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Inside the Robot Kingdom: Japan, Mechatronics and the Coming Robotopia by Frederik L. Schodt

carbon-based life, computer age, Computer Numeric Control, computer vision, deindustrialization, Deng Xiaoping, deskilling, factory automation, game design, guest worker program, industrial robot, Jacques de Vaucanson, Norbert Wiener, post-industrial society, robot derives from the Czech word robota Czech, meaning slave, Ronald Reagan, Silicon Valley, telepresence, The Wealth of Nations by Adam Smith, V2 rocket, warehouse automation, Whole Earth Review, women in the workforce

Communication will be critical for acceptance."17 * * * * * * * * * * * * Toy and amusement robots appeal to our dreams of a future far beyond the present technological horizon, although the industry that manufactures them is trapped in an older, labor-intensive world. It is to the unromantic industrial robot we must now turn—and to the manufacturers that have so enthusiastically put them to work. PART THREE After Industrial Robots: Building the Kingdom Japan Manufactures the Industrial Robot * * * The companies that can make their own robots, that can manufacture the best industrial robots for their industries, they'll be way ahead of the other fellow. GEORGE C. DEVOL, JR. * * * Early industrial robot technology was like a fragile flower that needed the right soil to grow, and when transplanted into Japan it flourished beyond anyone's wildest dreams.

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—WHOLE EARTH REVIEW * * * * * * * * * * * * "One of the best Sci-Tech books of 1988" ‘LIBRARY JOURNAL Contents On the New 2010 Digital Version Preface PART ONE Introducing the Robot Kingdom and the Robot 1 The Robot Kingdom 2 What Is a Robot? PART TWO Before Industrial Robots: A State of Mind 3 The First Japanese Robot 4 Robots of the Imagination 5 The Toy Robot Kingdom PART THREE After Industrial Robots: Building the Kingdom 6 Japan Manufactures the Industrial Robot 7 An Empire of Yellow Robots 8 The Man—Machine Interface 9 Robots and the Wealth of Nations PART FOUR Beyond Industrial Robots 10 Religion and Robots 11 Six Legs, Four Legs, Two Legs, or None? Color Photo Section Notes Bibliography Index Credits About The Author On the New Digital Edition of Inside the Robot Kingdom I began doing research for Inside the Robot Kingdom in the mid-1980s.

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Sangyoyo robotto nyumon [An Introduction to Industrial Robots]. Tokyo: Taiga Shuppan, 1985. Ishihara, Fujio. SF robottogaku nyumon [An Introduction to SF Robotics]. Tokyo: Haya- kawa Shobo, 1981. Iwai, Masakazu. Hitachi, Toshiba, Matsushita FA no saizensen: "shijo taiyogata" seisan genba o yuku [On the Front Lines of Factory Automation at Hitachi, Toshiba, and Matsushita: On the Site of Market-Oriented Production]. Tokyo: Diamond-sha, 1986. Japan Industrial Robot Association (JIRA), ed. Sangyoyo robotto hando bukku [Industrial Robot Handbook]. 1985 ed. Tokyo: Japan Industrial Robot Association, 1985. --. Sangyoyo robotto ni kansuru daigaku-kokuritsu kenkyu kikan nado no kenkyu kaihatsu doko chosa hokokusho [Survey of Trends in Industrial Robot Research and Development at University and National Laboratories].

The Economic Singularity: Artificial Intelligence and the Death of Capitalism by Calum Chace

"World Economic Forum" Davos, 3D printing, additive manufacturing, agricultural Revolution, AI winter, Airbnb, AlphaGo, Alvin Toffler, Amazon Robotics, Andy Rubin, artificial general intelligence, augmented reality, autonomous vehicles, banking crisis, basic income, Baxter: Rethink Robotics, Berlin Wall, Bernie Sanders, bitcoin, blockchain, Boston Dynamics, bread and circuses, call centre, Chris Urmson, congestion charging, credit crunch, David Ricardo: comparative advantage, deep learning, DeepMind, Demis Hassabis, digital divide, Douglas Engelbart, Dr. Strangelove, driverless car, Elon Musk, en.wikipedia.org, Erik Brynjolfsson, Fairchild Semiconductor, Flynn Effect, full employment, future of work, Future Shock, gender pay gap, Geoffrey Hinton, gig economy, Google Glasses, Google X / Alphabet X, Hans Moravec, Herman Kahn, hype cycle, ImageNet competition, income inequality, industrial robot, Internet of things, invention of the telephone, invisible hand, James Watt: steam engine, Jaron Lanier, Jeff Bezos, job automation, John Markoff, John Maynard Keynes: technological unemployment, John von Neumann, Kevin Kelly, Kiva Systems, knowledge worker, lifelogging, lump of labour, Lyft, machine translation, Marc Andreessen, Mark Zuckerberg, Martin Wolf, McJob, means of production, Milgram experiment, Narrative Science, natural language processing, Neil Armstrong, new economy, Nick Bostrom, Occupy movement, Oculus Rift, OpenAI, PageRank, pattern recognition, post scarcity, post-industrial society, post-work, precariat, prediction markets, QWERTY keyboard, railway mania, RAND corporation, Ray Kurzweil, RFID, Rodney Brooks, Sam Altman, Satoshi Nakamoto, Second Machine Age, self-driving car, sharing economy, Silicon Valley, Skype, SoftBank, software is eating the world, speech recognition, Stephen Hawking, Steve Jobs, TaskRabbit, technological singularity, TED Talk, The future is already here, The Future of Employment, Thomas Malthus, transaction costs, Two Sigma, Tyler Cowen, Tyler Cowen: Great Stagnation, Uber for X, uber lyft, universal basic income, Vernor Vinge, warehouse automation, warehouse robotics, working-age population, Y Combinator, young professional

These characteristics make it ripe for automation, and the fact that the output (cars) are high-value items means that investment in expensive automation systems can be justified. Around half of all the industrial robots in service today are engaged in car manufacturing.[xxi] Despite the recession, sales of industrial robots grew at 10% a year from 2008 to 2013, when 178,000 were sold worldwide. Sales in 2014 jumped 29% to 229,000, and the International Federation of Robotics expects the number to jump a further 75% to 400,000 by 2018. China became the biggest market in 2013, installing 37,000 robots compared with 30,000 in the USA[xxii]. Until recently, the industrial robots used in car manufacturing (and elsewhere) were expensive, inflexible, and dangerous to be around.

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Historically, China’s competitive strength in manufacturing has been its low wage costs, but this is changing fast: wages have grown at 12% a year on average since 2001, and Chinese manufacturers are embracing automation enthusiastically. As we saw in chapter 2.3, China is now the world’s largest market for industrial robots, but it has a long way to go before it catches up with the installed base in more developed countries. Industrial robots are far from perfect, and manufacturers have under-estimated the progress still required. In 2011 the CEO of Foxconn, a $130bn-turnover Taiwanese manufacturer that is famous for making iPhones, declared a target of installing a million robots by 2014.

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Until recently, the industrial robots used in car manufacturing (and elsewhere) were expensive, inflexible, and dangerous to be around. But the industrial robotics industry is changing: as well as growing quickly, its output is getting cheaper, safer and far more versatile. A landmark was reached in 2012 with the introduction of Baxter, a 3-foot tall robot (6 feet with his pedestal) from Rethink Robotics. The brainchild of Rodney Brooks, an Australian roboticist who used to be the director of the MIT Computer Science and Artificial Intelligence Laboratory, Baxter is much less dangerous to be around. By early 2015, Rethink had received over $100m in funding from venture capitalists, including the investment vehicle of Amazon founder Jeff Bezos.

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

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Evan Ackerman, “Covariant uses simple robot and gigantic neural net to automate warehouse picking,” IEEE Spectrum, January 29, 2020, spectrum.ieee.org/automaton/robotics/industrial-robots/covariant-ai-gigantic-neural-network-to-automate-warehouse-picking. 23. Jonathan Vanian, “Industrial robotics giant teams up with a rising A.I. startup,” Fortune, February 25, 2020, fortune.com/2020/02/25/industrial-robotics-ai-covariant/. 24. Alexander Lavin, J. Swaroop Guntupalli, Miguel Lázaro-Gredilla, et al., “Explaining visual cortex phenomena using recursive cortical network,” Vicarious Research Paper, July 30, 2018, www.biorxiv.org/content/biorxiv/early/2018/07/30/380048.full.pdf. 25. Tom Simonite, “These industrial robots get more adept with every task,” Wired, March 10, 2020, www.wired.com/story/these-industrial-robots-adept-every-task/. 26.

