data is the new oil

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Four Battlegrounds by Paul Scharre

2021 United States Capitol attack, 3D printing, active measures, activist lawyer, AI winter, AlphaGo, amateurs talk tactics, professionals talk logistics, artificial general intelligence, ASML, augmented reality, Automated Insights, autonomous vehicles, barriers to entry, Berlin Wall, Big Tech, bitcoin, Black Lives Matter, Boeing 737 MAX, Boris Johnson, Brexit referendum, business continuity plan, business process, carbon footprint, chief data officer, Citizen Lab, clean water, cloud computing, commoditize, computer vision, coronavirus, COVID-19, crisis actor, crowdsourcing, DALL-E, data is not the new oil, data is the new oil, data science, deep learning, deepfake, DeepMind, Demis Hassabis, Deng Xiaoping, digital map, digital rights, disinformation, Donald Trump, drone strike, dual-use technology, Elon Musk, en.wikipedia.org, endowment effect, fake news, Francis Fukuyama: the end of history, future of journalism, future of work, game design, general purpose technology, Geoffrey Hinton, geopolitical risk, George Floyd, global supply chain, GPT-3, Great Leap Forward, hive mind, hustle culture, ImageNet competition, immigration reform, income per capita, interchangeable parts, Internet Archive, Internet of things, iterative process, Jeff Bezos, job automation, Kevin Kelly, Kevin Roose, large language model, lockdown, Mark Zuckerberg, military-industrial complex, move fast and break things, Nate Silver, natural language processing, new economy, Nick Bostrom, one-China policy, Open Library, OpenAI, PalmPilot, Parler "social media", pattern recognition, phenotype, post-truth, purchasing power parity, QAnon, QR code, race to the bottom, RAND corporation, recommendation engine, reshoring, ride hailing / ride sharing, robotic process automation, Rodney Brooks, Rubik’s Cube, self-driving car, Shoshana Zuboff, side project, Silicon Valley, slashdot, smart cities, smart meter, Snapchat, social software, sorting algorithm, South China Sea, sparse data, speech recognition, Steve Bannon, Steven Levy, Stuxnet, supply-chain attack, surveillance capitalism, systems thinking, tech worker, techlash, telemarketer, The Brussels Effect, The Signal and the Noise by Nate Silver, TikTok, trade route, TSMC

., Scaling Laws for Autoregressive Generative Modeling (arXiv.org, November 6, 2020), https://arxiv.org/pdf/2010.14701.pdf. 20“Data is the new oil”: Joris Toonders, “Data Is the New Oil of the Digital Economy,” Wired, n.d., https://www.wired.com/insights/2014/07/data-new-oil-digital-economy/; Kiran Bhageshpur, “Data Is the New Oil—and That’s a Good Thing,” Forbes, November 15, 2019, https://www.forbes.com/sites/forbestechcouncil/2019/11/15/data-is-the-new-oil-and-thats-a-good-thing/?sh=10eefed73045; Adeola Adesina, “Data Is the New Oil,” Medium, November 13, 2018, https://medium.com/@adeolaadesina/data-is-the-new-oil-2947ed8804f6; Will Murphy, “Data Is the New Oil,” Towards Data Science, May 7, 2017, https://towardsdatascience.com/data-is-the-new-oil-f11440e80dd0; Giuliano Giacaglia, “Data Is the New Oil,” Hackernoon, February 9, 2019, https://hackernoon.com/data-is-the-new-oil-1227197762b2. 20data-is-not-the-new-oil articles: Antonio Garcia Martinez, “No, Data Is Not the New Oil,” Wired, February 26, 2019, https://www.wired.com/story/no-data-is-not-the-new-oil/; Bernard Marr, “Here’s Why Data Is Not the New Oil,” Forbes, March 5, 2018, https://www.forbes.com/sites/bernardmarr/2018/03/05/heres-why-data-is-not-the-new-oil/?

sh=10eefed73045; Adeola Adesina, “Data Is the New Oil,” Medium, November 13, 2018, https://medium.com/@adeolaadesina/data-is-the-new-oil-2947ed8804f6; Will Murphy, “Data Is the New Oil,” Towards Data Science, May 7, 2017, https://towardsdatascience.com/data-is-the-new-oil-f11440e80dd0; Giuliano Giacaglia, “Data Is the New Oil,” Hackernoon, February 9, 2019, https://hackernoon.com/data-is-the-new-oil-1227197762b2. 20data-is-not-the-new-oil articles: Antonio Garcia Martinez, “No, Data Is Not the New Oil,” Wired, February 26, 2019, https://www.wired.com/story/no-data-is-not-the-new-oil/; Bernard Marr, “Here’s Why Data Is Not the New Oil,” Forbes, March 5, 2018, https://www.forbes.com/sites/bernardmarr/2018/03/05/heres-why-data-is-not-the-new-oil/?sh=4b277fa13aa9; Samuel Flender, “Data Is Not the New Oil,” Towards Data Science, February 10, 2019, https://towardsdatascience.com/data-is-not-the-new-oil-bdb31f61bc2d; John Thuma, “Data Is Not the New Oil!”

AI researchers continue to see performance gains from ever-larger models and datasets, demonstrating the value of large datasets. The search for historical analogies to understand the geostrategic significance of digital power, such as data, is understandable, even if such analogies are bound to be imperfect. “Data is the new oil” became a common refrain for a brief period, spawning articles and op-eds in outlets such as Wired, Forbes, and the New York Times. (Not long after came a counter-wave of data-is-not-the-new-oil articles, including in many of the same outlets.) Data, of course, is not oil. But it can be a useful metaphor in certain ways.


pages: 301 words: 85,263

New Dark Age: Technology and the End of the Future by James Bridle

AI winter, Airbnb, Alfred Russel Wallace, AlphaGo, Anthropocene, Automated Insights, autonomous vehicles, back-to-the-land, Benoit Mandelbrot, Bernie Sanders, bitcoin, Boeing 747, British Empire, Brownian motion, Buckminster Fuller, Cambridge Analytica, Capital in the Twenty-First Century by Thomas Piketty, carbon footprint, coastline paradox / Richardson effect, cognitive bias, cognitive dissonance, combinatorial explosion, computer vision, congestion charging, cryptocurrency, data is the new oil, disinformation, Donald Trump, Douglas Engelbart, Douglas Engelbart, Douglas Hofstadter, Dr. Strangelove, drone strike, Edward Snowden, Eyjafjallajökull, Fairchild Semiconductor, fake news, fear of failure, Flash crash, fulfillment center, Google Earth, Greyball, Haber-Bosch Process, Higgs boson, hive mind, income inequality, informal economy, Internet of things, Isaac Newton, ITER tokamak, James Bridle, John von Neumann, Julian Assange, Kickstarter, Kim Stanley Robinson, Large Hadron Collider, late capitalism, Laura Poitras, Leo Hollis, lone genius, machine translation, mandelbrot fractal, meta-analysis, Minecraft, mutually assured destruction, natural language processing, Network effects, oil shock, p-value, pattern recognition, peak oil, recommendation engine, road to serfdom, Robert Mercer, Ronald Reagan, security theater, self-driving car, Seymour Hersh, Silicon Valley, Silicon Valley ideology, Skype, social graph, sorting algorithm, South China Sea, speech recognition, Spread Networks laid a new fibre optics cable between New York and Chicago, stem cell, Stuxnet, technoutopianism, the built environment, the scientific method, Uber for X, undersea cable, University of East Anglia, uranium enrichment, Vannevar Bush, warehouse robotics, WikiLeaks

Hollenbach, ‘Technology and Collective Action: The Effect of Cell Phone Coverage on Political Violence in Africa’, American Political Science Review 107:2 (May 2013). 14.Michael Palmer, ‘Data is the New Oil’, blog post, ANA, November 2006, ana.blogs.com. 15.‘The world’s most valuable resource is no longer oil, but data’, Economist, May 6, 2017, economist.com. 16.David Reid, ‘Mastercard’s boss just told a Saudi audience that “data is the new oil”’, CNBC, October 24, 2017, cnbc.com. 17.Stephen Kerr MP, Kevin Brennan MP, debate on ‘Leaving the EU: Data Protection’, October 12, 2017, transcript. 18.Palmer, ‘Data is the New Oil’. 19.For details of imperial classification and forced naming, see James C. Scott, Seeing Like a State, New Haven, CT: Yale University Press, 1998. 20.Arundhati Roy, ‘The End of Imagination’, Guardian, August 1, 1998, theguardian.com. 21.Sandia National Laboratories, ‘Expert Judgment on Markers to Deter Inadvertent Human Intrusion into the Waste Isolation Pilot Plant’, report, SAND92-1382 / UC-721, page F-49, available at wipp.energy.gov. 22.And into Eternity … Communication over 10000s of Years: How Will We Tell our Children’s Children Where the Nuclear Waste is?

The effects are seen everywhere. And yet we continue to place an inordinate value upon information that locks us into repeated cycles of violence, destruction, and death. Given our long history of doing exactly the same thing with other commodities, this realisation should not and cannot be dismissed. The phrase ‘data is the new oil’ was apparently coined in 2006 by Clive Humby, the British mathematician and architect of the Tesco Clubcard, a supermarket reward programme.14 Since then, it has been repeated and amplified, first by marketers, then by entrepreneurs, and ultimately by business leaders and policy makers. In May 2017, the Economist devoted an entire issue to the proposition, declaring that ‘smartphones and the internet have made data abundant, ubiquitous and far more valuable … By collecting more data, a firm has more scope to improve its products, which attracts more users, generating even more data, and so on.’15 The president and CEO of Mastercard told an audience in Saudi Arabia, the world’s largest producer of actual oil, that data could be as effective as crude as a means of generating wealth (he also said it was a ‘public good’).16 In British parliamentary debates on leaving the European Union, data’s oily qualities were cited by Members of Parliament on both sides.17 Yet few such citations address the implications of long-term, systemic and global reliance on such a poisonous material, or the dubious circumstances of its extraction.


pages: 458 words: 116,832

The Costs of Connection: How Data Is Colonizing Human Life and Appropriating It for Capitalism by Nick Couldry, Ulises A. Mejias

"World Economic Forum" Davos, 23andMe, Airbnb, Amazon Mechanical Turk, Amazon Web Services, behavioural economics, Big Tech, British Empire, call centre, Cambridge Analytica, Cass Sunstein, choice architecture, cloud computing, colonial rule, computer vision, corporate governance, dark matter, data acquisition, data is the new oil, data science, deep learning, different worldview, digital capitalism, digital divide, discovery of the americas, disinformation, diversification, driverless car, Edward Snowden, emotional labour, en.wikipedia.org, European colonialism, Evgeny Morozov, extractivism, fake news, Gabriella Coleman, gamification, gig economy, global supply chain, Google Chrome, Google Earth, hiring and firing, income inequality, independent contractor, information asymmetry, Infrastructure as a Service, intangible asset, Internet of things, Jaron Lanier, job automation, Kevin Kelly, late capitalism, lifelogging, linked data, machine readable, Marc Andreessen, Mark Zuckerberg, means of production, military-industrial complex, move fast and break things, multi-sided market, Naomi Klein, Network effects, new economy, New Urbanism, PageRank, pattern recognition, payday loans, Philip Mirowski, profit maximization, Ray Kurzweil, RFID, Richard Stallman, Richard Thaler, Salesforce, scientific management, Scientific racism, Second Machine Age, sharing economy, Shoshana Zuboff, side hustle, Sidewalk Labs, Silicon Valley, Slavoj Žižek, smart cities, Snapchat, social graph, social intelligence, software studies, sovereign wealth fund, surveillance capitalism, techlash, The Future of Employment, the scientific method, Thomas Davenport, Tim Cook: Apple, trade liberalization, trade route, undersea cable, urban planning, W. E. B. Du Bois, wages for housework, work culture , workplace surveillance

Oxford, UK: Oxford University Press, 2005. . “The ‘New’ Imperialism: Accumulation by Dispossession.” Socialist Register 40 (2004): 63–87. . A Short History of Neoliberalism. New York: Oxford University Press, 2010. Haupt, Michael. “‘Data Is the New Oil’—A Ludicrous Proposition.” Twenty One Hundred, May 2, 2016. https://medium.com/twenty-one-hundred/data-is-the-new-oil-a-ludicrous-proposition. Hawkins, Amy. “Beijing’s Big Brother Tech Needs African Faces.” Foreign Policy (blog), July 24, 2018. https://foreignpolicy.com/2018/07/24/beijings-big-brother-tech-needs-african-faces/. Health and Safety Executive Statistics.

It is the by-product of social interactions that are mediated by digital technologies, a by-product that is captured and processed by a third party that is not intimately involved with the people in the interaction and indeed can operate at many removes from them through the market for selling data. The first use of the metaphor of data as the “new oil” is attributed to Clive Humby, the conceptual grandfather of the loyalty shopping-club card, who in 2006 said, “Data is the new oil. It’s valuable, but if unrefined it cannot really be used. It has to be changed into gas, plastic, chemicals, et cetera to create a valuable entity that drives profitable activity; so must data be broken down, analyzed for it to have value.”14 Data must thus be presented as an ownerless resource that can be exploited only by certain parties (what Julie Cohen calls data refineries).15 A few excerpts from a report by the Organization for Economic Cooperation and Development are worth quoting at length.

