeted: The Cambridge Analytica Whistleblower's Inside Story of How Big Data, Trump, and Facebook Broke Democracy and How It Can Happen Again by Brittany Kaiser

Albert Einstein, Amazon Mechanical Turk, Asian financial crisis, Bernie Sanders, bitcoin, blockchain, Boris Johnson, Burning Man, call centre, centre right, Chelsea Manning, clean water, cognitive dissonance, crony capitalism, Dominic Cummings, Donald Trump, Edward Snowden, Etonian, haute couture, illegal immigration, Julian Assange, Mark Zuckerberg, Menlo Park, Nelson Mandela, off grid, open borders, Renaissance Technologies, Robert Mercer, rolodex, sentiment analysis, Silicon Valley, Silicon Valley startup, Skype, Snapchat, statistical model, the High Line, the scientific method, WikiLeaks, young professional

The Guardian article alleged that the data gathering Dr. Kogan had done was back in 2013, which was well before the cut-off date. The story gained traction overnight. It was reprinted everywhere, and led to additional reporting in influential publications such as Fortune and Mother Jones and on sites such as Business Insider and Gizmodo. Kogan’s 2013 data gathering had first taken place on an Amazon Marketplace platform called “Mechanical Turk.” He had paid users a dollar apiece to take the personality quiz This Is Your Digital Life. When users completed the quiz on Facebook, the app connected to the Friends API to take their data and that of their entire list of friends. From the answers Kogan had obtained through This Is Your Digital Life, he created a training set to model all the participants’ personalities and then reportedly sold the modeling and the data set to CA, where Alex Tayler and the team tested Kogan’s models and then created new, more accurate ones based on similar concepts of personality measurement.


pages: 349 words: 95,972

Messy: The Power of Disorder to Transform Our Lives by Tim Harford

affirmative action, Air France Flight 447, Airbnb, airport security, Albert Einstein, Amazon Mechanical Turk, Amazon Web Services, assortative mating, Atul Gawande, autonomous vehicles, banking crisis, Barry Marshall: ulcers, Basel III, Berlin Wall, British Empire, Broken windows theory, call centre, Cass Sunstein, Chris Urmson, cloud computing, collateralized debt obligation, crowdsourcing, deindustrialization, Donald Trump, Erdős number, experimental subject, Ferguson, Missouri, Filter Bubble, Frank Gehry, game design, global supply chain, Googley, Guggenheim Bilbao, high net worth, Inbox Zero, income inequality, industrial cluster, Internet of things, Jane Jacobs, Jeff Bezos, Loebner Prize, Louis Pasteur, Marc Andreessen, Mark Zuckerberg, Menlo Park, Merlin Mann, microbiome, out of africa, Paul Erdős, Richard Thaler, Rosa Parks, self-driving car, side project, Silicon Valley, Silicon Valley startup, Skype, Steve Jobs, Steven Levy, Stewart Brand, telemarketer, the built environment, The Death and Life of Great American Cities, Turing test, urban decay, William Langewiesche

Amazon was saved by a clever finance director, who had arranged a cash flow cushion, and some cobbled-together joint ventures. It had been close. As Brad Stone writes, “Amazon survived through a combination of conviction, improvisation, and luck.”14 Most companies would have retrenched at that point. Instead, over the next few years, Amazon launched products as disparate as the Kindle (which immediately and repeatedly sold out, as Amazon struggled to manufacture it), Mechanical Turk (an unsettlingly named global clearinghouse for labor, which pioneered crowdsourcing but was criticized as being a sweatshop), the Fire Phone (widely reviewed as ugly, weird, and disappointing), Marketplace (where competitors to Amazon would use Amazon’s own product listings to advertise their own cheaper alternatives), and Amazon Web Services. AWS in particular was a bold stroke—a move into cloud computing in 2006, four years ahead of Microsoft’s Azure and six years ahead of Google Compute.



pages: 742 words: 137,937

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

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, commoditize, computer age, Computer Numeric Control, computer vision, conceptual framework, corporate governance, creative destruction, crowdsourcing, Daniel Kahneman / Amos Tversky, death of newspapers, disintermediation, Douglas Hofstadter, en.wikipedia.org, Erik Brynjolfsson, Filter Bubble, 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, lifelogging, lump of labour, Marshall McLuhan, Metcalfe’s law, Narrative Science, natural language processing, Network effects, optical character recognition, Paul Samuelson, personalized medicine, pre–internet, Ray Kurzweil, Richard Feynman, Second Machine Age, self-driving car, semantic web, Shoshana Zuboff, Skype, social web, speech recognition, spinning jenny, strong AI, supply-chain management, telepresence, The Future of Employment, 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!, WikiLeaks, young professional