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The researchers at Covariant believe that “reinforcement learning”—or essentially learning through trial and error—is the most effective way to progress, and the company claims to be building a system based on a massive deep neural network that it calls “universal AI for robots,” which it expects to eventually power a variety of machines that can “see, reason and act in the world around them, completing tasks too complex and varied for traditional programmed robots.”21 The company, founded by researchers from the University of California at Berkeley and OpenAI, has received investments and publicity from some of the brightest lights in deep learning, including Turing Award winners Geoffrey Hinton and Yann LeCun, Google’s Jeff Dean and ImageNet founder Fei-Fei Li.22 In 2019, Covariant defeated nineteen other companies in a competition organized by the Swiss industrial robot maker ABB by demonstrating the only system capable of recognizing and manipulating a variety of items without any need for human intervention.23 Covariant will be working with ABB as well other major companies to imbue industrial robots deployed in warehouses and factories with intelligence that the company believes will eventually match or exceed human-level perception and dexterity. Many of the startup companies and university researchers working in this area believe, like Covariant, that a strategy founded on deep neural networks and reinforcement learning is the best way to fuel progress toward more dexterous robots.

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In parallel with its progress in artificial intelligence, Vicarious is also pursuing an innovative “robots as a service” business model, which may eventually prove to be disruptive across a range of industries. Rather than building or selling its own robots, Vicarious instead acquires industrial robots from companies like ABB, integrates them with its proprietary artificial intelligence software and then rents the robots out to companies in a way that’s roughly comparable to the way a temporary employment agency might place human workers. The result is that client companies do not have to make the upfront capital investment and long-term commitment that is normally associated with industrial robots. This directly addresses one of the biggest drawbacks of using robots: the machines are expensive to purchase, install and program, and therefore it takes a long time for the investment to pay for itself.

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

A Declaration of the Independence of Cyberspace, Aaron Swartz, AI winter, Airbnb, Albert Einstein, Alvin Toffler, Amazon Web Services, augmented reality, bank run, barriers to entry, Baxter: Rethink Robotics, bitcoin, blockchain, book scanning, Brewster Kahle, Burning Man, cloud computing, commoditize, computer age, Computer Lib, connected car, crowdsourcing, dark matter, data science, deep learning, DeepMind, dematerialisation, Downton Abbey, driverless car, Edward Snowden, Elon Musk, Filter Bubble, Freestyle chess, Gabriella Coleman, game design, Geoffrey Hinton, Google Glasses, hive mind, Howard Rheingold, index card, indoor plumbing, industrial robot, Internet Archive, Internet of things, invention of movable type, invisible hand, Jaron Lanier, Jeff Bezos, job automation, John Markoff, John Perry Barlow, Kevin Kelly, Kickstarter, lifelogging, linked data, Lyft, M-Pesa, machine readable, machine translation, Marc Andreessen, Marshall McLuhan, Mary Meeker, means of production, megacity, Minecraft, Mitch Kapor, multi-sided market, natural language processing, Netflix Prize, Network effects, new economy, Nicholas Carr, off-the-grid, old-boy network, peer-to-peer, peer-to-peer lending, personalized medicine, placebo effect, planetary scale, postindustrial economy, Project Xanadu, recommendation engine, RFID, ride hailing / ride sharing, robo advisor, Rodney Brooks, self-driving car, sharing economy, Silicon Valley, slashdot, Snapchat, social graph, social web, software is eating the world, speech recognition, Stephen Hawking, Steven Levy, Ted Nelson, TED Talk, The future is already here, the long tail, the scientific method, transport as a service, two-sided market, Uber for X, uber lyft, value engineering, Watson beat the top human players on Jeopardy!, WeWork, Whole Earth Review, Yochai Benkler, yottabyte, zero-sum game

accurate caption for any photo: Tom Simonite, “Google Creates Software That Tells You What It Sees in Images,” MIT Technology Review, November 18, 2014. Industrial robots cost $100,000-plus: Angelo Young, “Industrial Robots Could Be 16% Less Costly to Employ Than People by 2025,” International Business Times, February 11, 2015. four times that amount over a lifespan: Martin Haegele, Thomas Skordas, Stefan Sagert, et al., “Industrial Robot Automation,” White Paper FP6-001917, European Robotics Research Network, 2005. Priced at $25,000: Angelo Young, “Industrial Robots Could Be 16% Less Costly to Employ Than People by 2025,” International Business Times, February 11, 2015.

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The code has to be loaded in batch mode—i.e., in large, infrequent batches—because the robot cannot be reprogrammed while it is being used. Turns out the real cost of the typical industrial robot is not its hardware but its operation. Industrial robots cost $100,000-plus to purchase but can require four times that amount over a lifespan to program, train, and maintain. The costs pile up until the average lifetime bill for an industrial robot is half a million dollars or more. The third difference, then, is that Baxter is cheap. Priced at $25,000, it’s in a different league compared with the $500,000 total bill of its predecessors.

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Designed by Rodney Brooks, the former MIT professor who invented the bestselling Roomba vacuum cleaner and its descendants, Baxter is an early example of a new class of industrial robots created to work alongside humans. Baxter does not look impressive. Sure, it’s got big strong arms and a flat-screen display like many industrial bots. And Baxter’s hands perform repetitive manual tasks, just as factory robots do. But it’s different in three significant ways. First, it can look around and indicate where it is looking by shifting the cartoon eyes on its head. It can perceive humans working near it and avoid injuring them. And workers can see whether it sees them. Previous industrial robots couldn’t do this, which meant that working robots had to be physically segregated from humans.

Arriving Today: From Factory to Front Door -- Why Everything Has Changed About How and What We Buy by Christopher Mims

air freight, Airbnb, Amazon Robotics, Amazon Web Services, Apollo 11, augmented reality, autonomous vehicles, big-box store, blue-collar work, Boeing 747, book scanning, business logic, business process, call centre, cloud computing, company town, coronavirus, cotton gin, COVID-19, creative destruction, data science, Dava Sobel, deep learning, dematerialisation, deskilling, digital twin, Donald Trump, easy for humans, difficult for computers, electronic logging device, Elon Musk, Frederick Winslow Taylor, fulfillment center, gentrification, gig economy, global pandemic, global supply chain, guest worker program, Hans Moravec, heat death of the universe, hive mind, Hyperloop, immigration reform, income inequality, independent contractor, industrial robot, interchangeable parts, intermodal, inventory management, Jacquard loom, Jeff Bezos, Jessica Bruder, job automation, John Maynard Keynes: Economic Possibilities for our Grandchildren, Joseph Schumpeter, Kaizen: continuous improvement, Kanban, Kiva Systems, level 1 cache, Lewis Mumford, lockdown, lone genius, Lyft, machine readable, Malacca Straits, Mark Zuckerberg, market bubble, minimum wage unemployment, Nomadland, Ocado, operation paperclip, Panamax, Pearl River Delta, planetary scale, pneumatic tube, polynesian navigation, post-Panamax, random stow, ride hailing / ride sharing, robot derives from the Czech word robota Czech, meaning slave, Rodney Brooks, rubber-tired gantry crane, scientific management, self-driving car, sensor fusion, Shenzhen special economic zone , Shoshana Zuboff, Silicon Valley, six sigma, skunkworks, social distancing, South China Sea, special economic zone, spinning jenny, standardized shipping container, Steve Jobs, supply-chain management, surveillance capitalism, TED Talk, the scientific method, Tim Cook: Apple, Toyota Production System, traveling salesman, Turing test, two-sided market, Uber and Lyft, Uber for X, uber lyft, Upton Sinclair, vertical integration, warehouse automation, warehouse robotics, workplace surveillance

Drivers are given a prearranged time to arrive, scheduled by an algorithm so as to minimize the time they must wait in the port while also maximizing the efficiency of the sequence of containers lifted by the crane that day. Drivers back their trucks in and then get out and stand in what look like phone booths positioned on little concrete islands in between each lane. Here, as in factories filled with industrial robots, the key to keeping soft, eminently crushable, water balloon–like humans safe is to segregate them from the machines completely. Once a driver is in the safety kiosk, the invisible lasers shooting through the air allow the system to identify where the twistlocks are on the flatbed trailer and precisely lower a container onto those locks.