See Schiller, Digital Depression, 246; Thatcher, O’Sullivan, and Mahmoudi, “Data Colonialism”; Sassen, Expulsions; Zuboff, “Big Other,” 75–89; and Cohen, “Biopolitical Public Domain.” 10. Moore, Web of Life. 11. World Economic Forum, Personal Data. 12. Haupt, “A Ludicrous Proposition.” 13. World Economic Forum, Personal Data. 14. Palmer, “Data Is the New Oil.” 15. Cohen, “Biopolitical Public Domain.” 16. OECD, “Data-Driven,” 195–97. 17. Klein, This Changes Everything, 103. 18. Acosta, “Extractivismo y Neoextractivismo.” 19. In Klein, “Dancing the World.” 20. Morozov, “After the Facebook Scandal.” 21. Cohen, “Biopolitical Public Domain.” 22.


pages: 292 words: 76,185

Pivot: The Only Move That Matters Is Your Next One by Jenny Blake

Airbnb, Albert Einstein, Cal Newport, cloud computing, content marketing, data is the new oil, diversified portfolio, do what you love, East Village, en.wikipedia.org, Erik Brynjolfsson, fear of failure, future of work, high net worth, Jeff Bezos, job-hopping, Kevin Kelly, Khan Academy, knowledge worker, Lao Tzu, Lean Startup, minimum viable product, Nate Silver, passive income, Ralph Waldo Emerson, risk tolerance, Second Machine Age, sharing economy, side hustle, side project, Silicon Valley, Silicon Valley startup, Skype, Snapchat, software as a service, solopreneur, Startup school, stem cell, TED Talk, too big to fail, Tyler Cowen, white picket fence, young professional, zero-sum game

Chapter 7: Make Yourself Discoverable “Well-being is enhanced”: Brian R. Little, Me, Myself, and Us: The Science of Personality and the Art of Well-Being (New York: PublicAffairs, 2014), 196. suggests aiming for “1,000 True Fans”: Kevin Kelly, “1,000 True Fans,” KK.org, March 4, 2008, kk.org/thetechnium/1000-true-fans/. “data is the new oil”: Michael Palmer, “Data Is the New Oil,” ANA Marketing Maestros, November 3, 2006, ana.blogs.com/maestros/2006/11/data_is_the_new.html. STAGE THREE: PILOT “Making assumptions and then taking them personally”: Don Miguel Ruiz with Janet Mills, The Voice of Knowledge: A Practical Guide to Inner Peace (San Rafael, CA: Amber-Allen Publishing, 2004).

Aggregating and analyzing data, conducting original research: With increasingly more data available on everything from how many steps we take, to our heart rate, to mapping our genome, people will need help making sense of this data, “separating the signal from the noise,” as political pollster Nate Silver does. Some say that “data is the new oil” in our digital economy, and must be refined in order to add value. REVEL IN THE WORK OTHERS REJECT After four years at her PR firm, Amy Schoenberger, who you met in the introduction, started feeling uninspired. She knew that it was time to make a change; however, she loved her company, the culture, and the people, and she did not want to leave.


pages: 502 words: 107,657

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

Alan Greenspan, Albert Einstein, algorithmic trading, Amazon Mechanical Turk, Apollo 11, 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, data science, driverless car, en.wikipedia.org, Erik Brynjolfsson, Everything should be made as simple as possible, experimental subject, Google Glasses, happiness index / gross national happiness, information security, job satisfaction, Johann Wolfgang von Goethe, lifelogging, machine readable, 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, SpaceShipOne, speech recognition, statistical model, Steven Levy, supply chain finance, 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

The challenge is tackled by a systematic, scientific means to develop and continually improve prediction—to literally learn to predict. The solution is machine learning—computers automatically developing new knowledge and capabilities by furiously feeding on modern society’s greatest and most potent unnatural resource: data. “Feed Me!”—Food for Thought for the Machine Data is the new oil. —European Consumer Commissioner Meglena Kuneva The only source of knowledge is experience. —Albert Einstein In God we trust. All others must bring data. —William Edwards Deming (a business professor famous for work in manufacturing) Most people couldn’t be less interested in data. It can seem like such dry, boring stuff.

Budgeting the staff and tools for a PA project requires this leap, knowing not what specifically will be discovered and yet trusting that something will be. Sitting on an expert panel at Predictive Analytics World, leading UK consultant Tom Khabaza put it this way: “Projects never fail due to lack of patterns.” With The Data Effect in mind, the scientist rests easy. Data is the new oil. It’s this century’s greatest possession and often considered an organization’s most important strategic asset. Several thought leaders have dubbed it as such—“the new oil”—including European Consumer Commissioner Meglena Kuneva, who also calls it “the new currency of the digital world.” It’s not a hyperbole.

Olofson, Susan Feldman, Steve Conway, Matthew Eastwood, and Natalya Yezhkova, “Worldwide Big Data Technology and Services 2012–2012 Forecast,” ICD Analyze the Future, March 2012, Doc #233485. www.idc.com/getdoc.jsp?containerId=233485. The Prediction Effect: Tom Khabaza says, “There are always patterns.” Tom Khabaza, “Nine Laws of Data Mining—Part 2,” Data Mining & Predictive Analytics, edited by Tom Khabaza, January 14, 2012. http://khabaza.codimension.net/index_files/Page346.htm. “Personal data is the new oil of the Internet and the new currency of the digital world”: Meglena Kuneva, European Consumer Commissioner, March 2009, “Personal Data: The Emergence of a New Asset Class,” An Initiative of the World Economic Forum, January 2011. http://gerdleonhard.typepad.com/files/wef_ittc_personaldatanewasset_report_2011.pdf.


Demystifying Smart Cities by Anders Lisdorf

3D printing, artificial general intelligence, autonomous vehicles, backpropagation, behavioural economics, Big Tech, bike sharing, bitcoin, business intelligence, business logic, business process, chief data officer, circular economy, clean tech, clean water, cloud computing, computer vision, Computing Machinery and Intelligence, congestion pricing, continuous integration, crowdsourcing, data is the new oil, data science, deep learning, digital rights, digital twin, distributed ledger, don't be evil, Elon Musk, en.wikipedia.org, facts on the ground, Google Glasses, hydroponic farming, income inequality, information security, Infrastructure as a Service, Internet of things, Large Hadron Collider, Masdar, microservices, Minecraft, OSI model, platform as a service, pneumatic tube, ransomware, RFID, ride hailing / ride sharing, risk tolerance, Salesforce, self-driving car, smart cities, smart meter, software as a service, speech recognition, Stephen Hawking, Steve Jobs, Steve Wozniak, Stuxnet, Thomas Bayes, Turing test, urban sprawl, zero-sum game

We will consider what a device is and how they connect in distributed solutions. This is what is typically referred to as the Internet of Things. We look at the challenges of managing thousands or even millions of devices and what it takes to secure them. Chapter 4 is about data. Some say data is the new oil; regardless of whether that is true, it is a crucial aspect to understand since all data is not the same and needs to be secured and managed differently. Recent increased concern about privacy and exponential growth in unstructured sensor data will be addressed. Chapter 5 is about intelligence, in particular artificial intelligence (AI) .

It will sap the powers of those trying to innovate and will divert attention from things that are considered valuable in the organization. © Anders Lisdorf 2020 A. LisdorfDemystifying Smart Citieshttps://doi.org/10.1007/978-1-4842-5377-9_9 9. Build the data refinery: Because cities run on data Anders Lisdorf1 (1)Copenhagen, Denmark From raw data to useful information “Data is the new oil!” Mathematician and IT architect Clive Humby seems to have been the first to coin the phrase in 2006 where he helped Tesco develop from a fledgling UK retail chain to an intercontinental titan that rivals the likes of Walmart and Carrefour, through the use of data. This was done with the Tesco loyalty program that pioneered offers targeted to particular segments.


pages: 345 words: 75,660

Prediction Machines: The Simple Economics of Artificial Intelligence by Ajay Agrawal, Joshua Gans, Avi Goldfarb

Abraham Wald, Ada Lovelace, AI winter, Air France Flight 447, Airbus A320, algorithmic bias, AlphaGo, Amazon Picking Challenge, artificial general intelligence, autonomous vehicles, backpropagation, basic income, Bayesian statistics, Black Swan, blockchain, call centre, Capital in the Twenty-First Century by Thomas Piketty, Captain Sullenberger Hudson, carbon tax, Charles Babbage, classic study, collateralized debt obligation, computer age, creative destruction, Daniel Kahneman / Amos Tversky, data acquisition, data is the new oil, data science, deep learning, DeepMind, deskilling, disruptive innovation, driverless car, Elon Musk, en.wikipedia.org, Erik Brynjolfsson, everywhere but in the productivity statistics, financial engineering, fulfillment center, general purpose technology, Geoffrey Hinton, Google Glasses, high net worth, ImageNet competition, income inequality, information retrieval, inventory management, invisible hand, Jeff Hawkins, job automation, John Markoff, Joseph Schumpeter, Kevin Kelly, Lyft, Minecraft, Mitch Kapor, Moneyball by Michael Lewis explains big data, Nate Silver, new economy, Nick Bostrom, On the Economy of Machinery and Manufactures, OpenAI, paperclip maximiser, pattern recognition, performance metric, profit maximization, QWERTY keyboard, race to the bottom, randomized controlled trial, Ray Kurzweil, ride hailing / ride sharing, Robert Solow, Salesforce, Second Machine Age, self-driving car, shareholder value, Silicon Valley, statistical model, Stephen Hawking, Steve Jobs, Steve Jurvetson, Steven Levy, strong AI, The Future of Employment, the long tail, The Signal and the Noise by Nate Silver, Tim Cook: Apple, trolley problem, Turing test, Uber and Lyft, uber lyft, US Airways Flight 1549, Vernor Vinge, vertical integration, warehouse automation, warehouse robotics, Watson beat the top human players on Jeopardy!, William Langewiesche, Y Combinator, zero-sum game

First eBook Edition: Apr 2018 ISBN: 978-1-63369-567-2 eISBN: 978-1-63369-568-9 To our families, colleagues, students, and startups who inspired us to think clearly and deeply about artificial intelligence. Contents Cover Title Page Copyright Dedication Acknowledgments 1. Introduction: Machine Intelligence 2. Cheap Changes Everything Part One: Prediction 3. Prediction Machine Magic 4. Why It’s Called Intelligence 5. Data Is the New Oil 6. The New Division of Labor Part Two: Decision Making 7. Unpacking Decisions 8. The Value of Judgment 9. Predicting Judgment 10. Taming Complexity 11. Fully Automated Decision Making Part Three: Tools 12. Deconstructing Work Flows 13. Decomposing Decisions 14. Job Redesign Part Four: Strategy 15.

We remain agnostic on the link between prediction and intelligence. None of our conclusions rely on taking a position on whether advances in prediction represent advances in intelligence. We focus on the consequences of a drop in the cost of prediction, not a drop in the cost of intelligence. 5 Data Is the New Oil Hal Varian, the chief economist at Google, channeling Coca-Cola’s Robert Goizueta, said in 2013, “[A] billion hours ago, modern homo sapiens emerged. A billion minutes ago, Christianity began. A billion seconds ago, the IBM PC was released. A billion Google searches ago … was this morning.”1 Google isn’t the only company with extraordinary amounts of data.


pages: 288 words: 86,995

Rule of the Robots: How Artificial Intelligence Will Transform Everything by Martin Ford

AI winter, Airbnb, algorithmic bias, algorithmic trading, Alignment Problem, AlphaGo, Amazon Mechanical Turk, Amazon Web Services, artificial general intelligence, Automated Insights, autonomous vehicles, backpropagation, basic income, Big Tech, big-box store, call centre, carbon footprint, Chris Urmson, Claude Shannon: information theory, clean water, cloud computing, commoditize, computer age, computer vision, Computing Machinery and Intelligence, coronavirus, correlation does not imply causation, COVID-19, crowdsourcing, data is the new oil, data science, deep learning, deepfake, DeepMind, Demis Hassabis, deskilling, disruptive innovation, Donald Trump, Elon Musk, factory automation, fake news, fulfillment center, full employment, future of work, general purpose technology, Geoffrey Hinton, George Floyd, gig economy, Gini coefficient, global pandemic, Googley, GPT-3, high-speed rail, hype cycle, ImageNet competition, income inequality, independent contractor, industrial robot, informal economy, information retrieval, Intergovernmental Panel on Climate Change (IPCC), Internet of things, Jeff Bezos, job automation, John Markoff, Kiva Systems, knowledge worker, labor-force participation, Law of Accelerating Returns, license plate recognition, low interest rates, low-wage service sector, Lyft, machine readable, machine translation, Mark Zuckerberg, Mitch Kapor, natural language processing, Nick Bostrom, Northpointe / Correctional Offender Management Profiling for Alternative Sanctions, Ocado, OpenAI, opioid epidemic / opioid crisis, passive income, pattern recognition, Peter Thiel, Phillips curve, post scarcity, public intellectual, Ray Kurzweil, recommendation engine, remote working, RFID, ride hailing / ride sharing, Robert Gordon, Rodney Brooks, Rubik’s Cube, Sam Altman, self-driving car, Silicon Valley, Silicon Valley startup, social distancing, SoftBank, South of Market, San Francisco, special economic zone, speech recognition, stealth mode startup, Stephen Hawking, superintelligent machines, TED Talk, The Future of Employment, The Rise and Fall of American Growth, the scientific method, Turing machine, Turing test, Tyler Cowen, Tyler Cowen: Great Stagnation, Uber and Lyft, uber lyft, universal basic income, very high income, warehouse automation, warehouse robotics, Watson beat the top human players on Jeopardy!, WikiLeaks, women in the workforce, Y Combinator

However, it is generally limited to areas like web search, social media interactions and online shopping transactions. In these arenas, the established companies are likely to remain dominant, but far more data of completely different kinds resides across the economy and society, under the control of governments, organizations and businesses in other industries. It’s often said data is the new oil. If we embrace this analogy, then it’s fair to say that the tech companies in many ways fulfill a role similar to that of perhaps Halliburton, offering the technology and know-how required to extract value from the resource. The tech giants do, of course, also control huge data reserves of their own, but still the lion’s share of this ever-expanding global data resource lies in the hands of others.