pages: 567 words: 122,311

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

"Robert Solow", 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, basic income, Baxter: Rethink Robotics, British Empire, business cycle, business intelligence, business process, call centre, Charles Lindbergh, Chuck Templeton: OpenTable:, clean water, combinatorial explosion, computer age, computer vision, congestion charging, corporate governance, creative destruction, crowdsourcing, David Ricardo: comparative advantage, digital map, 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, G4S, game design, global village, happiness index / gross national happiness, illegal immigration, immigration reform, income inequality, income per capita, indoor plumbing, industrial robot, informal economy, intangible asset, inventory management, James Watt: steam engine, Jeff Bezos, jimmy wales, job automation, John Markoff, 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, Marc Andreessen, Mark Zuckerberg, Mars Rover, mass immigration, 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, Paul Samuelson, payday loans, post-work, 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 took a large problem (finding the duplicates among millions of pages), broke it down into many small tasks (are these two pages duplicates?), sent the tasks out to a large group of people, collected their responses, and used them to make progress on the problem (eliminating the duplicates). The software was originally intended only for internal use, but in November of 2005 Amazon released it to the public under the name Mechanical Turk, in honor of a famous eighteenth-century chess-playing ‘robot’ that turned out to have a human inside it.25 The Mechanical Turk software was similar to this automaton in that it too appeared to accomplish tasks automatically, but in reality made use of human labor. 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.


pages: 320 words: 87,853

The Black Box Society: The Secret Algorithms That Control Money and Information by Frank Pasquale

Affordable Care Act / Obamacare, algorithmic trading, Amazon Mechanical Turk, American Legislative Exchange Council, asset-backed security, Atul Gawande, bank run, barriers to entry, basic income, Berlin Wall, Bernie Madoff, Black Swan, bonus culture, Brian Krebs, business cycle, call centre, Capital in the Twenty-First Century by Thomas Piketty, Chelsea Manning, Chuck Templeton: OpenTable:, cloud computing, collateralized debt obligation, computerized markets, corporate governance, Credit Default Swap, credit default swaps / collateralized debt obligations, crowdsourcing, cryptocurrency, Debian, don't be evil, drone strike, Edward Snowden, en.wikipedia.org, Fall of the Berlin Wall, Filter Bubble, financial innovation, financial thriller, fixed income, Flash crash, full employment, Goldman Sachs: Vampire Squid, Google Earth, Hernando de Soto, High speed trading, hiring and firing, housing crisis, informal economy, information asymmetry, information retrieval, interest rate swap, Internet of things, invisible hand, Jaron Lanier, Jeff Bezos, job automation, Julian Assange, Kevin Kelly, knowledge worker, Kodak vs Instagram, kremlinology, late fees, London Interbank Offered Rate, London Whale, Marc Andreessen, Mark Zuckerberg, mobile money, moral hazard, new economy, Nicholas Carr, offshore financial centre, PageRank, pattern recognition, Philip Mirowski, precariat, profit maximization, profit motive, quantitative easing, race to the bottom, recommendation engine, regulatory arbitrage, risk-adjusted returns, Satyajit Das, search engine result page, shareholder value, Silicon Valley, Snapchat, social intelligence, Spread Networks laid a new fibre optics cable between New York and Chicago, statistical arbitrage, statistical model, Steven Levy, the scientific method, too big to fail, transaction costs, two-sided market, universal basic income, Upton Sinclair, value at risk, WikiLeaks, zero-sum game

But note Matt Yglesias on how this ultimately helped Apple, and the fundamental lesson: nobody gets displaced, it’s just a clash of titans over market share. Matthew Yglesias, “A Great iOS Google Maps Product Vindicates Apple’s Strategy,” Slate MoneyBox (blog), December 13, 2012, http://www.slate.com /blogs /moneybox /2012/12/13/ios _google _maps _if _it _s _great _thank _apple _s _strat egy.html. 213. Labor experts have sharply criticized Amazon’s labor practices both online (at its Mechanical Turk platform) and its warehouses. Trebor Scholz, ed., Digital Labor: The Internet as Factory and Playground (New York: Routledge, 2013). 214. Norman Solomon, “If Obama Orders the CIA to Kill a U.S. Citizen, Amazon Will Be a Partner in Assassination,” Alternet, February 12, 2014, http://www.alternet.org/print /news-amp-politics/if-obama-orders-cia-kill-us -citizen-amazon-will-be-partner-assassination. 215.