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Make the ceilings snow white, the floors polished concrete, and fill the guts of the thing—miles of curving stainless-steel conveyor—with tens of thousands of daisy-yellow plastic totes. Standing on the second-floor mezzanine at one end of the facility, looking down its improbable length, the eye alights on a Fanuc industrial robot arm two stories tall. Also yellow, it swings to and fro. The arm grabs a yellow bin, a “tote” as they’re known within Amazon, from a conveyor. Using its purpose-designed actuator, it lifts its mass with a speed suggesting it weighs nothing at all. It pauses at the top of the arc of its movement, as if taking a moment to think.

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Chapter 15 The Unbearable Complexity of Robotic Warehousing It’s at this point in the story that a reasonable person asks why, in a company that has deployed so many robots, so many humans must perform the many Sisyphean tasks at the heart of Amazon’s sorting of goods in its warehouses. The world’s first industrial robot was installed in a factory owned by General Motors in 1961; the underlying technology was patented in 1954. Why have we not by now created robotic arms dexterous enough to take over a task as elementary as picking up an object and placing it in a soft-sided cubby? The short answer to that question is that this task only seems elementary because humans are so incredibly good at it.

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

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

Electric-car company Tesla’s new plant in Fremont, California, uses 160 highly flexible industrial robots to assemble about 400 cars per week. As a new-car chassis arrives at the next position in the assembly line, multiple robots descend on it and operate in coordination. The machines are able to autonomously swap the tools wielded by their robotic arms in order to complete a variety of tasks. The same robot, for example, installs the seats, retools itself, and then applies adhesive and drops the windshield into place.2 According to the International Federation of Robotics, global shipments of industrial robots increased by more than 60 percent between 2000 and 2012, with total sales of about $28 billion in 2012.

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Rethink was founded by Rodney Brooks, one of the world’s foremost robotics researchers at MIT and a co-founder of iRobot, the company that makes the Roomba automated vacuum cleaner as well as military robots used to defuse bombs in Iraq and Afghanistan. Baxter, which costs significantly less than a year’s wages for a typical US manufacturing worker, is essentially a scaled-down industrial robot that is designed to operate safely in close proximity to people. In contrast to industrial robots, which require complex and expensive programming, Baxter can be trained simply by moving its arms through the required motions. If a facility uses multiple robots, one Baxter can be trained and then the knowledge can be propagated to the others simply by plugging in a USB device.

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John Markoff, “Skilled Work, Without the Worker,” New York Times, August 18, 2012, http://www.nytimes.com/2012/08/19/business/new-wave-of-adept-robots-is-changing-global-industry.html. 2. Damon Lavrinc, “Peek Inside Tesla’s Robotic Factory,” Wired.com, July 16, 2013, http://www.wired.com/autopia/2013/07/tesla-plant-video/. 3. International Federation of Robotics website, Industrial Robot Statistics 2013, http://www.ifr.org/industrial-robots/statistics/. 4. Jason Tanz, “Kinect Hackers Are Changing the Future of Robotics,” Wired Magazine, July 2011, http://www.wired.com/magazine/2011/06/mf_kinect/. 5. Esther Shein, “Businesses Adopting Robots for New Tasks,” Computerworld, August 1, 2013, http://www.computerworld.com/s/article/9241118/Businesses_adopting_robots_for_new_tasks. 6.

Fully Automated Luxury Communism by Aaron Bastani

"Peter Beck" AND "Rocket Lab", Alan Greenspan, Anthropocene, autonomous vehicles, banking crisis, basic income, Berlin Wall, Bernie Sanders, Boston Dynamics, Bretton Woods, Brexit referendum, capital controls, capitalist realism, cashless society, central bank independence, collapse of Lehman Brothers, computer age, computer vision, CRISPR, David Ricardo: comparative advantage, decarbonisation, deep learning, dematerialisation, DIY culture, Donald Trump, double helix, driverless car, electricity market, Elon Musk, energy transition, Erik Brynjolfsson, fake news, financial independence, Francis Fukuyama: the end of history, future of work, Future Shock, G4S, general purpose technology, Geoffrey Hinton, Gregor Mendel, housing crisis, income inequality, industrial robot, Intergovernmental Panel on Climate Change (IPCC), Internet of things, Isaac Newton, James Watt: steam engine, Jeff Bezos, Jeremy Corbyn, Jevons paradox, job automation, John Markoff, John Maynard Keynes: technological unemployment, Joseph Schumpeter, Kevin Kelly, Kuiper Belt, land reform, Leo Hollis, liberal capitalism, low earth orbit, low interest rates, low skilled workers, M-Pesa, market fundamentalism, means of production, mobile money, more computing power than Apollo, new economy, off grid, pattern recognition, Peter H. Diamandis: Planetary Resources, post scarcity, post-work, price mechanism, price stability, private spaceflight, Productivity paradox, profit motive, race to the bottom, rewilding, RFID, rising living standards, Robert Solow, scientific management, Second Machine Age, self-driving car, sensor fusion, shareholder value, Silicon Valley, Simon Kuznets, Slavoj Žižek, SoftBank, stem cell, Stewart Brand, synthetic biology, technological determinism, technoutopianism, the built environment, the scientific method, The Wealth of Nations by Adam Smith, Thomas Malthus, transatlantic slave trade, Travis Kalanick, universal basic income, V2 rocket, Watson beat the top human players on Jeopardy!, We are as Gods, Whole Earth Catalog, working-age population

The evidence appears to lend at least some weight to Leontief’s conclusion, nowhere more so than in manufacturing. In 1970 there were around 1,000 industrial robots worldwide. By the beginning of 2016 that number had risen to 1.8 million and is expected to exceed 3 million by 2020. Since 2010 the global stock of industrial robots has increased by an annual average of more than 10 per cent. Compound growth means if that trend persists manufacturing won’t just stop creating jobs – as it already has done despite massively increased output – but their numbers will significantly decline. The ever-greater employment of industrial robots correlates entirely with what can be observed in both manufacturing jobs and output.

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While progress over the last half century has been dizzying, the parable of rice grains on the chessboard remains instructive. If such trends persist for another six decades, the results – like the pile of rice bigger than Everest – are almost beyond comprehension. If that single field of rice halfway up the board represents global real-time communication and millions of industrial robots, then what is the mountain? Can Moore’s Law Endure? The transformative power of Moore’s Law, should it persist, is inarguable. The key question, then, is how much longer it can endure. In 2015 researchers at Intel foresaw it prevailing for at least another ten years, although by the standards of a trajectory more than five decades old, that hardly counts as optimistic.

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Bradford DeLong would write in August 2001, just a month after the file-sharing service Napster was taken down, ‘the most basic condition for economic efficiency … [is] that price equal marginal cost.’ They went on: ‘with information goods, the social and marginal cost of distribution is close to zero.’ This held true not only for films, music, books and academic papers but also for the design of an industrial robot or pharmaceutical drug. Indeed, as subsequent chapters will make clear, it holds true for ever broader swathes of the economy. Therein lies the paradox for capitalism, a system under which things are produced for exchange and profit. If information goods are to be distributed at their marginal cost of production – zero – they cannot be created and produced by entrepreneurial firms that use revenues obtained from sales to consumers to cover their costs.

A World Without Work: Technology, Automation, and How We Should Respond by Daniel Susskind

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Yet it is worth remembering that Amazon is among the most advanced users of robotics, with a fleet of over one hundred thousand ground-based robots across its warehouses.24 And some robots today are already capable of accomplishing remarkable physical feats, like opening doors and climbing walls, ascending stairs and landing backflips, carrying cables over harsh terrain and knotting ropes together in midair.25 Meanwhile, the global population of industrial robots is rising steadily: the International Federation of Robotics, a trade association, anticipates there will be more than three million of them in operation in 2020, double the number in 2014.27 Figure 5.1: Global Stock of Industrial Robots (000’s)26 The car manufacturing industry provides a good case study of task encroachment unfolding in the industrial world. Once upon a time, building a car was a bespoke activity, where craftsmen made each component from scratch.