While Google’s access to NHS data that was originally contracted to DeepMind immediately led to an outcry in the United Kingdom, Chinese tech companies generally benefit from a smoother path to implementation and profitability when it comes to leveraging artificial intelligence in areas like healthcare and education. If data is the new oil, then China’s AI entrepreneurs are new age wildcatters—drilling and erecting pumps to extract value at every promising location across a relatively unpoliced digital terrain. Even before the explosion of venture-backed AI startups, China’s major technology companies, especially Tencent, Alibaba and Baidu, were making massive investments in artificial intelligence research and development.


pages: 713 words: 93,944

Seven Databases in Seven Weeks: A Guide to Modern Databases and the NoSQL Movement by Eric Redmond, Jim Wilson, Jim R. Wilson

AGPL, Amazon Web Services, business logic, create, read, update, delete, data is the new oil, database schema, Debian, domain-specific language, en.wikipedia.org, fault tolerance, full text search, general-purpose programming language, Kickstarter, Large Hadron Collider, linked data, MVC pattern, natural language processing, node package manager, random walk, recommendation engine, Ruby on Rails, seminal paper, Skype, social graph, sparse data, web application

Also a special thanks to all the unsung heroes who monitor IRC, message boards, mailing lists, and bug systems ready to help anyone who needs you. Your dedication to open source keeps these projects kicking. Copyright © 2012, The Pragmatic Bookshelf. Preface It has been said that data is the new oil. If this is so, then databases are the fields, the refineries, the drills, and the pumps. Data is stored in databases, and if you’re interested in tapping into it, then coming to grips with the modern equipment is a great start. Databases are tools; they are the means to an end. Each database has its own story and its own way of looking at the world.

Spidering the graph quickly means you can’t afford network hops to other database nodes, so graph databases don’t scale out well. It’s likely that if you use a graph database, it’ll be one piece of a larger system, with the bulk of the data stored elsewhere and only the relationships maintained in the graph. 9.2 Making a Choice As we said at the beginning, data is the new oil. We sit upon a vast ocean of data, yet until it’s refined into information, it’s unusable (and with a more crude comparison, there’s a lot of money in data these days). The ease of collecting and ultimately storing, mining, and refining the data out there starts with the database you choose.


pages: 380 words: 109,724

Don't Be Evil: How Big Tech Betrayed Its Founding Principles--And All of US by Rana Foroohar

"Susan Fowler" uber, "World Economic Forum" Davos, accounting loophole / creative accounting, Airbnb, Alan Greenspan, algorithmic bias, algorithmic management, AltaVista, Andy Rubin, autonomous vehicles, banking crisis, barriers to entry, behavioural economics, Bernie Madoff, Bernie Sanders, Big Tech, bitcoin, Black Lives Matter, book scanning, Brewster Kahle, Burning Man, call centre, Cambridge Analytica, cashless society, clean tech, cloud computing, cognitive dissonance, Colonization of Mars, computer age, corporate governance, creative destruction, Credit Default Swap, cryptocurrency, data is the new oil, data science, deal flow, death of newspapers, decentralized internet, Deng Xiaoping, digital divide, digital rights, disinformation, disintermediation, don't be evil, Donald Trump, drone strike, Edward Snowden, Elon Musk, en.wikipedia.org, Erik Brynjolfsson, Etonian, Evgeny Morozov, fake news, Filter Bubble, financial engineering, future of work, Future Shock, game design, gig economy, global supply chain, Gordon Gekko, Great Leap Forward, greed is good, income inequality, independent contractor, informal economy, information asymmetry, intangible asset, Internet Archive, Internet of things, invisible hand, Jaron Lanier, Jeff Bezos, job automation, job satisfaction, junk bonds, Kenneth Rogoff, life extension, light touch regulation, low interest rates, Lyft, Mark Zuckerberg, Marshall McLuhan, Martin Wolf, Menlo Park, military-industrial complex, move fast and break things, Network effects, new economy, offshore financial centre, PageRank, patent troll, Paul Volcker talking about ATMs, paypal mafia, Peter Thiel, pets.com, price discrimination, profit maximization, race to the bottom, recommendation engine, ride hailing / ride sharing, Robert Bork, Sand Hill Road, search engine result page, self-driving car, shareholder value, sharing economy, Sheryl Sandberg, Shoshana Zuboff, side hustle, Sidewalk Labs, Silicon Valley, Silicon Valley startup, smart cities, Snapchat, SoftBank, South China Sea, sovereign wealth fund, Steve Bannon, Steve Jobs, Steven Levy, stock buybacks, subscription business, supply-chain management, surveillance capitalism, TaskRabbit, tech billionaire, tech worker, TED Talk, Telecommunications Act of 1996, The Chicago School, the long tail, the new new thing, Tim Cook: Apple, too big to fail, Travis Kalanick, trickle-down economics, Uber and Lyft, Uber for X, uber lyft, Upton Sinclair, warehouse robotics, WeWork, WikiLeaks, zero-sum game

That’s faster than in the online publishing, data processing, and information services industry itself, according to U.S. Bureau of Economic Analysis data. If the current trends hold, our data will be worth $197.7 billion by 2022—more than the total value of American agricultural output. That is resource extraction on a massive scale. If data is the new oil, then the United States is the Saudi Arabia of the digital era. The leading Internet platform companies are the new Aramco and ExxonMobil.54 Data is the new fuel for growth in multiple industries, from manufacturing to retail to financial services. But unlike other assets, it doesn’t necessarily fuel job growth, but rather, profit growth.

I’d argue that while we are spending the time to figure out exactly how to regulate and curb the power of Big Tech, we should also make sure that it isn’t mining our biggest natural resource for free. As we learned earlier in this book, the extraction of personal data is America’s fastest growing industry, one that will be worth $197.7 billion by 2022 if current trends hold—more than the total value of American agricultural output.5 If data is the new oil, then the United States is the Saudi Arabia of the digital era. The leading Internet platform companies are the new Aramco and ExxonMobil. But the tech platform companies are not the only ones in the digital surveillance business. Data brokers such as credit bureaus, healthcare firms, and credit card companies collect and sell all sorts of sensitive personal user data to other businesses and organizations that do not have the scale to collect it themselves.


Reset by Ronald J. Deibert

23andMe, active measures, air gap, Airbnb, Amazon Web Services, Anthropocene, augmented reality, availability heuristic, behavioural economics, Bellingcat, Big Tech, bitcoin, blockchain, blood diamond, Brexit referendum, Buckminster Fuller, business intelligence, Cal Newport, call centre, Cambridge Analytica, carbon footprint, cashless society, Citizen Lab, clean water, cloud computing, computer vision, confounding variable, contact tracing, contact tracing app, content marketing, coronavirus, corporate social responsibility, COVID-19, crowdsourcing, data acquisition, data is the new oil, decarbonisation, deep learning, deepfake, Deng Xiaoping, disinformation, Donald Trump, Doomsday Clock, dual-use technology, Edward Snowden, Elon Musk, en.wikipedia.org, end-to-end encryption, Evgeny Morozov, failed state, fake news, Future Shock, game design, gig economy, global pandemic, global supply chain, global village, Google Hangouts, Great Leap Forward, high-speed rail, income inequality, information retrieval, information security, Internet of things, Jaron Lanier, Jeff Bezos, John Markoff, Lewis Mumford, liberal capitalism, license plate recognition, lockdown, longitudinal study, Mark Zuckerberg, Marshall McLuhan, mass immigration, megastructure, meta-analysis, military-industrial complex, move fast and break things, Naomi Klein, natural language processing, New Journalism, NSO Group, off-the-grid, Peter Thiel, planetary scale, planned obsolescence, post-truth, proprietary trading, QAnon, ransomware, Robert Mercer, Sheryl Sandberg, Shoshana Zuboff, Silicon Valley, single source of truth, Skype, Snapchat, social distancing, sorting algorithm, source of truth, sovereign wealth fund, sparse data, speech recognition, Steve Bannon, Steve Jobs, Stuxnet, surveillance capitalism, techlash, technological solutionism, the long tail, the medium is the message, The Structural Transformation of the Public Sphere, TikTok, TSMC, undersea cable, unit 8200, Vannevar Bush, WikiLeaks, zero day, zero-sum game

There are deeper layers, like those legacy standards and protocols, that remain largely fixed. But caked on top of them is a bewildering array of new applications, features, and devices.14 Weaving through it all are rivers of data, some neatly contained in proper channels, others pouring through the cracks and crevices and spilling out in the form of data breaches. The phrase “data is the new oil” refers to the value to be gained from all the data that is routinely harvested by machines from both humans and other machines — the entire complex bristling with millions of pulsating data-sorting algorithms and sensors. The gradual rollout of fifth-generation cellular technology, known as 5G, will dramatically increase the speed and broadband capacity of cellular networks, fuelling an even greater volume of data circulating among a larger number of networked devices.

Research undertaken at the University of Massachusetts, Amherst, in which the researchers performed a life-cycle assessment for training several common large AI models, found that training a single AI model can emit more than 626,000 pounds of carbon dioxide equivalent — or nearly five times the lifetime emissions of the average American car (including its manufacturing).352 It’s become common to hear that “data is the new oil,” usually meaning that it is a valuable resource. Studies like these give the analogy an entirely different and disturbing connotation. While we are on the topic of analogies and metaphors, there is none more misleading than the omnipresent “cloud.” While “the cloud” brings to mind something intangible and unsubstantial, it is precisely the opposite when it comes to the data infrastructure that underpins our communications ecosystem.


pages: 222 words: 70,132

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

"Friedman doctrine" OR "shareholder theory", "there is no alternative" (TINA), 1960s counterculture, affirmative action, Affordable Care Act / Obamacare, Airbnb, AlphaGo, Amazon Mechanical Turk, American Legislative Exchange Council, AOL-Time Warner, Apple's 1984 Super Bowl advert, back-to-the-land, barriers to entry, basic income, battle of ideas, big data - Walmart - Pop Tarts, Big Tech, bitcoin, Brewster Kahle, Buckminster Fuller, Burning Man, Clayton Christensen, Cody Wilson, commoditize, content marketing, creative destruction, crony capitalism, crowdsourcing, data is the new oil, data science, David Brooks, David Graeber, decentralized internet, don't be evil, Donald Trump, Douglas Engelbart, Douglas Engelbart, Dynabook, Edward Snowden, Elon Musk, equal pay for equal work, Erik Brynjolfsson, Fairchild Semiconductor, fake news, future of journalism, future of work, George Akerlof, George Gilder, Golden age of television, Google bus, Hacker Ethic, Herbert Marcuse, Howard Rheingold, income inequality, informal economy, information asymmetry, information retrieval, Internet Archive, Internet of things, invisible hand, Jacob Silverman, Jaron Lanier, Jeff Bezos, job automation, John Markoff, John Maynard Keynes: technological unemployment, John Perry Barlow, John von Neumann, Joseph Schumpeter, Kevin Kelly, Kickstarter, labor-force participation, Larry Ellison, life extension, Marc Andreessen, Mark Zuckerberg, Max Levchin, Menlo Park, Metcalfe’s law, military-industrial complex, Mother of all demos, move fast and break things, natural language processing, Network effects, new economy, Norbert Wiener, offshore financial centre, packet switching, PalmPilot, Paul Graham, paypal mafia, Peter Thiel, plutocrats, pre–internet, Ray Kurzweil, reality distortion field, 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, Skinner box, smart grid, Snapchat, Social Justice Warrior, software is eating the world, Steve Bannon, Steve Jobs, Stewart Brand, tech billionaire, techno-determinism, technoutopianism, TED Talk, The Chicago School, the long tail, The Market for Lemons, The Rise and Fall of American Growth, Tim Cook: Apple, trade route, Tragedy of the Commons, transfer pricing, Travis Kalanick, trickle-down economics, Tyler Cowen, Tyler Cowen: Great Stagnation, universal basic income, unpaid internship, vertical integration, We are as Gods, We wanted flying cars, instead we got 140 characters, web application, Whole Earth Catalog, winner-take-all economy, women in the workforce, Y Combinator, you are the product