pages: 299 words: 91,839

What Would Google Do? by Jeff Jarvis

23andMe, Amazon Mechanical Turk, Amazon Web Services, Anne Wojcicki, barriers to entry, Berlin Wall, business process, call centre, cashless society, citizen journalism, clean water, commoditize, connected car, credit crunch, crowdsourcing, death of newspapers, different worldview, disintermediation, diversified portfolio, don't be evil, fear of failure, Firefox, future of journalism, G4S, 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, old-boy network, 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, WikiLeaks, Y Combinator, Zipcar

He sells his retail services to other merchants, sending them customers online and taking a cut, in some cases warehousing and shipping their inventory and charging for the services. He also took the computer infrastructure he had to build and offered it to any company as a low-cost, pay-as-you-go service: computing power, storage, databases, and a mechanism for paying programmers. Countless companies now use Amazon Web Services as their backend, foregoing or at least forestalling investments in computers and software. Amazon has also created the infrastructure for an on-demand workforce called Mechanical Turk (named after a phony chess-playing automaton from 1769 that had a human chess master hidden inside). Companies post a repetitive task to be done and anyone can earn money—as little as one cent per task—by verifying the address in a picture, for example, or categorizing content. It’s a flexible marketplace for labor. With all these services, Amazon is supporting a wave of entrepreneurial effort.


pages: 316 words: 87,486

Listen, Liberal: Or, What Ever Happened to the Party of the People? by Thomas Frank

Affordable Care Act / Obamacare, Airbnb, Amazon Mechanical Turk, American ideology, barriers to entry, Berlin Wall, Bernie Sanders, blue-collar work, Burning Man, centre right, circulation of elites, Clayton Christensen, collective bargaining, Credit Default Swap, David Brooks, deindustrialization, disruptive innovation, Donald Trump, Edward Snowden, Fall of the Berlin Wall, financial innovation, Frank Gehry, full employment, George Gilder, gig economy, Gini coefficient, income inequality, Jaron Lanier, Jeff Bezos, knowledge economy, knowledge worker, Lean Startup, mandatory minimum, Marc Andreessen, Mark Zuckerberg, market bubble, mass immigration, mass incarceration, McMansion, microcredit, mobile money, moral panic, mortgage debt, Nelson Mandela, new economy, obamacare, payday loans, Peter Thiel, plutocrats, Plutocrats, Ponzi scheme, post-industrial society, postindustrial economy, pre–internet, profit maximization, profit motive, race to the bottom, Republic of Letters, Richard Florida, ride hailing / ride sharing, Ronald Reagan, sharing economy, Silicon Valley, Steve Jobs, Steven Levy, TaskRabbit, Thorstein Veblen, too big to fail, Travis Kalanick, Uber for X, union organizing, urban decay, women in the workforce, Works Progress Administration, young professional

Jobs then forwarded Schmidt’s email around with this comment appended: “:)”19 Amazon, meanwhile, is famous for devising ways to goad its executives into fighting with one another—engaging in what the New York Times calls an “experiment in how far it can push white-collar workers”—while its blue-collar workers, often recruited through local temp agencies, are electronically tracked so that their efficiency is maximized as they go about assembling items in the company’s enormous fulfillment centers.20 For the rest of us, Amazon has come up with a nifty device for casual employment called “the Mechanical Turk,” in which tasks that can’t be done by computers are tossed to the reserve army of the millions, who receive pennies for their trouble. This last is a good introduction to the so-called sharing economy—“sharing” because you’re using your own car or apartment or computer, not your employer’s—which has been one of the few robustly growing employment opportunities of the Obama years.


pages: 391 words: 105,382

Utopia Is Creepy: And Other Provocations by Nicholas Carr

Air France Flight 447, Airbnb, Airbus A320, AltaVista, Amazon Mechanical Turk, augmented reality, autonomous vehicles, Bernie Sanders, book scanning, Brewster Kahle, Buckminster Fuller, Burning Man, Captain Sullenberger Hudson, centralized clearinghouse, Charles Lindbergh, cloud computing, cognitive bias, collaborative consumption, computer age, corporate governance, crowdsourcing, Danny Hillis, deskilling, digital map, disruptive innovation, Donald Trump, Electric Kool-Aid Acid Test, 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, Joan Didion, job automation, Kevin Kelly, lifelogging, low skilled workers, Marc Andreessen, Mark Zuckerberg, Marshall McLuhan, means of production, Menlo Park, mental accounting, natural language processing, Network effects, new economy, Nicholas Carr, Norman Mailer, off grid, 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


pages: 706 words: 202,591