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When Daron Acemoglu and Pascual Restrepo looked at the use of industrial robots in the United States from 1990 to 2007, they found a contemporary case of the substituting force overrunning the complementing force, reducing the demand for workers across the entire economy. Remember that in thinking about new technologies, we are used to stories like that of the ATM: machines displace some people, but also raise the demand for their work elsewhere, and overall employment stays the same or even rises. But that is not what happened with industrial robots. On average, one more robot per thousand workers meant about 5.6 fewer jobs in the entire economy, and wages that were about 0.5 percent lower across the whole economy as well.

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And all this was happening in 2007, more than a decade ago, before most of the technological advances described in the preceding pages.32 Critics might point out that this result applied not to all technologies, but only to one particular category, industrial robots. But that misses the deeper point: traditionally, many economists have imagined that this result was not possible for any technology. The illusion nurtured in the Age of Labor was that any technological progress ultimately benefits workers overall. But here, even after taking into account the ways in which these industrial robots helped some human beings through the complementing force, workers overall were still worse off. THE TIMING How long will it take to arrive at a world with less work?

The Globotics Upheaval: Globalisation, Robotics and the Future of Work by Richard Baldwin

agricultural Revolution, Airbnb, AlphaGo, AltaVista, Amazon Web Services, Apollo 11, augmented reality, autonomous vehicles, basic income, Big Tech, bread and circuses, business process, business process outsourcing, call centre, Capital in the Twenty-First Century by Thomas Piketty, Cass Sunstein, commoditize, computer vision, Corn Laws, correlation does not imply causation, Credit Default Swap, data science, David Ricardo: comparative advantage, declining real wages, deep learning, DeepMind, deindustrialization, deskilling, Donald Trump, Douglas Hofstadter, Downton Abbey, Elon Musk, Erik Brynjolfsson, facts on the ground, Fairchild Semiconductor, future of journalism, future of work, George Gilder, Google Glasses, Google Hangouts, Hans Moravec, hiring and firing, hype cycle, impulse control, income inequality, industrial robot, intangible asset, Internet of things, invisible hand, James Watt: steam engine, Jeff Bezos, job automation, Kevin Roose, knowledge worker, laissez-faire capitalism, Les Trente Glorieuses, low skilled workers, machine translation, Machine translation of "The spirit is willing, but the flesh is weak." to Russian and back, manufacturing employment, Mark Zuckerberg, mass immigration, mass incarceration, Metcalfe’s law, mirror neurons, new economy, optical character recognition, pattern recognition, Ponzi scheme, post-industrial society, post-work, profit motive, remote working, reshoring, ride hailing / ride sharing, Robert Gordon, Robert Metcalfe, robotic process automation, Ronald Reagan, Salesforce, San Francisco homelessness, Second Machine Age, self-driving car, side project, Silicon Valley, Skype, Snapchat, social intelligence, sovereign wealth fund, standardized shipping container, statistical model, Stephen Hawking, Steve Jobs, supply-chain management, systems thinking, TaskRabbit, telepresence, telepresence robot, telerobotics, Thomas Malthus, trade liberalization, universal basic income, warehouse automation

Computer-controlled machines rapidly displaced workers, especially in the auto industry, and especially those involved in welding, painting, and specific pick-and-place tasks. As ICT advanced, the repetitive, manual tasks that industrial robots could handle increased—displacing jobs as it went. From the 1990s, many factories in advanced economies turned into computer systems where the peripherals were industrial robots, computerized machine tools, guided vehicles, and so on. Roger Smith’s dream of Hamtramck-like factories supplanting workers came true, or mostly true. Factories became places where workers helped machines make things, not the other way around.

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NEW TECHNOLOGICAL IMPULSE The Hamtramck auto factory in Detroit, Michigan, was supposed to be “the most modern auto plant in the world,” according to General Motors (GM) chief Roger Smith. But that’s not what he was calling it after they turned on the lights and ramped up production in 1985. What was supposed to be a showcase for the cost-cutting and quality-boosting advantages of industrial robots turned into a clump of chaos. The painting robots melted the plastic taillights and occasionally went wild, painting each other, and the walls as well as the cars. The robots fitting the windshields sometimes got confused and sent the glass smashing into the car instead of installing it gently.

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PHYSICAL SKILLS Physical skills are important in a wide range of service-sector and professional jobs. Some of the physical skills involve moving things a long way (“gross motor skills”) or over only very short distances (“fine motor skills/dexterity”). Another set entails “mobility across unknown terrain,” and “navigation.” (Table 6.4) Not surprisingly, industrial robots—what might be called “steel-collar robots” to contrast them with white-collar robots—are above average when it comes to most physical skills. They are, after all, machines. One area where they are not as good as the average person is in mobility in places they are not familiar with. Moving around an Amazon warehouse, for instance, poses no issues for AI-trained robots, but crossing rugged or unusual terrain is a skill where AI displays below-human capacities.

China's Disruptors: How Alibaba, Xiaomi, Tencent, and Other Companies Are Changing the Rules of Business by Edward Tse

3D printing, Airbnb, Airbus A320, Asian financial crisis, barriers to entry, bilateral investment treaty, business process, capital controls, commoditize, conceptual framework, corporate governance, creative destruction, crowdsourcing, currency manipulation / currency intervention, David Graeber, Deng Xiaoping, disruptive innovation, experimental economics, global supply chain, global value chain, Great Leap Forward, high net worth, high-speed rail, household responsibility system, industrial robot, Joseph Schumpeter, Lyft, Masayoshi Son, middle-income trap, money market fund, offshore financial centre, Pearl River Delta, reshoring, rising living standards, risk tolerance, Silicon Valley, Skype, Snapchat, SoftBank, sovereign wealth fund, special economic zone, speech recognition, Steve Jobs, thinkpad, trade route, wealth creators, working-age population

Over the past 20 years China has increased its grain productivity by 2.6 percent annually: See Xinhua News Agency, “Chinese Innovations to Benefit the World: Bill Gates,” April 7, 2014, available at http://www.chinadaily.com.cn/business/2013-04/07/content_16381042.htm (accessed September 2, 2014). China is now the world’s biggest industrial robot market: See “Industrial Robot Statistics,” International Federation of Robotics, 2014, available at http://www.ifr.org/industrial-robots/statistics/ (accessed September 2, 2014). officials have committed $82 billion over the five years: See Christina Larson, “China Expected to Be the Top Market for Industrial Robots by 2016,” Bloomberg Businessweek, November 15, 2013, available at http://www.businessweek.com/articles/2013-11-15/china-expected-to-be-top-market-for-industrial-robots-by-2016 (accessed September 2, 2014). the world’s leading developer of 3D printing technology: See “China Developing World’s Largest 3D Printer, Prints 6m Metal Parts in One Piece,” 3ders.org, February 7, 2014, available at http://www.3ders.org/articles/20140207-china-developing-world-largest-3d-printer--prints-6m-metal-parts-in-one-piece.html (accessed September 2, 2014).

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The likelihood, however, is rather the opposite: as Chinese companies refine their ability to introduce new practices and technologies to enhance their manufacturing prowess, they will find themselves in a strong position to claim a greater share of higher-end processes. Robots are widely regarded as a solution to worker shortages and rising wages. After robotics sales to China rose 25 percent annually from 2005 to 2012, and then jumped 36 percent in 2013, China is now the world’s biggest industrial robot market, accounting for one-fifth of all sales. Many of these robots are used in the auto industry, where the number deployed rose from just over 50 per 10,000 staff in 2006 to more than 200 as of mid 2014. In Zhejiang, one of China’s leading industrial provinces, just to the south of Shanghai, officials have committed $82 billion over the five years through 2017 for factories to invest in automating production lines.