The answer is externalities. Like the Kochs, Google and Facebook are in the extraction industry—their business model is to extract as much personal data from as many people in the world at the lowest possible price and to resell that data to as many companies as possible at the highest possible price—data is the new oil. And like Koch Industries, Google and Facebook create externalities during the extraction process. Brewster Kahle, founder of the Internet Archive, outlined some of these externalities: Edward Snowden showed we’ve inadvertently built the world’s largest surveillance network with the web. China can make it impossible for people there to read things, and just a few big service providers are the de facto organizers of your experience.


pages: 281 words: 71,242

World Without Mind: The Existential Threat of Big Tech by Franklin Foer

artificial general intelligence, back-to-the-land, Berlin Wall, big data - Walmart - Pop Tarts, Big Tech, big-box store, Buckminster Fuller, citizen journalism, Colonization of Mars, computer age, creative destruction, crowdsourcing, data is the new oil, data science, deep learning, DeepMind, don't be evil, Donald Trump, Double Irish / Dutch Sandwich, Douglas Engelbart, driverless car, Edward Snowden, Electric Kool-Aid Acid Test, Elon Musk, Evgeny Morozov, Fall of the Berlin Wall, Filter Bubble, Geoffrey Hinton, global village, Google Glasses, Haight Ashbury, hive mind, income inequality, intangible asset, Jeff Bezos, job automation, John Markoff, Kevin Kelly, knowledge economy, Law of Accelerating Returns, Marc Andreessen, Mark Zuckerberg, Marshall McLuhan, means of production, move fast and break things, new economy, New Journalism, Norbert Wiener, off-the-grid, offshore financial centre, PageRank, Peace of Westphalia, Peter Thiel, planetary scale, Ray Kurzweil, scientific management, self-driving car, Silicon Valley, Singularitarianism, software is eating the world, Steve Jobs, Steven Levy, Stewart Brand, strong AI, supply-chain management, TED Talk, the medium is the message, the scientific method, The Wealth of Nations by Adam Smith, The Wisdom of Crowds, Thomas L Friedman, Thorstein Veblen, Upton Sinclair, Vernor Vinge, vertical integration, We are as Gods, Whole Earth Catalog, yellow journalism

We need to entertain the possibility that the monopolies of our day may be even more firmly entrenched than the giants in whose path they stride. One of the reasons for the growing distance between the tech companies and their competition is that they have such a large stockpile of a precious asset. • • • ONE OF THE CLICHÉS OF OUR TIME: Data is the new oil. This felt like hyperbole when first articulated, but now feels perfectly apt. “Data” is a bloodless word, but what it represents is hardly bloodless. It’s the record of our actions: what we read, what we watch, where we travel over the course of a day, what we purchase, our correspondence, our search inquiries, the thoughts we begin to type and then delete.


pages: 239 words: 70,206

Data-Ism: The Revolution Transforming Decision Making, Consumer Behavior, and Almost Everything Else by Steve Lohr

"World Economic Forum" Davos, 23andMe, Abraham Maslow, Affordable Care Act / Obamacare, Albert Einstein, Alvin Toffler, Bear Stearns, behavioural economics, big data - Walmart - Pop Tarts, bioinformatics, business cycle, business intelligence, call centre, Carl Icahn, classic study, cloud computing, computer age, conceptual framework, Credit Default Swap, crowdsourcing, Daniel Kahneman / Amos Tversky, Danny Hillis, data is the new oil, data science, David Brooks, driverless car, East Village, Edward Snowden, Emanuel Derman, Erik Brynjolfsson, everywhere but in the productivity statistics, financial engineering, Frederick Winslow Taylor, Future Shock, Google Glasses, Ida Tarbell, impulse control, income inequality, indoor plumbing, industrial robot, informal economy, Internet of things, invention of writing, Johannes Kepler, John Markoff, John von Neumann, lifelogging, machine translation, Mark Zuckerberg, market bubble, meta-analysis, money market fund, natural language processing, obamacare, pattern recognition, payday loans, personalized medicine, planned obsolescence, precision agriculture, pre–internet, Productivity paradox, RAND corporation, rising living standards, Robert Gordon, Robert Solow, Salesforce, scientific management, Second Machine Age, self-driving car, Silicon Valley, Silicon Valley startup, SimCity, six sigma, skunkworks, speech recognition, statistical model, Steve Jobs, Steven Levy, The Design of Experiments, the scientific method, Thomas Kuhn: the structure of scientific revolutions, Tony Fadell, unbanked and underbanked, underbanked, Von Neumann architecture, Watson beat the top human players on Jeopardy!, yottabyte

“Now, it’s getting to be valuable.” In September 2014, Zhou left IBM to start her own company. The idea, she says, is inspired by the work she did at IBM, and researchers there will continue to pursue the underlying technologies she developed in service of corporations. But Zhou has her eye on the consumer market. If data is the new oil, she says, then we are all data wells, and potentially valuable ones. The data-infused profiles of a person’s traits and values, Zhou says, should be exploited by the individual as a kind of currency in exchange for truly personalized products, services, and advice from businesses, with tailored pricing as well.


Work in the Future The Automation Revolution-Palgrave MacMillan (2019) by Robert Skidelsky Nan Craig

3D printing, Airbnb, algorithmic trading, AlphaGo, Alvin Toffler, Amazon Web Services, anti-work, antiwork, artificial general intelligence, asset light, autonomous vehicles, basic income, behavioural economics, business cycle, cloud computing, collective bargaining, Computing Machinery and Intelligence, correlation does not imply causation, creative destruction, data is the new oil, data science, David Graeber, David Ricardo: comparative advantage, deep learning, DeepMind, deindustrialization, Demis Hassabis, deskilling, disintermediation, do what you love, Donald Trump, driverless car, Erik Brynjolfsson, fake news, feminist movement, Ford Model T, Frederick Winslow Taylor, future of work, Future Shock, general purpose technology, gig economy, global supply chain, income inequality, independent contractor, informal economy, Internet of things, Jarndyce and Jarndyce, Jarndyce and Jarndyce, job automation, job polarisation, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, John von Neumann, Joseph Schumpeter, knowledge economy, Loebner Prize, low skilled workers, Lyft, Mark Zuckerberg, means of production, moral panic, Network effects, new economy, Nick Bostrom, off grid, pattern recognition, post-work, Ronald Coase, scientific management, Second Machine Age, self-driving car, sharing economy, SoftBank, Steve Jobs, strong AI, tacit knowledge, technological determinism, technoutopianism, TED Talk, The Chicago School, The Future of Employment, the market place, The Nature of the Firm, The Wealth of Nations by Adam Smith, Thorstein Veblen, Turing test, Uber for X, uber lyft, universal basic income, wealth creators, working poor

The other aspect that leads to a monopoly is the ability to extract and control data. By situating themselves between all these different groups, platforms position themselves in a space where they can collect a lot of data. Any interaction that happens on the platform becomes a piece of information that can then be fed into things like machine learning. If data is the new oil, platforms are the new oil rigs. Their intermediary nature allows them to build a moat around their business since as they collect more and more data, it become increasingly difficult for the competitors to beat them. The result is again a tendency towards monopolisation, as the data-rich get richer.


pages: 269 words: 70,543

Tech Titans of China: How China's Tech Sector Is Challenging the World by Innovating Faster, Working Harder, and Going Global by Rebecca Fannin

"World Economic Forum" Davos, Adam Neumann (WeWork), Airbnb, augmented reality, autonomous vehicles, Benchmark Capital, Big Tech, bike sharing, blockchain, call centre, cashless society, Chuck Templeton: OpenTable:, clean tech, cloud computing, computer vision, connected car, corporate governance, cryptocurrency, data is the new oil, data science, deep learning, Deng Xiaoping, Didi Chuxing, digital map, disruptive innovation, Donald Trump, El Camino Real, electricity market, Elon Musk, fake news, family office, fear of failure, fulfillment center, glass ceiling, global supply chain, Great Leap Forward, income inequality, industrial robot, information security, Internet of things, invention of movable type, Jeff Bezos, Kickstarter, knowledge worker, Lyft, Mark Zuckerberg, Mary Meeker, megacity, Menlo Park, money market fund, Network effects, new economy, peer-to-peer lending, personalized medicine, Peter Thiel, QR code, RFID, ride hailing / ride sharing, Sand Hill Road, self-driving car, sharing economy, Shenzhen was a fishing village, Silicon Valley, Silicon Valley startup, Skype, smart cities, smart transportation, Snapchat, social graph, SoftBank, software as a service, South China Sea, sovereign wealth fund, speech recognition, stealth mode startup, Steve Jobs, stock buybacks, supply-chain management, tech billionaire, TechCrunch disrupt, TikTok, Tim Cook: Apple, Travis Kalanick, Uber and Lyft, Uber for X, uber lyft, urban planning, Vision Fund, warehouse automation, WeWork, winner-take-all economy, Y Combinator, young professional

But he emphasizes that China is catching up at an astonishingly rapid rate in implementing the technology in practical ways. China has an advantage based on large numbers of well-trained AI talent, a supportive government policy, and access to a vast amount of data sets powering AI and gleaned from China’s world-leading number of internet and mobile phone users, he notes. In the age of AI, data is the new oil, so China is the new Saudi Arabia, says Lee, author of AI Superpowers.4 His venture investment firm in Beijing, Sinovation Ventures, which I’ve visited multiple times, is betting on AI’s future. Lee, who is widely known for his pioneering work in speech recognition and artificial intelligence, is an investor in five Chinese AI companies worth more than $1 billion.


pages: 250 words: 79,360

Escape From Model Land: How Mathematical Models Can Lead Us Astray and What We Can Do About It by Erica Thompson

Alan Greenspan, Bayesian statistics, behavioural economics, Big Tech, Black Swan, butterfly effect, carbon tax, coronavirus, correlation does not imply causation, COVID-19, data is the new oil, data science, decarbonisation, DeepMind, Donald Trump, Drosophila, Emanuel Derman, Financial Modelers Manifesto, fudge factor, germ theory of disease, global pandemic, hindcast, I will remember that I didn’t make the world, and it doesn’t satisfy my equations, implied volatility, Intergovernmental Panel on Climate Change (IPCC), John von Neumann, junk bonds, Kim Stanley Robinson, lockdown, Long Term Capital Management, moral hazard, mouse model, Myron Scholes, Nate Silver, Neal Stephenson, negative emissions, paperclip maximiser, precautionary principle, RAND corporation, random walk, risk tolerance, selection bias, self-driving car, social distancing, Stanford marshmallow experiment, statistical model, systematic bias, tacit knowledge, tail risk, TED Talk, The Great Moderation, The Great Resignation, the scientific method, too big to fail, trolley problem, value at risk, volatility smile, Y2K

Not just in science, but those who are doing any kind of quantitative analytics: actuaries, financial traders, energy forecasters, start-up founders, humanitarian responders, public health analysts, environmental consultants, social-media marketers, bookies, sports teams – you name it! Models are ubiquitous now in everyday life, analysing and interpreting rivers of data gathered in many different ways from personal devices to satellites. If ‘data is the new oil’, then models are the new pipelines – and they are also refineries. How are models constructed? To whom do they deliver power? How should we regulate them? How can we use them responsibly? I do not have final answers to these questions, but I hope that this book can help to address them: first, by reframing generic worries about models into more specific and tractable questions; second, by emphasising that the social and political content of models is at least as important as their mathematical and statistical content; and third, by offering a guide to some of the routes by which we can escape from Model Land. 2 Thinking Inside the Box There are more things in heaven and earth, Horatio, Than are dreamt of in your philosophy.