When Computers Can Think: The Artificial Intelligence Singularity by Anthony Berglas, William Black, Samantha Thalind, Max Scratchmann, Michelle Estes

3D printing, Abraham Maslow, AI winter, air gap, anthropic principle, artificial general intelligence, Asilomar, augmented reality, Automated Insights, autonomous vehicles, availability heuristic, backpropagation, blue-collar work, Boston Dynamics, brain emulation, call centre, cognitive bias, combinatorial explosion, computer vision, Computing Machinery and Intelligence, create, read, update, delete, cuban missile crisis, David Attenborough, DeepMind, disinformation, driverless car, Elon Musk, en.wikipedia.org, epigenetics, Ernest Rutherford, factory automation, feminist movement, finite state, Flynn Effect, friendly AI, general-purpose programming language, Google Glasses, Google X / Alphabet X, Gödel, Escher, Bach, Hans Moravec, industrial robot, Isaac Newton, job automation, John von Neumann, Law of Accelerating Returns, license plate recognition, Mahatma Gandhi, mandelbrot fractal, natural language processing, Nick Bostrom, Parkinson's law, patent troll, patient HM, pattern recognition, phenotype, ransomware, Ray Kurzweil, Recombinant DNA, self-driving car, semantic web, Silicon Valley, Singularitarianism, Skype, sorting algorithm, speech recognition, statistical model, stem cell, Stephen Hawking, Stuxnet, superintelligent machines, technological singularity, Thomas Malthus, Turing machine, Turing test, uranium enrichment, Von Neumann architecture, Watson beat the top human players on Jeopardy!, wikimedia commons, zero day

A logical illusion that could never exist in reality. But it is, in fact, commonplace for computers to program themselves when guided by people. Similar to the way that 3-D printers can print many of the parts used to make 3-D printers. Industrial robots can be used to make industrial robots. It is only a matter of time before a combination of 3-D printers, industrial robots and automatic milling machines automatically produce 3-D printers, industrial robots and automatic milling machines. In that case, the sorcerer’s apprentice might have had a relatively easy problem to deal with. Computers ultimately execute instructions that have been written in ones and zeros, but they are not programmed that way.

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A task such as carving a clarinet could take a skilled artisan several hours, whereas a fully automated milling machine can complete the task in a few minutes. Shipments of industrial robots. Corporate http://www.ifr.org/industrial-robots/statistics/ More recently, the use of single-arm industrial robots has become ubiquitous for repetitive tasks such as welding, painting and parts assembly. Robots now cost roughly $50,000 for the arm, plus as much again for specialized tooling such as welders, cutters or paint sprayers. They have become very competitive with the cost of labour in the western world. Robots are made by robots, so their price is likely to reduce over time. As previously discussed, most current industrial robots have no intelligence whatsoever.

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Blog John Brolese on http://www.abc.net.au/news/2011-12-13/close-up–a-spider-wasp-takes-on-aspider/3729180 These behaviours are is is often attributed to being just instinct, as neither the spiders nor the wasps consciously know why they do what they do, but there is nothing “just” about these instincts. Every spider’s web is different depending on the location. It cannot simply make a rigidly predetermined sequence of moves, like ordinary industrial robots do. Instead, it has to sense its natural environment in order to produce a web that works. The instinct certainly provides a basic plan, such as to start with the top line and then drop radials, and finally the spiral. But realizing that basic plan in a chaotic natural environment requires much more intelligence than is possessed by current robots.

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

Throughout its short history, cyber crime has always been hidden behind computer screens—a two-dimensional problem that might affect your wallet or your bank account. No more. As a result of advances in robotics, cyber crime will finally escape its virtual confines and explode onto our physical space. And we are wholly unprepared for what is coming next. The Military-Industrial (Robotic) Complex For decades, industrial robots have toiled side by side with human workers in warehouses and on factory floors, but modern industrial robots are marvels of engineering, capable of lifting hundreds of pounds and moving objects repeatedly to within 0.006 inch’s accuracy, a feat no human being could match. Initially, these machines were expensive, often costing hundreds of thousands of dollars and requiring months of highly customized computer programming before they could perform their assigned tasks.

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These robots work three shifts a day, 365 days a year, and never take a coffee break. Industrial robots are growing exponentially cheaper, more efficient, and more user-friendly, and perhaps no other robot exemplifies this trend as much as Baxter, the cute low-cost industrial bot from Rethink Robotics. At $22,000, it is a tenth of the price of its predecessors. More impressive is the fact that it works right out of the box and can be up and running in just an hour, as opposed to the eighteen months it took to integrate the previous generations of industrial robots into a factory operation. Baxter can learn to do simple tasks, such as “pick and place” objects on an assembly line, in just five minutes.

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Cacace, affidavit, Sept. 28, 2011, http://​www.​justice.​gov/; “Muslim Pleads Guilty to Plotting to Blow Up the Pentagon and Capitol with Model Airplanes Packed with Explosives,” Mail Online, July 20, 2012; “US Man Admits Model Plane Plot,” BBC News; Brian Ballou, “Rezwan Ferdaus of Ashland Sentenced to 17 Years in Terror Plot; Plotted to Blow Up Pentagon, Capitol,” Boston.com, Nov. 1, 2012; Jess Bidgood, “Rezwan Ferdaus of Massachusetts Gets 17 Years in Terrorist Plot,” New York Times, Nov. 2, 2012. 2 The number of robotics start-up companies: “Global Industrial Robotics Market Revenues to Surpass $37 Billion by 2018,” Business Wire, Feb. 24, 2014. 3 “where bits from the digital realm”: Marcus Wohlsen, “Forget Robots. We’ll Soon Be Fusing Technology with Living Matter,” Wired, May 27, 2014. 4 Despite the costs: Industrial Federation of Robotics, http://​www.​ifr.​org/​industrial-​robots/​statistics/. 5 In just one Hyundai factory: “Car, Airbag, Money: Robots Make Cars,” video, http://​channel.​nationalgeographic.​com/; Tamara Walsh, “Rise of the Robots: 2 Industries Increasingly Turning to Robotics for Innovation,” Motley Fool, Aug. 24, 2014. 6 Not to be outdone: Katie Lobosco, “Army of Robots to Invade Amazon Warehouses,” CNNMoney, May 22, 2014. 7 More impressive is the fact: Rodney Brooks, “Robots at Work,” World Future Society, Futurist, May–June 2013. 8 In more than 150 medical centers: “The Invisible Unarmed,” Economist, March 29, 2014. 293 Over 500,000 such operations: Stewart Pinkerton, “The Pros and Cons of Robotic Surgery,” Wall Street Journal, Nov. 17, 2013. 9 Using similar technology: Jacques Marescaux et al., “Transcontinental Robot-Assisted Remote Telesurgery: Feasibility and Potential Applications,” Annals of Surgery 235, no. 4 (2002): 300–301. 10 Though the gains: For a definitive view into the world of military robotics, see Peter W.

Augmented: Life in the Smart Lane by Brett King

23andMe, 3D printing, additive manufacturing, Affordable Care Act / Obamacare, agricultural Revolution, Airbnb, Albert Einstein, Amazon Web Services, Any sufficiently advanced technology is indistinguishable from magic, Apollo 11, Apollo Guidance Computer, Apple II, artificial general intelligence, asset allocation, augmented reality, autonomous vehicles, barriers to entry, bitcoin, Bletchley Park, blockchain, Boston Dynamics, business intelligence, business process, call centre, chief data officer, Chris Urmson, Clayton Christensen, clean water, Computing Machinery and Intelligence, congestion charging, CRISPR, crowdsourcing, cryptocurrency, data science, deep learning, DeepMind, deskilling, different worldview, disruptive innovation, distributed generation, distributed ledger, double helix, drone strike, electricity market, Elon Musk, Erik Brynjolfsson, Fellow of the Royal Society, fiat currency, financial exclusion, Flash crash, Flynn Effect, Ford Model T, future of work, gamification, Geoffrey Hinton, gig economy, gigafactory, Google Glasses, Google X / Alphabet X, Hans Lippershey, high-speed rail, Hyperloop, income inequality, industrial robot, information asymmetry, Internet of things, invention of movable type, invention of the printing press, invention of the telephone, invention of the wheel, James Dyson, Jeff Bezos, job automation, job-hopping, John Markoff, John von Neumann, Kevin Kelly, Kickstarter, Kim Stanley Robinson, Kiva Systems, Kodak vs Instagram, Leonard Kleinrock, lifelogging, low earth orbit, low skilled workers, Lyft, M-Pesa, Mark Zuckerberg, Marshall McLuhan, megacity, Metcalfe’s law, Minecraft, mobile money, money market fund, more computing power than Apollo, Neal Stephenson, Neil Armstrong, Network effects, new economy, Nick Bostrom, obamacare, Occupy movement, Oculus Rift, off grid, off-the-grid, packet switching, pattern recognition, peer-to-peer, Ray Kurzweil, retail therapy, RFID, ride hailing / ride sharing, Robert Metcalfe, Salesforce, Satoshi Nakamoto, Second Machine Age, selective serotonin reuptake inhibitor (SSRI), self-driving car, sharing economy, Shoshana Zuboff, Silicon Valley, Silicon Valley startup, Skype, smart cities, smart grid, smart transportation, Snapchat, Snow Crash, social graph, software as a service, speech recognition, statistical model, stem cell, Stephen Hawking, Steve Jobs, Steve Wozniak, strong AI, synthetic biology, systems thinking, TaskRabbit, technological singularity, TED Talk, telemarketer, telepresence, telepresence robot, Tesla Model S, The future is already here, The Future of Employment, Tim Cook: Apple, trade route, Travis Kalanick, TSMC, Turing complete, Turing test, Twitter Arab Spring, uber lyft, undersea cable, urban sprawl, V2 rocket, warehouse automation, warehouse robotics, Watson beat the top human players on Jeopardy!, white picket fence, WikiLeaks, yottabyte

The Robot Growth Explosion Robots are still relatively rare today. Within a couple of decades though, they will outnumber the world’s population. In 2014, sales of industrial robots increased 29 per cent to 229,261 units, according to the International Federation of Robotics.4 In 2000, the population of industrial robots was around 1 million, with 40 per cent of those being situated in Japan, but by 2010 the global industrial robot population had ballooned to close to 9 million.5 Nevertheless, industrial robots are only a small part of the robot population. According to a research study by Tractica, annual shipments of consumer robots, a category that includes robotic vacuums, lawn mowers and pool cleaners as well as social robots, will increase from at least 6.6 million units in 2015 to more than 31 million units worldwide by 2020, with a cumulative total of nearly 100 million consumer robots shipped during that period.

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The term is an eponym, named after the famous inventor Thomas Edison. 3 In 1970, Masahiro Mori, a professor at the Tokyo Institute of Technology, published a two-page, koan-like article entitled “Bukimi No Tani” (不気味の谷, “The Uncanny Valley”) in an obscure Japanese journal called Energy. After 40 years, it is still considered one of the defining essays on robotics in society. 4 International Federation of Robotics, http://www.ifr.org/industrial-robots/statistics/. 5 IEEE.org, http://spectrum.ieee.org/automaton/robotics/industrial-robots/041410-world-robot-population. 6 iRobot financial reports 7 Michael Addady, “The number of drones expected to sell during the holidays is scaring the government,” Fortune, 29 September 2015. 8 Author’s own estimate based on PricewaterhouseCoopers (PWC), IHC research and annual vehicle sales projections 9 As do autonomous vehicles, the Hubble Space Telescope and my iRobot vacuum cleaner 10 http://www.pbs.org/newshour/rundown/smart-robots-will-take-third-jobs-2025-gartner-says/ 11 Kevin Kelly, “Better than human: Why Robots Will—and Must—Take our Jobs,” Wired, 24 December 2014, http://www.wired.com/2012/12/ff-robots-will-take-our-jobs/. 12 “Amazon Acquires Kiva Systems in Second-Biggest Takeover,” Bloomberg Business, 19 March 2012. 13 Called Hangar One, the hangar is located at Moffett Federal Airfield.

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The Internet, and with it broad technology automation, has created a more serious problem for employment. Erik Brynjolfsson, a professor at the MIT Sloan School of Management, and his collaborator Andrew McAfee have been arguing for the last five years that advances in computer technology—from improved industrial robotics to automated translation services—are largely behind the sluggish employment growth of the last 10 to 15 years.30 Figure 1.11: Productivity changes related to employment and median family income (Credit: HBR) Brynjolfsson and McAfee analysed the last 70 years of employment data and found that while productivity has continued to improve, employment has not kept up pace in recent years.

Power and Progress: Our Thousand-Year Struggle Over Technology and Prosperity by Daron Acemoglu, Simon Johnson

"Friedman doctrine" OR "shareholder theory", "World Economic Forum" Davos, 4chan, agricultural Revolution, AI winter, Airbnb, airline deregulation, algorithmic bias, algorithmic management, Alignment Problem, AlphaGo, An Inconvenient Truth, artificial general intelligence, augmented reality, basic income, Bellingcat, Bernie Sanders, Big Tech, Bletchley Park, blue-collar work, British Empire, carbon footprint, carbon tax, carried interest, centre right, Charles Babbage, ChatGPT, Clayton Christensen, clean water, cloud computing, collapse of Lehman Brothers, collective bargaining, computer age, Computer Lib, Computing Machinery and Intelligence, conceptual framework, contact tracing, Corn Laws, Cornelius Vanderbilt, coronavirus, corporate social responsibility, correlation does not imply causation, cotton gin, COVID-19, creative destruction, declining real wages, deep learning, DeepMind, deindustrialization, Demis Hassabis, Deng Xiaoping, deskilling, discovery of the americas, disinformation, Donald Trump, Douglas Engelbart, Douglas Engelbart, Edward Snowden, Elon Musk, en.wikipedia.org, energy transition, Erik Brynjolfsson, European colonialism, everywhere but in the productivity statistics, factory automation, facts on the ground, fake news, Filter Bubble, financial innovation, Ford Model T, Ford paid five dollars a day, fulfillment center, full employment, future of work, gender pay gap, general purpose technology, Geoffrey Hinton, global supply chain, Gordon Gekko, GPT-3, Grace Hopper, Hacker Ethic, Ida Tarbell, illegal immigration, income inequality, indoor plumbing, industrial robot, interchangeable parts, invisible hand, Isaac Newton, Jacques de Vaucanson, James Watt: steam engine, Jaron Lanier, Jeff Bezos, job automation, Johannes Kepler, John Markoff, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, Joseph-Marie Jacquard, Kenneth Arrow, Kevin Roose, Kickstarter, knowledge economy, labor-force participation, land reform, land tenure, Les Trente Glorieuses, low skilled workers, low-wage service sector, M-Pesa, manufacturing employment, Marc Andreessen, Mark Zuckerberg, megacity, mobile money, Mother of all demos, move fast and break things, natural language processing, Neolithic agricultural revolution, Norbert Wiener, NSO Group, offshore financial centre, OpenAI, PageRank, Panopticon Jeremy Bentham, paperclip maximiser, pattern recognition, Paul Graham, Peter Thiel, Productivity paradox, profit maximization, profit motive, QAnon, Ralph Nader, Ray Kurzweil, recommendation engine, ride hailing / ride sharing, Robert Bork, Robert Gordon, Robert Solow, robotic process automation, Ronald Reagan, scientific management, Second Machine Age, self-driving car, seminal paper, shareholder value, Sheryl Sandberg, Shoshana Zuboff, Silicon Valley, social intelligence, Social Responsibility of Business Is to Increase Its Profits, social web, South Sea Bubble, speech recognition, spice trade, statistical model, stem cell, Steve Jobs, Steve Wozniak, strikebreaker, subscription business, Suez canal 1869, Suez crisis 1956, supply-chain management, surveillance capitalism, tacit knowledge, tech billionaire, technoutopianism, Ted Nelson, TED Talk, The Future of Employment, The Rise and Fall of American Growth, The Structural Transformation of the Public Sphere, The Wealth of Nations by Adam Smith, theory of mind, Thomas Malthus, too big to fail, total factor productivity, trade route, transatlantic slave trade, trickle-down economics, Turing machine, Turing test, Twitter Arab Spring, Two Sigma, Tyler Cowen, Tyler Cowen: Great Stagnation, union organizing, universal basic income, Unsafe at Any Speed, Upton Sinclair, upwardly mobile, W. E. B. Du Bois, War on Poverty, WikiLeaks, wikimedia commons, working poor, working-age population

After all, the company needs more workers, such as welders and painters, to meet the additional demand, and it will pay them more, if necessary. In contrast, consider what happens when the same automaker installs industrial robots. Robots can perform most welding and painting tasks, and can do so more cheaply than production methods employing a larger number of workers. As a result, the company’s average productivity increases significantly, but it has less need for human welders and painters. This is a general problem. Many new technologies, like industrial robots, expand the set of tasks performed by machines and algorithms, displacing workers who used to be employed in these tasks.