pages: 677 words: 206,548

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

23andMe, 3D printing, active measures, additive manufacturing, Affordable Care Act / Obamacare, Airbnb, airport security, Albert Einstein, algorithmic trading, Alvin Toffler, Apollo 11, Apollo 13, artificial general intelligence, Asilomar, Asilomar Conference on Recombinant DNA, augmented reality, autonomous vehicles, Baxter: Rethink Robotics, Bill Joy: nanobots, bitcoin, Black Swan, blockchain, borderless world, Boston Dynamics, Brian Krebs, business process, butterfly effect, call centre, Charles Lindbergh, Chelsea Manning, Citizen Lab, cloud computing, Cody Wilson, cognitive dissonance, computer vision, connected car, corporate governance, crowdsourcing, cryptocurrency, data acquisition, data is the new oil, data science, Dean Kamen, deep learning, DeepMind, digital rights, disinformation, disintermediation, Dogecoin, don't be evil, double helix, Downton Abbey, driverless car, drone strike, Edward Snowden, Elon Musk, Erik Brynjolfsson, Evgeny Morozov, Filter Bubble, Firefox, Flash crash, Free Software Foundation, future of work, game design, gamification, global pandemic, Google Chrome, Google Earth, Google Glasses, Gordon Gekko, Hacker News, high net worth, High speed trading, hive mind, Howard Rheingold, hypertext link, illegal immigration, impulse control, industrial robot, information security, Intergovernmental Panel on Climate Change (IPCC), Internet of things, Jaron Lanier, Jeff Bezos, job automation, John Harrison: Longitude, John Markoff, Joi Ito, Jony Ive, Julian Assange, Kevin Kelly, Khan Academy, Kickstarter, Kiva Systems, knowledge worker, Kuwabatake Sanjuro: assassination market, Large Hadron Collider, Larry Ellison, Laura Poitras, Law of Accelerating Returns, Lean Startup, license plate recognition, lifelogging, litecoin, low earth orbit, M-Pesa, machine translation, Mark Zuckerberg, Marshall McLuhan, Menlo Park, Metcalfe’s law, MITM: man-in-the-middle, mobile money, more computing power than Apollo, move fast and break things, Nate Silver, national security letter, natural language processing, Nick Bostrom, obamacare, Occupy movement, Oculus Rift, off grid, off-the-grid, offshore financial centre, operational security, optical character recognition, Parag Khanna, pattern recognition, peer-to-peer, personalized medicine, Peter H. Diamandis: Planetary Resources, Peter Thiel, pre–internet, printed gun, RAND corporation, ransomware, Ray Kurzweil, Recombinant DNA, refrigerator car, RFID, ride hailing / ride sharing, Rodney Brooks, Ross Ulbricht, Russell Brand, Salesforce, Satoshi Nakamoto, Second Machine Age, security theater, self-driving car, shareholder value, Sheryl Sandberg, Silicon Valley, Silicon Valley startup, SimCity, Skype, smart cities, smart grid, smart meter, Snapchat, social graph, SoftBank, software as a service, speech recognition, stealth mode startup, Stephen Hawking, Steve Jobs, Steve Wozniak, strong AI, Stuxnet, subscription business, supply-chain management, synthetic biology, tech worker, technological singularity, TED Talk, telepresence, telepresence robot, Tesla Model S, The future is already here, The Future of Employment, the long tail, The Wisdom of Crowds, Tim Cook: Apple, trade route, uranium enrichment, Virgin Galactic, Wall-E, warehouse robotics, Watson beat the top human players on Jeopardy!, Wave and Pay, We are Anonymous. We are Legion, web application, Westphalian system, WikiLeaks, Y Combinator, you are the product, zero day

There’s an App for That Location, Location, Location CHAPTER 5: THE SURVEILLANCE ECONOMY You Thought Hackers Were Bad? Meet the Data Brokers Analyzing You But I’ve Got Nothing to Hide Privacy Risks and Other Unpleasant Surprises Opening Pandora’s Virtual Box Knowledge Is Power, Code Is King, and Orwell Was Right CHAPTER 6: BIG DATA, BIG RISK Data Is the New Oil Bad Stewards, Good Victims, or Both? Data Brokers Are Poor Stewards of Your Data Too Social Networking Ills Illicit Data: The Lifeblood of Identity Theft Stalkers, Bullies, and Exes—Oh My! Online Threats to Minors Haters Gonna Hate Burglary 2.0 Targeted Scams and Targeted Killings Counterintelligence Implications of Leaked Government Data So No Online Profile Is Better, Right?

LeT simply processed the data the public was leaking and leveraged them in real time to kill more people and outmaneuver authorities. That was terrorism in the digital age circa 2008. What might terrorists do with the technologies available today? What will they do with the technologies of tomorrow? The lesson of Mumbai is that exponential change applies not just for good but for evil as well. Data Is the New Oil Data is constantly being generated by everything around us. Every digital process, sensor, mobile phone, GPS device, car engine, medical lab test, credit card transaction, hotel door lock, report card, and social media exchange produces data. Smart phones are turning human beings into human sensors, generating vast sums of information about us.


pages: 282 words: 81,873

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

"World Economic Forum" Davos, 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, Big Tech, bitcoin, Bitcoin Ponzi scheme, Build a better mousetrap, California gold rush, cashless society, colonial rule, computer age, cryptocurrency, data is the new oil, deep learning, digital nomad, disruptive innovation, Donald Trump, Douglas Hofstadter, driverless car, Elon Musk, Evgeny Morozov, Extropian, fail fast, fake it until you make it, fake news, gamification, gentrification, gig economy, Google bus, Google Glasses, Google X / Alphabet X, Greyball, growth hacking, hacker house, Hacker News, hive mind, illegal immigration, immigration reform, independent contractor, intentional community, Internet of things, invisible hand, Isaac Newton, Jeff Bezos, job automation, Kevin Kelly, Khan Academy, Larry Ellison, 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, mutually assured destruction, Neal Stephenson, obamacare, Parker Conrad, passive income, patent troll, Patri Friedman, Paul Graham, peer-to-peer lending, Peter H. Diamandis: Planetary Resources, Peter Thiel, platform as a service, plutocrats, Ponzi scheme, post-work, public intellectual, 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, selling pickaxes during a gold rush, sharing economy, side project, Silicon Valley, Silicon Valley billionaire, Silicon Valley startup, Singularitarianism, Skype, Snapchat, Social Justice Warrior, social software, software as a service, source of truth, South of Market, San Francisco, Startup school, stealth mode startup, Steve Bannon, Steve Jobs, Steve Wozniak, TaskRabbit, tech billionaire, tech bro, tech worker, TechCrunch disrupt, technological singularity, technoutopianism, telepresence, too big to fail, Travis Kalanick, tulip mania, Tyler Cowen, Uber for X, uber lyft, ubercab, unit 8200, upwardly mobile, Vernor Vinge, vertical integration, Virgin Galactic, X Prize, Y Combinator, Zenefits

Shouldn’t you be working? Why are you reading this? Click. Swipe. Share. We insist. Anxious? Have some dopamine. Ding! Have some more. Boredom was once possible. Idle hands made tremendous things. Today, no one is idle. Everybody’s working, even when they tell themselves they’re taking a break. It is said that “data is the new oil.” But we are the data; the new oil is us. And unlike oil, we are a renewable resource. The startup bubble that began around 2005 ended approximately twelve years later without fanfare. Easy money for half-baked startups dried up, as did the initial public stock offerings of overhyped companies.


pages: 308 words: 85,880

How to Fix the Future: Staying Human in the Digital Age by Andrew Keen

"World Economic Forum" Davos, 23andMe, Ada Lovelace, Affordable Care Act / Obamacare, Airbnb, Albert Einstein, AlphaGo, Andrew Keen, Apple's 1984 Super Bowl advert, augmented reality, autonomous vehicles, basic income, Bernie Sanders, Big Tech, bitcoin, Black Swan, blockchain, Brewster Kahle, British Empire, carbon tax, Charles Babbage, computer age, Cornelius Vanderbilt, creative destruction, crowdsourcing, data is the new oil, death from overwork, DeepMind, Demis Hassabis, Didi Chuxing, digital capitalism, digital map, digital rights, disinformation, don't be evil, Donald Trump, driverless car, Edward Snowden, Elon Musk, Erik Brynjolfsson, European colonialism, fake news, Filter Bubble, Firefox, fulfillment center, full employment, future of work, gig economy, global village, income inequality, independent contractor, informal economy, Internet Archive, Internet of things, invisible hand, Isaac Newton, James Watt: steam engine, Jane Jacobs, Jaron Lanier, Jeff Bezos, jimmy wales, job automation, Joi Ito, Kevin Kelly, knowledge economy, Lyft, Marc Andreessen, Marc Benioff, Mark Zuckerberg, Marshall McLuhan, Menlo Park, Mitch Kapor, move fast and break things, Network effects, new economy, Nicholas Carr, Norbert Wiener, OpenAI, Parag Khanna, peer-to-peer, Peter Thiel, plutocrats, post-truth, postindustrial economy, precariat, Ralph Nader, Ray Kurzweil, Recombinant DNA, rent-seeking, ride hailing / ride sharing, Rutger Bregman, Salesforce, Sam Altman, Sand Hill Road, Second Machine Age, self-driving car, sharing economy, Silicon Valley, Silicon Valley billionaire, Silicon Valley ideology, Silicon Valley startup, Skype, smart cities, Snapchat, social graph, software is eating the world, Stephen Hawking, Steve Jobs, Steve Wozniak, subscription business, surveillance capitalism, Susan Wojcicki, tech baron, tech billionaire, tech worker, technological determinism, technoutopianism, The Future of Employment, the High Line, the new new thing, Thomas L Friedman, Tim Cook: Apple, Travis Kalanick, Triangle Shirtwaist Factory, Uber and Lyft, Uber for X, uber lyft, universal basic income, Unsafe at Any Speed, Upton Sinclair, urban planning, WikiLeaks, winner-take-all economy, Y Combinator, Yogi Berra, Zipcar

Astra Taylor, The People’s Platform: Taking Back Power and Culture in the Digital Age (Metropolitan Books, 2014). 7. Jaron Lanier, Who Owns the Future? (Simon & Schuster, 2013), 336. 8. Keen, The Internet Is Not the Answer, 27–28. 9. Ibid., 182. 10. Geoff Descreumaux, “One Minute on the Internet in 2016,” wersm.com, April 22, 2016. 11. The idea that “data is the new oil” has been expressed by numerous pundits including Meglena Kuneva, the European consumer commissioner; the Silicon Valley venture capitalist Ann Winblad; and the IBM CEO Virginia Rometty. 12. John Gapper, “LinkedIn Swaps Business Cards with Microsoft,” Financial Times, June 15, 2016. 13. Quentin Hardy, “The Web’s Creator Looks to Reinvent It,” New York Times, June 7, 2016. 14.


pages: 295 words: 87,204

The Capitalist Manifesto by Johan Norberg

AltaVista, anti-communist, barriers to entry, Berlin Wall, Bernie Sanders, Big Tech, Boris Johnson, business climate, business cycle, capital controls, Capital in the Twenty-First Century by Thomas Piketty, carbon footprint, carbon tax, Charles Babbage, computer age, coronavirus, COVID-19, creative destruction, crony capitalism, data is not the new oil, data is the new oil, David Graeber, DeepMind, degrowth, deindustrialization, Deng Xiaoping, digital map, disinformation, Donald Trump, Elon Musk, energy transition, Erik Brynjolfsson, export processing zone, failed state, Filter Bubble, gig economy, Gini coefficient, global supply chain, Google Glasses, Greta Thunberg, Gunnar Myrdal, Hans Rosling, Hernando de Soto, Howard Zinn, income inequality, independent contractor, index fund, Indoor air pollution, industrial robot, Intergovernmental Panel on Climate Change (IPCC), invention of the printing press, invisible hand, Jeff Bezos, Jeremy Corbyn, job automation, job satisfaction, Joseph Schumpeter, land reform, liberal capitalism, lockdown, low cost airline, low interest rates, low skilled workers, Lyft, manufacturing employment, Mark Zuckerberg, means of production, meta-analysis, Minecraft, multiplanetary species, Naomi Klein, Neal Stephenson, Nelson Mandela, Network effects, open economy, passive income, Paul Graham, Paul Samuelson, payday loans, planned obsolescence, precariat, profit motive, Ralph Nader, RAND corporation, rent control, rewilding, ride hailing / ride sharing, Ronald Coase, Rosa Parks, Salesforce, Sam Bankman-Fried, Shenzhen was a fishing village, Silicon Valley, Simon Kuznets, Snapchat, social distancing, social intelligence, South China Sea, Stephen Fry, Steve Jobs, tech billionaire, The Spirit Level, The Wealth of Nations by Adam Smith, TikTok, Tim Cook: Apple, total factor productivity, trade liberalization, transatlantic slave trade, Tyler Cowen, Uber and Lyft, uber lyft, ultimatum game, Virgin Galactic, Washington Consensus, working-age population, World Values Survey, X Prize, you are the product, zero-sum game

These companies can take advantage of spectacular network effects. You have to be on Facebook because so many people are already there, and when you join, the platform becomes even more indispensable for others. Then Facebook gets more and more data, which means they can tailor their services and their ads to even more people. Data is the new oil, so success breeds success for social media, search engines, map services, e-commerce, payment apps, streaming, app-based taxi services and other digital services. At the same time, the debate about social media has taken a very dark turn. What was once considered the salvation of democracy is now more often seen as its gravedigger.