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Most people around the globe today are better off than our ancestors because citizens and workers in early industrial societies organized, challenged elite-dominated choices about technology and work conditions, and forced ways of sharing the gains from technical improvements more equitably. Today we need to do the same again. The good news is that incredible tools are available to us, including magnetic resonance imaging (MRI), mRNA vaccines, industrial robots, the internet, tremendous computational power, and massive amounts of data on things we could not measure before. We can use these innovations to solve real problems—but only if these awesome capabilities are focused on helping people. This is not the direction in which we are currently heading, however.

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Some innovations boost how much individuals contribute to production, rather than automating or offshoring work. For example, new software tools that aid the tasks of car mechanics and enable greater precision work increase worker marginal productivity. This is completely different from installing industrial robots with the goal of replacing people. Even more important for raising worker marginal productivity is the creation of new tasks. There was plenty of automation in car manufacturing during the momentous reorganization of the industry led by Henry Ford starting in the 1910s. But mass-production methods and assembly lines simultaneously introduced a range of new design, technical, machine-operation, and clerical tasks, boosting the industry’s demand for workers (as we will detail in Chapter 7).

The Technology Trap: Capital, Labor, and Power in the Age of Automation by Carl Benedikt Frey

3D printing, AlphaGo, Alvin Toffler, autonomous vehicles, basic income, Bernie Sanders, Branko Milanovic, British Empire, business cycle, business process, call centre, Cambridge Analytica, Capital in the Twenty-First Century by Thomas Piketty, Charles Babbage, Clayton Christensen, collective bargaining, computer age, computer vision, Corn Laws, Cornelius Vanderbilt, creative destruction, data science, David Graeber, David Ricardo: comparative advantage, deep learning, DeepMind, deindustrialization, demographic transition, desegregation, deskilling, Donald Trump, driverless car, easy for humans, difficult for computers, Edward Glaeser, Elon Musk, Erik Brynjolfsson, everywhere but in the productivity statistics, factory automation, Fairchild Semiconductor, falling living standards, first square of the chessboard / second half of the chessboard, Ford Model T, Ford paid five dollars a day, Frank Levy and Richard Murnane: The New Division of Labor, full employment, future of work, game design, general purpose technology, Gini coefficient, Great Leap Forward, Hans Moravec, high-speed rail, Hyperloop, income inequality, income per capita, independent contractor, industrial cluster, industrial robot, intangible asset, interchangeable parts, Internet of things, invention of agriculture, invention of movable type, invention of the steam engine, invention of the wheel, Isaac Newton, James Hargreaves, James Watt: steam engine, Jeremy Corbyn, job automation, job satisfaction, job-hopping, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, Joseph Schumpeter, Kickstarter, Kiva Systems, knowledge economy, knowledge worker, labor-force participation, labour mobility, Lewis Mumford, Loebner Prize, low skilled workers, machine translation, Malcom McLean invented shipping containers, manufacturing employment, mass immigration, means of production, Menlo Park, minimum wage unemployment, natural language processing, new economy, New Urbanism, Nick Bostrom, Norbert Wiener, nowcasting, oil shock, On the Economy of Machinery and Manufactures, OpenAI, opioid epidemic / opioid crisis, Pareto efficiency, pattern recognition, pink-collar, Productivity paradox, profit maximization, Renaissance Technologies, rent-seeking, rising living standards, Robert Gordon, Robert Solow, robot derives from the Czech word robota Czech, meaning slave, safety bicycle, Second Machine Age, secular stagnation, self-driving car, seminal paper, Silicon Valley, Simon Kuznets, social intelligence, sparse data, speech recognition, spinning jenny, Stephen Hawking, tacit knowledge, The Future of Employment, The Rise and Fall of American Growth, The Wealth of Nations by Adam Smith, Thomas Malthus, total factor productivity, trade route, Triangle Shirtwaist Factory, Turing test, union organizing, universal basic income, warehouse automation, washing machines reduced drudgery, wealth creators, women in the workforce, working poor, zero-sum game

Meanwhile, in places specializing in routine manufacturing work, automation has had the opposite effect: it has replaced workers rather than creating new functions for them. FIGURE 16: The U.S. Geography of Industrial Robots, 2016 Source: International Federation of Robotics (database), 2016, World Robotics: Industrial Robots, Frankfurt am Main, https://ifr.org/worldrobotics/; S. Ruggles et al., 2018, IPUMS USA, version 8.0 (dataset). https://usa.ipums.org/usa/. Note: This figure shows the number of industrial robots per thousand workers across America in 2016. Darker shades correspond to more robots per thousand workers. County boundaries are based on maps from IPUMS NHGIS (www.nhgis.org).

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When new technologies replace workers in existing tasks, those workers’ skills become obsolete. Even when technologies are replacing for some but augmenting for others, workers might suffer hardships. In recent years, the creation of new jobs for robotics engineers has provided little relief to those who lost their jobs to industrial robots on the assembly lines. The arrival of the power loom, in similar fashion, replaced the jobs of hand-loom weavers, while creating new jobs for power-loom weavers. But while hand-loom weavers’ incomes diminished almost immediately, it took decades for the wages of power-loom weavers to rise, as they had to acquire new skills and a new labor market had to develop for those skills.36 Because replacing technological progress often comes with what Schumpeter called a “perennial gale of creative destruction,” there are always winners and losers.37 The overwhelming focus of popular commentary on unanswerable questions like whether there will be enough jobs in 2050 is unfortunate.

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Workers’ jobs were turned into mechanical motions, in which conveyors brought the task to the worker. Such specialization greatly increased productivity in American factories but brought greater monotony for the worker. From this point of view, factory automation can be regarded as a blessing because it meant that industrial robots, controlled by computers, could eliminate the need for direct human intervention in operating machines. Instead of having workers specializing in machine tending, many routine tasks could suddenly be performed by robots with a higher degree of accuracy. As automation progressed, more complex and creative functions became more plentiful.

Driverless: Intelligent Cars and the Road Ahead by Hod Lipson, Melba Kurman

AI winter, Air France Flight 447, AlphaGo, Amazon Mechanical Turk, autonomous vehicles, backpropagation, barriers to entry, butterfly effect, carbon footprint, Chris Urmson, cloud computing, computer vision, connected car, creative destruction, crowdsourcing, DARPA: Urban Challenge, deep learning, digital map, Donald Shoup, driverless car, Elon Musk, en.wikipedia.org, Erik Brynjolfsson, General Motors Futurama, Geoffrey Hinton, Google Earth, Google X / Alphabet X, Hans Moravec, high net worth, hive mind, ImageNet competition, income inequality, industrial robot, intermodal, Internet of things, Jeff Hawkins, job automation, Joseph Schumpeter, lone genius, Lyft, megacity, Network effects, New Urbanism, Oculus Rift, pattern recognition, performance metric, Philippa Foot, precision agriculture, RFID, ride hailing / ride sharing, Second Machine Age, self-driving car, Silicon Valley, smart cities, speech recognition, statistical model, Steve Jobs, technoutopianism, TED Talk, Tesla Model S, Travis Kalanick, trolley problem, Uber and Lyft, uber lyft, Unsafe at Any Speed, warehouse robotics

Mike Ramsey, “Ford, Mercedes-Benz Set Up Shop in Silicon Valley,” Wall Street Journal, March 27, 2015, http://www.wsj.com/articles/ford-mercedes-set-up-shop-in-silicon-valley-1427475558 5. “Autonomous Vehicles: Self-Driving—the New Auto Industry Paradigm,” Morgan Stanley Research, December 6, 2013. 6. Industrial Robot Statistics, World Robotics 2015, March 19, 2016, http://www.ifr.org/industrial-robots/statistics/ 7. Scott Corwin, Joe Vitale, Eamonn Kelly, and Elizabeth Cathles, “The Future of Mobility,” Deloitte Report, September 24, 2015, http://dupress.com/articles/future-of-mobility-transportation-technology 8. Adrienne LaFrance, “The High-Stakes Race to Rid the World of Human Drivers,” Atlantic, December 1, 2015, http://www.theatlantic.com/technology/archive/2015/12/driverless-cars-are-this-centurys-space-race/417672/ 9.