Data Action: Using Data for Public Good by Sarah Williams

affirmative action, Amazon Mechanical Turk, Andrei Shleifer, augmented reality, autonomous vehicles, Brexit referendum, Cambridge Analytica, Charles Babbage, City Beautiful movement, commoditize, coronavirus, COVID-19, crowdsourcing, data acquisition, data is the new oil, data philanthropy, data science, digital divide, digital twin, Donald Trump, driverless car, Edward Glaeser, fake news, four colour theorem, global village, Google Earth, informal economy, Internet of things, Jane Jacobs, John Snow's cholera map, Kibera, Lewis Mumford, Marshall McLuhan, mass immigration, mass incarceration, megacity, military-industrial complex, Minecraft, neoliberal agenda, New Urbanism, Norbert Wiener, nowcasting, oil shale / tar sands, openstreetmap, place-making, precautionary principle, RAND corporation, ride hailing / ride sharing, selection bias, self-driving car, sentiment analysis, Sidewalk Labs, smart cities, Smart Cities: Big Data, Civic Hackers, and the Quest for a New Utopia, Steven Levy, the built environment, The Chicago School, The Death and Life of Great American Cities, transatlantic slave trade, Uber for X, upwardly mobile, urban planning, urban renewal, W. E. B. Du Bois, Works Progress Administration

In a recent book about the topic, The Costs of Connection: How Data is Colonizing Human Life Appropriating It for Capitalism, the authors Nick Couldry and Ulises Mejias define data colonialism as “the extension of the global process of extraction that started under colonialism and continued through industrial capitalism, culminating in today's new form: instead of natural resources and labor, what is now being appropriated is human life through the conversation into data.” 9 It is we, the world's citizens, who collectively make the data they are referring to by providing large corporations and many smaller ones with detailed information of every moment of our lives: everything from our real-time geo-location to our email records, most of it time-stamped. That data belongs to companies who log and package it to sell it as a product to others for everything from ad targeting to improving transport services. We might have heard it said that “data is the new oil”—and, according to the authors of The Costs of Connection, we are little drops of oil, being exploited for profit and control. Similarly, as the authors of Compromised Data express it in their book on the topic: “data is being employed to accelerate prevalent neoliberal redefinitions of the role of the state and the transformation of citizenship into consumer practices.” 10 The concept of data colonialism is hard to wrap your head around, so I will attempt to share my view on its meaning.


pages: 337 words: 103,522

The Creativity Code: How AI Is Learning to Write, Paint and Think by Marcus Du Sautoy

3D printing, Ada Lovelace, Albert Einstein, algorithmic bias, AlphaGo, Alvin Roth, Andrew Wiles, Automated Insights, Benoit Mandelbrot, Bletchley Park, Cambridge Analytica, Charles Babbage, Claude Shannon: information theory, computer vision, Computing Machinery and Intelligence, correlation does not imply causation, crowdsourcing, data is the new oil, data science, deep learning, DeepMind, Demis Hassabis, Donald Trump, double helix, Douglas Hofstadter, driverless car, Elon Musk, Erik Brynjolfsson, Fellow of the Royal Society, Flash crash, Gödel, Escher, Bach, Henri Poincaré, Jacquard loom, John Conway, Kickstarter, Loebner Prize, machine translation, mandelbrot fractal, Minecraft, move 37, music of the spheres, Mustafa Suleyman, Narrative Science, natural language processing, Netflix Prize, PageRank, pattern recognition, Paul Erdős, Peter Thiel, random walk, Ray Kurzweil, recommendation engine, Rubik’s Cube, Second Machine Age, Silicon Valley, speech recognition, stable marriage problem, Turing test, Watson beat the top human players on Jeopardy!, wikimedia commons

One of the users said she was a closet lesbian mother and that the data about her movie preferences could have revealed this fact. That you might be able to infer sexual orientation or political leanings from your movie preferences has led to this being called the Brokeback Mountain factor. Eventually the case was settled out of court, but it led to Netflix cancelling the second round of the competition. Data is the new oil, but we are spilling it all over the internet. Who owns that data and what can be done with it is going to be a major question for society as we head into a future fuelled by this oil. How to train your algorithm You may feel there is something scary about algorithms telling you what you might like if it means you will never see things it thinks you won’t like.


pages: 346 words: 97,330

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

"World Economic Forum" Davos, Affordable Care Act / Obamacare, AlphaGo, Amazon Mechanical Turk, Apollo 13, augmented reality, autonomous vehicles, barriers to entry, basic income, benefit corporation, Big Tech, 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, cognitive load, collaborative consumption, collective bargaining, computer vision, corporate social responsibility, cotton gin, crowdsourcing, data is the new oil, data science, deep learning, DeepMind, deindustrialization, deskilling, digital divide, do well by doing good, do what you love, don't be evil, Donald Trump, Elon Musk, employer provided health coverage, en.wikipedia.org, equal pay for equal work, Erik Brynjolfsson, fake news, financial independence, Frank Levy and Richard Murnane: The New Division of Labor, fulfillment center, future of work, gig economy, glass ceiling, global supply chain, hiring and firing, ImageNet competition, independent contractor, industrial robot, informal economy, information asymmetry, Jeff Bezos, job automation, knowledge economy, low skilled workers, low-wage service sector, machine translation, market friction, Mars Rover, natural language processing, new economy, operational security, passive income, pattern recognition, post-materialism, post-work, power law, race to the bottom, Rana Plaza, recommendation engine, ride hailing / ride sharing, Ronald Coase, scientific management, search costs, 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, TED Talk, The Future of Employment, The Nature of the Firm, Tragedy of the Commons, transaction costs, two-sided market, union organizing, universal basic income, Vilfredo Pareto, Wayback Machine, women in the workforce, work culture , Works Progress Administration, Y Combinator, Yochai Benkler

They also rely on people doing ghost work to improve their services’ algorithms and artificial intelligence by cleaning up training data from large stores of proprietary data. Tech companies collect and archive information about how people use their sites. Data such as top search-query terms, popular song choices, and mouse cursor movements can be harvested to fuel product development. If customer data is the new oil, the people doing ghost work operate the rigs. The biggest difference between MTurk and tech companies’ internal platforms, like UHRS, is that MTurk recruits and sells labor as well as the platform work site itself, while, on big tech companies’ platforms, a third party—a vendor management system (VMS)—recruits and supplies ghost work labor.


pages: 362 words: 97,288

Ghost Road: Beyond the Driverless Car by Anthony M. Townsend

A Pattern Language, active measures, AI winter, algorithmic trading, Alvin Toffler, Amazon Robotics, asset-backed security, augmented reality, autonomous vehicles, backpropagation, big-box store, bike sharing, Blitzscaling, Boston Dynamics, business process, Captain Sullenberger Hudson, car-free, carbon footprint, carbon tax, circular economy, company town, computer vision, conceptual framework, congestion charging, congestion pricing, connected car, creative destruction, crew resource management, crowdsourcing, DARPA: Urban Challenge, data is the new oil, Dean Kamen, deep learning, deepfake, deindustrialization, delayed gratification, deliberate practice, dematerialisation, deskilling, Didi Chuxing, drive until you qualify, driverless car, drop ship, Edward Glaeser, Elaine Herzberg, Elon Musk, en.wikipedia.org, extreme commuting, financial engineering, financial innovation, Flash crash, food desert, Ford Model T, fulfillment center, Future Shock, General Motors Futurama, gig economy, Google bus, Greyball, haute couture, helicopter parent, independent contractor, inventory management, invisible hand, Jane Jacobs, Jeff Bezos, Jevons paradox, jitney, job automation, John Markoff, John von Neumann, Joseph Schumpeter, Kickstarter, Kiva Systems, Lewis Mumford, loss aversion, Lyft, Masayoshi Son, megacity, microapartment, minimum viable product, mortgage debt, New Urbanism, Nick Bostrom, North Sea oil, Ocado, openstreetmap, pattern recognition, Peter Calthorpe, random walk, Ray Kurzweil, Ray Oldenburg, rent-seeking, ride hailing / ride sharing, Rodney Brooks, self-driving car, sharing economy, Shoshana Zuboff, Sidewalk Labs, Silicon Valley, Silicon Valley startup, Skype, smart cities, Smart Cities: Big Data, Civic Hackers, and the Quest for a New Utopia, SoftBank, software as a service, sovereign wealth fund, Stephen Hawking, Steve Jobs, surveillance capitalism, technological singularity, TED Talk, Tesla Model S, The Coming Technological Singularity, The Death and Life of Great American Cities, The future is already here, The Future of Employment, The Great Good Place, too big to fail, traffic fines, transit-oriented development, Travis Kalanick, Uber and Lyft, uber lyft, urban planning, urban sprawl, US Airways Flight 1549, Vernor Vinge, vertical integration, Vision Fund, warehouse automation, warehouse robotics

v=B8R148hFxPw. 35reduced the cost of lidar: Kirsten Korosec, “Five Things to Know about the Future of Google’s Self-Driving Car Company: Waymo,” Fortune, January 8, 2017, http://fortune.com/2017/01/08/waymo-detroit-future/. 35higher resolution than radar and longer range: Sebastian Thrun et al., “Stanley: The Robot That Won the DARPA Grand Challenge,” Journal of Field Robotics 23, no. 9 (2006): 661–92, http://isl.ecst.csuchico.edu/DOCS/darpa2005/DARPA%202005%20Stanley.pdf. 35more than 3,000 smartphone-toting citizens: Author’s calculation based on Brian Krzanich, “Data Is the New Oil in the Future of Automated Driving,” Intel, November 15, 2016, https://newsroom.intel.com/editorials/krzanich-the-future-of-automated-driving/#gs.dcqfk7. 36neural networks were put to work in banks and postal systems: Leon Bottou, “Graph Transformer Networks,” Leon Bottou (website), September 28, 2018, https://leon.bottou.org/talks/gtn. 37The occupancy grid provides a geometric structure: Lipson and Kurman, Driverless, 93–94. 38these predictions are represented by a cone of uncertainty: Lipson and Kurman, Driverless, 95–98. 38more people will have died at the hands of drivers: World Health Organization, Global Status Report on Road Safety: Time for Action (Geneva, Switzerland: World Health Organization, 2009), ix. 38kill more children and young adults (age 5 to 29): World Health Organization, Global Status Report on Road Safety 2018 (Geneva, Switzerland: World Health Organization, 2018). 40autonomous vehicles can operate: For instance, see Lipson and Kurman, Driverless, 127–36, 143–48, which scopes out a strictly limited role for government in the driverless revolution. 40“Why would we invest in putting wires in the road?”


pages: 328 words: 96,678

MegaThreats: Ten Dangerous Trends That Imperil Our Future, and How to Survive Them by Nouriel Roubini

"World Economic Forum" Davos, 2021 United States Capitol attack, 3D printing, 9 dash line, AI winter, AlphaGo, artificial general intelligence, asset allocation, assortative mating, autonomous vehicles, bank run, banking crisis, basic income, Bear Stearns, Big Tech, bitcoin, Bletchley Park, blockchain, Boston Dynamics, Bretton Woods, British Empire, business cycle, business process, call centre, carbon tax, Carmen Reinhart, cashless society, central bank independence, collateralized debt obligation, Computing Machinery and Intelligence, coronavirus, COVID-19, creative destruction, credit crunch, crony capitalism, cryptocurrency, currency manipulation / currency intervention, currency peg, data is the new oil, David Ricardo: comparative advantage, debt deflation, decarbonisation, deep learning, DeepMind, deglobalization, Demis Hassabis, democratizing finance, Deng Xiaoping, disintermediation, Dogecoin, Donald Trump, Elon Musk, en.wikipedia.org, energy security, energy transition, Erik Brynjolfsson, Ethereum, ethereum blockchain, eurozone crisis, failed state, fake news, family office, fiat currency, financial deregulation, financial innovation, financial repression, fixed income, floating exchange rates, forward guidance, Fractional reserve banking, Francis Fukuyama: the end of history, full employment, future of work, game design, geopolitical risk, George Santayana, Gini coefficient, global pandemic, global reserve currency, global supply chain, GPS: selective availability, green transition, Greensill Capital, Greenspan put, Herbert Marcuse, high-speed rail, Hyman Minsky, income inequality, inflation targeting, initial coin offering, Intergovernmental Panel on Climate Change (IPCC), Internet of things, invention of movable type, Isaac Newton, job automation, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, junk bonds, Kenneth Rogoff, knowledge worker, Long Term Capital Management, low interest rates, low skilled workers, low-wage service sector, M-Pesa, margin call, market bubble, Martin Wolf, mass immigration, means of production, meme stock, Michael Milken, middle-income trap, Mikhail Gorbachev, Minsky moment, Modern Monetary Theory, money market fund, money: store of value / unit of account / medium of exchange, moral hazard, mortgage debt, Mustafa Suleyman, Nash equilibrium, natural language processing, negative equity, Nick Bostrom, non-fungible token, non-tariff barriers, ocean acidification, oil shale / tar sands, oil shock, paradox of thrift, pets.com, Phillips curve, planetary scale, Ponzi scheme, precariat, price mechanism, price stability, public intellectual, purchasing power parity, quantitative easing, race to the bottom, Ralph Waldo Emerson, ransomware, Ray Kurzweil, regulatory arbitrage, reserve currency, reshoring, Robert Shiller, Ronald Reagan, Salesforce, Satoshi Nakamoto, Savings and loan crisis, Second Machine Age, short selling, Silicon Valley, smart contracts, South China Sea, sovereign wealth fund, Stephen Hawking, TED Talk, The Great Moderation, the payments system, Thomas L Friedman, TikTok, too big to fail, Turing test, universal basic income, War on Poverty, warehouse robotics, Washington Consensus, Watson beat the top human players on Jeopardy!, working-age population, Yogi Berra, Yom Kippur War, zero-sum game, zoonotic diseases

“China Drafts Tough Rules to Stop Data from Leaving Its Borders as Beijing Tightens Grip on Information,” the South China Morning Post reported in October 2021. The Cyberspace Administration of China wants to review all business-processing data before it exits the country.30 The United States is also imposing restrictions on Chinese ownership of apps that can collect data of US citizens. Since data is the new oil, the crucial driver of big business, this is the beginning of a much wider form of protectionism and trade restrictions. Tariffs and restrictions imposed by both countries during the Trump administration have accelerated decoupling. A more fragmented economy will increasingly divide the world into two competing economic systems, one dominated by the West, one by China.


Forward: Notes on the Future of Our Democracy by Andrew Yang

2013 Report for America's Infrastructure - American Society of Civil Engineers - 19 March 2013, Affordable Care Act / Obamacare, Amazon Web Services, American Society of Civil Engineers: Report Card, basic income, benefit corporation, Bernie Sanders, blockchain, blue-collar work, call centre, centre right, clean water, contact tracing, coronavirus, correlation does not imply causation, COVID-19, data is the new oil, data science, deepfake, disinformation, Donald Trump, facts on the ground, fake news, forensic accounting, future of work, George Floyd, gig economy, global pandemic, income inequality, independent contractor, Jaron Lanier, Jeff Bezos, job automation, Kevin Roose, labor-force participation, Marc Benioff, Mark Zuckerberg, medical bankruptcy, new economy, obamacare, opioid epidemic / opioid crisis, pez dispenser, QAnon, recommendation engine, risk tolerance, rolodex, Ronald Reagan, Rutger Bregman, Sam Altman, Saturday Night Live, shareholder value, Shoshana Zuboff, Silicon Valley, Simon Kuznets, single-payer health, Snapchat, social distancing, SoftBank, surveillance capitalism, systematic bias, tech billionaire, TED Talk, The Day the Music Died, the long tail, TikTok, universal basic income, winner-take-all economy, working poor

Fortune 500 companies do it. Even local mom-and-pop shops do it with basic Google or Facebook ads. On my campaign we tried to be responsible, but all of the structural forces pushed us to gather as much consumer data as possible. Data has become big business. How big? You might have heard the saying that “data is the new oil.” That may be an understatement. Consider that, as of the time of this writing in mid-2021, ExxonMobil is valued at $258 billion. What is Facebook valued at? $1 trillion. Google? $1.7 trillion. Both Facebook and Google are built largely on the monetization of our data. Most of their revenue comes from advertising businesses that rely upon consumer targeting.


pages: 382 words: 105,819

Zucked: Waking Up to the Facebook Catastrophe by Roger McNamee

"Susan Fowler" uber, "World Economic Forum" Davos, 4chan, Albert Einstein, algorithmic trading, AltaVista, Amazon Web Services, Andy Rubin, barriers to entry, Bernie Sanders, Big Tech, Bill Atkinson, Black Lives Matter, Boycotts of Israel, Brexit referendum, Cambridge Analytica, carbon credits, Cass Sunstein, cloud computing, computer age, cross-subsidies, dark pattern, data is the new oil, data science, disinformation, Donald Trump, Douglas Engelbart, Douglas Engelbart, driverless car, Electric Kool-Aid Acid Test, Elon Musk, fake news, false flag, Filter Bubble, game design, growth hacking, Ian Bogost, income inequality, information security, Internet of things, It's morning again in America, Jaron Lanier, Jeff Bezos, John Markoff, laissez-faire capitalism, Lean Startup, light touch regulation, Lyft, machine readable, Marc Andreessen, Marc Benioff, Mark Zuckerberg, market bubble, Max Levchin, Menlo Park, messenger bag, Metcalfe’s law, minimum viable product, Mother of all demos, move fast and break things, Network effects, One Laptop per Child (OLPC), PalmPilot, paypal mafia, Peter Thiel, pets.com, post-work, profit maximization, profit motive, race to the bottom, recommendation engine, Robert Mercer, Ronald Reagan, Russian election interference, Sand Hill Road, self-driving car, Sheryl Sandberg, Silicon Valley, Silicon Valley startup, Skype, Snapchat, social graph, software is eating the world, Stephen Hawking, Steve Bannon, Steve Jobs, Steven Levy, Stewart Brand, subscription business, TED Talk, The Chicago School, The future is already here, Tim Cook: Apple, two-sided market, Uber and Lyft, Uber for X, uber lyft, Upton Sinclair, vertical integration, WikiLeaks, Yom Kippur War

The platforms have also used a variety of techniques to limit would-be competitors’ access to capital. In economic terms, Facebook, Google, and Amazon exploited their economic power to reduce competition. Regulators are reconsidering their hands-off policies. Past bragging by internet platforms—statements like “software is eating the world” and “data is the new oil”—has invited greater scrutiny. User data has value, even if users do not understand that to be the case. We know this because Facebook and Google are two of the most valuable companies ever created, and their businesses are based on monetizing user data. Harm is increasingly evident, and policy makers and regulators are taking notice.


pages: 422 words: 104,457

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

AltaVista, Ayatollah Khomeini, barriers to entry, bitcoin, Chelsea Manning, Chuck Templeton: OpenTable:, clean water, crowdsourcing, cuban missile crisis, data is the new oil, David Graeber, Debian, disinformation, Edward Snowden, Filter Bubble, Firefox, Free Software Foundation, Garrett Hardin, GnuPG, Google Chrome, Google Glasses, Ida Tarbell, incognito mode, informal economy, Jacob Appelbaum, John Gilmore, John Markoff, Julian Assange, Laura Poitras, Marc Andreessen, market bubble, market design, medical residency, meta-analysis, mutually assured destruction, operational security, Panopticon Jeremy Bentham, prediction markets, price discrimination, randomized controlled trial, RFID, Robert Shiller, Ronald Reagan, security theater, Silicon Valley, Silicon Valley startup, Skype, smart meter, sparse data, Steven Levy, Tragedy of the Commons, Upton Sinclair, WikiLeaks, Y2K, zero-sum game, Zimmermann PGP

Tracking is so crucial to the industry that in 2013 Randall Rothenberg, the president of the Interactive Advertising Bureau, said that if the industry lost its ability to track people, “billions of dollars in Internet advertising and hundreds of thousands of jobs dependent on it would disappear.” Meglena Kuneva, a member of the European Commission, summed it up best in 2009 when she said: “Personal data is the new oil of the Internet and the new currency of the digital world.” * * * If you were to build a taxonomy of trackers it would look something like this: GOVERNMENT • Incidental collectors. Agencies that collect data in their normal course of business, such as state motor vehicle registries and the IRS, but are not directly in the data business


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, backpropagation, basic income, Bayesian statistics, Benoit Mandelbrot, bioinformatics, Black Swan, Brownian motion, cellular automata, Charles Babbage, Claude Shannon: information theory, combinatorial explosion, computer vision, constrained optimization, correlation does not imply causation, creative destruction, crowdsourcing, Danny Hillis, data is not the new oil, data is the new oil, data science, deep learning, DeepMind, double helix, Douglas Hofstadter, driverless car, Erik Brynjolfsson, experimental subject, Filter Bubble, future of work, Geoffrey Hinton, global village, Google Glasses, Gödel, Escher, Bach, Hans Moravec, incognito mode, information retrieval, Jeff Hawkins, job automation, John Markoff, John Snow's cholera map, John von Neumann, Joseph Schumpeter, Kevin Kelly, large language model, lone genius, machine translation, mandelbrot fractal, Mark Zuckerberg, Moneyball by Michael Lewis explains big data, Narrative Science, Nate Silver, natural language processing, Netflix Prize, Network effects, Nick Bostrom, NP-complete, off grid, P = NP, PageRank, pattern recognition, phenotype, planetary scale, power law, 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 long tail, 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, yottabyte, zero-sum game

The race is on, and whoever learns fastest wins. It doesn’t stop with understanding customers better: companies can apply machine learning to every aspect of their operations, provided data is available, and data is pouring in from computers, communication devices, and ever-cheaper and more ubiquitous sensors. “Data is the new oil” is a popular refrain, and as with oil, refining it is big business. IBM, as well plugged into the corporate world as anyone, has organized its growth strategy around providing analytics to companies. Businesses look at data as a strategic asset: What data do I have that my competitors don’t?


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, Benchmark Capital, big data - Walmart - Pop Tarts, bitcoin, blockchain, business cycle, business logic, 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, data science, digital map, discounted cash flows, disintermediation, driverless car, Edward Glaeser, Elon Musk, en.wikipedia.org, Erik Brynjolfsson, financial innovation, Free Software Foundation, gigafactory, growth hacking, Haber-Bosch Process, High speed trading, independent contractor, information asymmetry, Internet of things, inventory management, invisible hand, Jean Tirole, Jeff Bezos, jimmy wales, John Markoff, Kevin Roose, Khan Academy, Kickstarter, Lean Startup, Lyft, Marc Andreessen, market design, Max Levchin, Metcalfe’s law, multi-sided market, Network effects, new economy, PalmPilot, 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, Salesforce, Satoshi Nakamoto, search costs, self-driving car, shareholder value, sharing economy, side project, Silicon Valley, Skype, smart contracts, smart grid, Snapchat, social bookmarking, social contagion, software is eating the world, Steve Jobs, TaskRabbit, The Chicago School, the long tail, the payments system, Tim Cook: Apple, transaction costs, Travis Kalanick, two-sided market, Uber and Lyft, Uber for X, uber lyft, vertical integration, winner-take-all economy, zero-sum game, Zipcar

As of 2011, there were more than three thousand games on Facebook, collectively weakening Zynga’s individual bargaining power.20 The startup’s response may be to sell, to fight back through multihoming, or to expand into other business arenas. Zynga, for example, now multihomes on Tencent’s QQ social network and on the Apple and Google mobile platforms, as well as offering its own cloud service. HOW PLATFORMS COMPETE (3): LEVERAGING THE VALUE OF DATA One of the clichés of the Internet economy is the saying “Data is the new oil”—and like most clichés, it contains a lot of truth. Data can be a source of enormous value to platform businesses, and well-run firms are using data to shore up their competitive positions in a wide variety of ways. Platform businesses can use data to improve their competitive performance in two general ways—tactically and strategically.


pages: 1,172 words: 114,305

New Laws of Robotics: Defending Human Expertise in the Age of AI by Frank Pasquale

affirmative action, Affordable Care Act / Obamacare, Airbnb, algorithmic bias, Amazon Mechanical Turk, Anthropocene, augmented reality, Automated Insights, autonomous vehicles, basic income, battle of ideas, Bernie Sanders, Big Tech, Bill Joy: nanobots, bitcoin, blockchain, Brexit referendum, call centre, Cambridge Analytica, carbon tax, citizen journalism, Clayton Christensen, collective bargaining, commoditize, computer vision, conceptual framework, contact tracing, coronavirus, corporate social responsibility, correlation does not imply causation, COVID-19, critical race theory, cryptocurrency, data is the new oil, data science, decarbonisation, deep learning, deepfake, deskilling, digital divide, digital twin, disinformation, disruptive innovation, don't be evil, Donald Trump, Douglas Engelbart, driverless car, effective altruism, Elon Musk, en.wikipedia.org, Erik Brynjolfsson, Evgeny Morozov, fake news, Filter Bubble, finite state, Flash crash, future of work, gamification, general purpose technology, Google Chrome, Google Glasses, Great Leap Forward, green new deal, guns versus butter model, Hans Moravec, high net worth, hiring and firing, holacracy, Ian Bogost, independent contractor, informal economy, information asymmetry, information retrieval, interchangeable parts, invisible hand, James Bridle, Jaron Lanier, job automation, John Markoff, Joi Ito, Khan Academy, knowledge economy, late capitalism, lockdown, machine readable, Marc Andreessen, Mark Zuckerberg, means of production, medical malpractice, megaproject, meta-analysis, military-industrial complex, Modern Monetary Theory, Money creation, move fast and break things, mutually assured destruction, natural language processing, new economy, Nicholas Carr, Nick Bostrom, Norbert Wiener, nuclear winter, obamacare, One Laptop per Child (OLPC), open immigration, OpenAI, opioid epidemic / opioid crisis, paperclip maximiser, paradox of thrift, pattern recognition, payday loans, personalized medicine, Peter Singer: altruism, Philip Mirowski, pink-collar, plutocrats, post-truth, pre–internet, profit motive, public intellectual, QR code, quantitative easing, race to the bottom, RAND corporation, Ray Kurzweil, recommendation engine, regulatory arbitrage, Robert Shiller, Rodney Brooks, Ronald Reagan, self-driving car, sentiment analysis, Shoshana Zuboff, Silicon Valley, Singularitarianism, smart cities, smart contracts, software is eating the world, South China Sea, Steve Bannon, Strategic Defense Initiative, surveillance capitalism, Susan Wojcicki, tacit knowledge, TaskRabbit, technological solutionism, technoutopianism, TED Talk, telepresence, telerobotics, The Future of Employment, The Turner Diaries, Therac-25, Thorstein Veblen, too big to fail, Turing test, universal basic income, unorthodox policies, wage slave, Watson beat the top human players on Jeopardy!, working poor, workplace surveillance , Works Progress Administration, zero day

“Google’s experiments do appear to have been designed to deceive,” said Oxford researcher Thomas King when interviewed by noted tech journalist Natasha Lomas.81 Travis Korte commented that “we should make AI sound different from humans for the same reason we put a smelly additive in normally odorless natural gas.”82 Korte’s comment puts a new spin on the old saw that “big data is the new oil”—you need to know when you’re dealing with it, lest it blow up in your face. It’s an entirely different matter to have a conversation with a human (however brief) and to be subject to the manipulation of a human-mimicking AI controlled by one of the largest companies on earth. Duplex may seem like an outlier, a deputation of small talk to AI with little lasting impact.


Succeeding With AI: How to Make AI Work for Your Business by Veljko Krunic

AI winter, Albert Einstein, algorithmic trading, AlphaGo, Amazon Web Services, anti-fragile, anti-pattern, artificial general intelligence, autonomous vehicles, Bayesian statistics, bioinformatics, Black Swan, Boeing 737 MAX, business process, cloud computing, commoditize, computer vision, correlation coefficient, data is the new oil, data science, deep learning, DeepMind, en.wikipedia.org, fail fast, Gini coefficient, high net worth, information retrieval, Internet of things, iterative process, job automation, Lean Startup, license plate recognition, minimum viable product, natural language processing, recommendation engine, self-driving car, sentiment analysis, Silicon Valley, six sigma, smart cities, speech recognition, statistical model, strong AI, tail risk, The Design of Experiments, the scientific method, web application, zero-sum game

TIP Starting with technology stack considerations as your main focus can lead you into the trap of overconcentrating on the infrastructure, and you can lose focus on the sequence of data science use cases that you should implement. Remember, your attention is a finite resource too. Let’s embrace the analogy that data is the new oil. If you need a new oilfield, you’d put your greatest focus into finding oil and understanding what an oilfield looks like. You most certainly wouldn’t start by buying the best oil drilling equipment in the world, with the drilling location as an afterthought. The same thing applies to data—concentrate on finding oil, not on the drilling equipment.


System Error by Rob Reich

"Friedman doctrine" OR "shareholder theory", "World Economic Forum" Davos, 2021 United States Capitol attack, A Declaration of the Independence of Cyberspace, Aaron Swartz, AI winter, Airbnb, airport security, Alan Greenspan, Albert Einstein, algorithmic bias, AlphaGo, AltaVista, artificial general intelligence, Automated Insights, autonomous vehicles, basic income, Ben Horowitz, Berlin Wall, Bernie Madoff, Big Tech, bitcoin, Blitzscaling, Cambridge Analytica, Cass Sunstein, clean water, cloud computing, computer vision, contact tracing, contact tracing app, coronavirus, corporate governance, COVID-19, creative destruction, CRISPR, crowdsourcing, data is the new oil, data science, decentralized internet, deep learning, deepfake, DeepMind, deplatforming, digital rights, disinformation, disruptive innovation, Donald Knuth, Donald Trump, driverless car, dual-use technology, Edward Snowden, Elon Musk, en.wikipedia.org, end-to-end encryption, Fairchild Semiconductor, fake news, Fall of the Berlin Wall, Filter Bubble, financial engineering, financial innovation, fulfillment center, future of work, gentrification, Geoffrey Hinton, George Floyd, gig economy, Goodhart's law, GPT-3, Hacker News, hockey-stick growth, income inequality, independent contractor, informal economy, information security, Jaron Lanier, Jeff Bezos, Jim Simons, jimmy wales, job automation, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, John Perry Barlow, Lean Startup, linear programming, Lyft, Marc Andreessen, Mark Zuckerberg, meta-analysis, minimum wage unemployment, Monkeys Reject Unequal Pay, move fast and break things, Myron Scholes, Network effects, Nick Bostrom, Northpointe / Correctional Offender Management Profiling for Alternative Sanctions, NP-complete, Oculus Rift, OpenAI, Panopticon Jeremy Bentham, Parler "social media", pattern recognition, personalized medicine, Peter Thiel, Philippa Foot, premature optimization, profit motive, quantitative hedge fund, race to the bottom, randomized controlled trial, recommendation engine, Renaissance Technologies, Richard Thaler, ride hailing / ride sharing, Ronald Reagan, Sam Altman, Sand Hill Road, scientific management, self-driving car, shareholder value, Sheryl Sandberg, Shoshana Zuboff, side project, Silicon Valley, Snapchat, social distancing, Social Responsibility of Business Is to Increase Its Profits, software is eating the world, spectrum auction, speech recognition, stem cell, Steve Jobs, Steven Levy, strong AI, superintelligent machines, surveillance capitalism, Susan Wojcicki, tech billionaire, tech worker, techlash, technoutopianism, Telecommunications Act of 1996, telemarketer, The Future of Employment, TikTok, Tim Cook: Apple, traveling salesman, Triangle Shirtwaist Factory, trolley problem, Turing test, two-sided market, Uber and Lyft, uber lyft, ultimatum game, union organizing, universal basic income, washing machines reduced drudgery, Watson beat the top human players on Jeopardy!, When a measure becomes a target, winner-take-all economy, Y Combinator, you are the product

An age of smart machines that delivers increased efficiency in the workplace might well bring about a new chapter in economic growth and productivity. Of course, there’s a huge downside risk as well: if the age of automation displaces huge numbers of people from the workforce, many people will lose a reliable source of income and suffer a threat to their material welfare. It’s been said that if big data is the new oil of the economy, then AI is the electricity. Andrew Ng, a leading AI scientist, says that AI will produce “automation on steroids” and transform every industry known to humankind. The benefits of increasing automation are easy to see, but the costs are often concentrated and sometimes hard to pin down.


pages: 516 words: 116,875

Greater: Britain After the Storm by Penny Mordaunt, Chris Lewis

"World Economic Forum" Davos, 2021 United States Capitol attack, 3D printing, accelerated depreciation, Ada Lovelace, Airbnb, banking crisis, battle of ideas, behavioural economics, Bernie Madoff, bitcoin, Black Lives Matter, blockchain, Bob Geldof, Boeing 747, Boris Johnson, Bretton Woods, Brexit referendum, British Empire, carbon footprint, Charles Babbage, collective bargaining, Corn Laws, corporate social responsibility, COVID-19, credit crunch, crowdsourcing, data is not the new oil, data is the new oil, David Attenborough, death from overwork, Deng Xiaoping, Diane Coyle, Donald Trump, Downton Abbey, driverless car, Elon Musk, en.wikipedia.org, experimental economics, failed state, fake news, Firefox, fixed income, full employment, gender pay gap, global pandemic, global supply chain, green new deal, happiness index / gross national happiness, high-speed rail, impact investing, Jeremy Corbyn, Khartoum Gordon, lateral thinking, Live Aid, lockdown, loss aversion, low skilled workers, microaggression, mittelstand, moral hazard, Neil Kinnock, Nelson Mandela, Ocado, off-the-grid, offshore financial centre, Panamax, Ponzi scheme, post-truth, quantitative easing, remote working, road to serfdom, Salesforce, Sheryl Sandberg, Skype, smart cities, social distancing, South China Sea, sovereign wealth fund, Steve Jobs, Steven Pinker, surveillance capitalism, transaction costs, transcontinental railway

They foretold 9/11, the banking crisis, the rise of nationalism, the climate change movement, the coming of Brexit and the rise of Donald Trump. It wasn’t a lack of data that hid these issues; it was an inability to read the mood. Communication is not the same as conversation. They don’t teach that at university. Graduates may say that data is the new oil, but stock markets are moved as much by sentiment as they are by statistics. Looking at statistics will not help you understand sentiment. Britain may be doing well in aggregate, but the experience in the regions can feel very different. Britain has always been an open country and culture.


pages: 521 words: 118,183

The Wires of War: Technology and the Global Struggle for Power by Jacob Helberg

"World Economic Forum" Davos, 2021 United States Capitol attack, A Declaration of the Independence of Cyberspace, active measures, Affordable Care Act / Obamacare, air gap, Airbnb, algorithmic management, augmented reality, autonomous vehicles, Berlin Wall, Bernie Sanders, Big Tech, bike sharing, Black Lives Matter, blockchain, Boris Johnson, Brexit referendum, cable laying ship, call centre, Cambridge Analytica, Cass Sunstein, cloud computing, coronavirus, COVID-19, creative destruction, crisis actor, data is the new oil, data science, decentralized internet, deep learning, deepfake, deglobalization, deindustrialization, Deng Xiaoping, deplatforming, digital nomad, disinformation, don't be evil, Donald Trump, dual-use technology, Edward Snowden, Elon Musk, en.wikipedia.org, end-to-end encryption, fail fast, fake news, Filter Bubble, Francis Fukuyama: the end of history, geopolitical risk, glass ceiling, global pandemic, global supply chain, Google bus, Google Chrome, GPT-3, green new deal, information security, Internet of things, Jeff Bezos, Jeffrey Epstein, John Markoff, John Perry Barlow, knowledge economy, Larry Ellison, lockdown, Loma Prieta earthquake, low earth orbit, low skilled workers, Lyft, manufacturing employment, Marc Andreessen, Mark Zuckerberg, Mary Meeker, Mikhail Gorbachev, military-industrial complex, Mohammed Bouazizi, move fast and break things, Nate Silver, natural language processing, Network effects, new economy, one-China policy, open economy, OpenAI, Parler "social media", Peter Thiel, QAnon, QR code, race to the bottom, Ralph Nader, RAND corporation, reshoring, ride hailing / ride sharing, Ronald Reagan, Russian election interference, Salesforce, Sam Altman, satellite internet, self-driving car, Sheryl Sandberg, side project, Silicon Valley, Silicon Valley ideology, Silicon Valley startup, Skype, smart grid, SoftBank, Solyndra, South China Sea, SpaceX Starlink, Steve Jobs, Steven Levy, Stuxnet, supply-chain attack, Susan Wojcicki, tech worker, techlash, technoutopianism, TikTok, Tim Cook: Apple, trade route, TSMC, Twitter Arab Spring, uber lyft, undersea cable, Unsafe at Any Speed, Valery Gerasimov, vertical integration, Wargames Reagan, Westphalian system, white picket fence, WikiLeaks, Y Combinator, zero-sum game

Already, there are reports that data from the African Union’s Chinese-built headquarters in Addis Ababa has been streaming to servers in Shanghai nightly for years,101 and that Huawei engineers have aided the Ugandan and Zambian regimes by intercepting their political rivals’ communications and tracking their locations.102 If data is the new oil, controlling the back-end would yield China a never-ending gusher of sweet Texas crude. Whoever’s digital sphere is larger will boast more data, bigger companies, and more powerful AI capabilities. Every cable under the Pacific, every camera system installed in an African country, could provide grist for Chinese algorithms.


pages: 497 words: 144,283

Connectography: Mapping the Future of Global Civilization by Parag Khanna

"World Economic Forum" Davos, 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, Anthropocene, 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, Carl Icahn, charter city, circular economy, 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 capitalism, digital divide, digital map, disruptive innovation, diversification, Doha Development Round, driverless car, Easter island, edge city, Edward Snowden, Elon Musk, energy security, Ethereum, ethereum blockchain, European colonialism, eurozone crisis, export processing zone, failed state, Fairphone, Fall of the Berlin Wall, family office, Ferguson, Missouri, financial innovation, financial repression, fixed income, forward guidance, gentrification, geopolitical risk, global supply chain, global value chain, global village, Google Earth, Great Leap Forward, Hernando de Soto, high net worth, high-speed rail, 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 earth orbit, low interest rates, manufacturing employment, mass affluent, mass immigration, megacity, Mercator projection, Metcalfe’s law, microcredit, middle-income trap, mittelstand, Monroe Doctrine, Multics, mutually assured destruction, Neal Stephenson, 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, Planet Labs, plutocrats, post-oil, post-Panamax, precautionary principle, private military company, purchasing power parity, quantum entanglement, Quicken Loans, QWERTY keyboard, race to the bottom, Rana Plaza, rent-seeking, reserve currency, Robert Gordon, Robert Shiller, Robert Solow, rolling blackouts, Ronald Coase, Scramble for Africa, Second Machine Age, sharing economy, Shenzhen special economic zone , 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, systems thinking, TaskRabbit, tech worker, TED Talk, 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, Tragedy of the Commons, transaction costs, Tyler Cowen, UNCLOS, uranium enrichment, urban planning, urban sprawl, vertical integration, WikiLeaks, Yochai Benkler, young professional, zero day

Whether these governments seek to monitor, filter, or protect digital flows, the geographic (and legal) location of servers, cables, routers, and data centers now matters as much as the geography of oil pipelines. The differences are crucial, however. Internet data can be replicated infinitely and exist in multiple places at the same time. Additionally, it can be rerouted or smuggled “in” to its destination, while the receiver has the ability to come “out” as well to access it. If data is the new oil, it is certainly much more slippery. It is true that the Internet is no longer a truly borderless, parallel universe. Even Twitter, the world’s most free and unfiltered medium of one-to-many expression, preemptively restricts content banned in various countries, while Google Maps loads tailored maps approved by national authorities based on the user’s server location.