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Some programs recognized the presence of a distinct visual feature in an image and compared that feature against a database of visual features. Many of these techniques worked well. In fact, many are still used by modern industrial robots to carry out concrete tasks, such as inspecting complex circuit boards or sorting machine parts into bins. A critical limitation of rule-based machine-vision software, however, is that it works best in structured environments where the robot’s machine vision will encounter only a selected set of objects. Show a banana to an industrial robot that’s programmed to sort only nuts and bolts and it will be dumbfounded, baffled by this novel yellow object that doesn’t match anything in its image library.

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For decades, researchers in the field of machine vision have tried and failed to create software that, like us, is capable of rapidly and accurately “understanding” the visual environment. The lack of such software has been a major technological barrier in the field of mobile robotics research. For most of their history, robots have struggled to process visual information. Industrial robots deal with this shortcoming by toiling blindly in closed-world environments in dark, unlit factories. For robots whose work involves some kind of visual activity, their workday is set up in such a way that they are never asked to classify or inspect objects that are unfamiliar to them. One of the barriers to the development of machine vison software has been insufficient computing power.

The Industries of the Future by Alec Ross

"World Economic Forum" Davos, 23andMe, 3D printing, Airbnb, Alan Greenspan, algorithmic bias, algorithmic trading, AltaVista, Anne Wojcicki, autonomous vehicles, banking crisis, barriers to entry, Bernie Madoff, bioinformatics, bitcoin, Black Lives Matter, blockchain, Boston Dynamics, Brian Krebs, British Empire, business intelligence, call centre, carbon footprint, clean tech, cloud computing, collaborative consumption, connected car, corporate governance, Credit Default Swap, cryptocurrency, data science, David Brooks, DeepMind, Demis Hassabis, disintermediation, Dissolution of the Soviet Union, distributed ledger, driverless car, Edward Glaeser, Edward Snowden, en.wikipedia.org, Erik Brynjolfsson, Evgeny Morozov, fiat currency, future of work, General Motors Futurama, global supply chain, Google X / Alphabet X, Gregor Mendel, industrial robot, information security, Internet of things, invention of the printing press, Jaron Lanier, Jeff Bezos, job automation, John Markoff, Joi Ito, Kevin Roose, Kickstarter, knowledge economy, knowledge worker, lifelogging, litecoin, low interest rates, M-Pesa, machine translation, Marc Andreessen, Mark Zuckerberg, Max Levchin, Mikhail Gorbachev, military-industrial complex, mobile money, money: store of value / unit of account / medium of exchange, Nelson Mandela, new economy, off-the-grid, offshore financial centre, open economy, Parag Khanna, paypal mafia, peer-to-peer, peer-to-peer lending, personalized medicine, Peter Thiel, precision agriculture, pre–internet, RAND corporation, Ray Kurzweil, recommendation engine, ride hailing / ride sharing, Rubik’s Cube, Satoshi Nakamoto, selective serotonin reuptake inhibitor (SSRI), self-driving car, sharing economy, Silicon Valley, Silicon Valley startup, Skype, smart cities, social graph, software as a service, special economic zone, supply-chain management, supply-chain management software, technoutopianism, TED Talk, The Future of Employment, Travis Kalanick, underbanked, unit 8200, Vernor Vinge, Watson beat the top human players on Jeopardy!, women in the workforce, work culture , Y Combinator, young professional

In Europe, all 28 member states: Eurostat, European Commission, “Population Structure and Ageing,” http://epp.eurostat.ec.europa.eu/statistics_explained/index.php/Population_structure_and_ageing; “European Commission Ageing Report: Europe Needs to Prepare for Growing Older,” May 15, 2015, http://ec.europa.eu/economy_finance/articles/structural_reforms/2012-05-15_ageing_report_en.htm. A few countries have already established: “Industrial Robot Statistics: World Robotics 2014 Industrial Robots,” International Federation of Robotics, http://www.ifr.org/industrial-robots/statistics/. Japan, the United States, and Germany dominate the landscape: Josh Bond, “Robot Report Predicts Significant Growth in Coming Decade,” Logistics Management, April 25, 2013, http://www.logisticsmgmt.com/article/robot_report_predicts_significant_growth_in_coming_decade.

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When President Barack Obama met PARO a few years ago on a tour of Japanese robotics innovations, he instinctually reached out and rubbed its head and back. It looks like a cute stuffed animal, but costs $6,000 and is classified by the US government as a class 2 medical device. Japan already leads the world in robotics, operating 310,000 of the 1.4 million industrial robots in existence across the world. It’s turning to eldercare robots in part because it has to and in part because it, uniquely, is in a great position to leverage its advanced industrial technology toward the long assembly line of the human life span. But can robots really take care of humans? Japan’s private and public sectors certainly think so.

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While Japan records the highest number of robot sales, China represents the most rapidly growing market, with sales increasing by 25 percent every year since 2005. There is quite a gap between the big five and the rest of the world. As both consumers and producers of robots, these countries outpace all others. By way of illustration, the number of industrial robots produced in South Korea, a country of 50 million people, is several times greater than the number produced in South America, Central America, Africa, and India combined, with populations totaling 2.8 billion. Russia is effectively a nonplayer in robotics despite its industrial base. It neither produces nor buys robots to any significant degree, instead maintaining extractive industries (natural gas, oil, iron, nickel) and industrial manufacturing plants that look and function the way they did in the 1970s and 1980s.

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

3D printing, additive manufacturing, air freight, algorithmic trading, anti-work, antiwork, back-to-the-land, banking crisis, basic income, battle of ideas, blockchain, Boris Johnson, Bretton Woods, business cycle, call centre, capital controls, capitalist realism, carbon footprint, carbon tax, Cass Sunstein, centre right, collective bargaining, crowdsourcing, cryptocurrency, David Graeber, decarbonisation, deep learning, deindustrialization, deskilling, Doha Development Round, Elon Musk, Erik Brynjolfsson, Evgeny Morozov, Ferguson, Missouri, financial independence, food miles, Francis Fukuyama: the end of history, full employment, future of work, gender pay gap, general purpose technology, housing crisis, housing justice, income inequality, industrial robot, informal economy, intermodal, Internet Archive, job automation, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, Kickstarter, Kiva Systems, late capitalism, liberation theology, Live Aid, low skilled workers, manufacturing employment, market design, Martin Wolf, mass immigration, mass incarceration, means of production, megaproject, minimum wage unemployment, Modern Monetary Theory, Mont Pelerin Society, Murray Bookchin, neoliberal agenda, New Urbanism, Occupy movement, oil shale / tar sands, oil shock, Overton Window, patent troll, pattern recognition, Paul Samuelson, Philip Mirowski, post scarcity, post-Fordism, post-work, postnationalism / post nation state, precariat, precautionary principle, price stability, profit motive, public intellectual, quantitative easing, reshoring, Richard Florida, rising living standards, road to serfdom, Robert Gordon, Ronald Reagan, Second Machine Age, secular stagnation, self-driving car, Slavoj Žižek, social web, stakhanovite, Steve Jobs, surplus humans, synthetic biology, tacit knowledge, technological determinism, the built environment, The Chicago School, The Future of Employment, the long tail, Tyler Cowen, Tyler Cowen: Great Stagnation, universal basic income, wages for housework, warehouse automation, We are all Keynesians now, We are the 99%, women in the workforce, working poor, working-age population

Technological and economic developments now enable countries to virtually leapfrog the industrialisation phase, which means that developing economies are now deindustrialising at much lower rates of per capita income and with much lower shares of manufacturing employment.106 China is a good example of this, with manufacturing employment in decline,107 labour struggles becoming more confident,108 real wages surging109 and demographic limits leading to a focus on ‘technological upgrading [and] productivity enhancements’ in order to maintain growth.110 The automation of factories is at the leading edge of this deindustrialisation trend, with China already the biggest purchaser of industrial robots, and expected to soon have more industrial robots in operation than either Europe or North America.111 The factory of the world is going robotic. Deindustrialisation can also be seen in ‘reshoring’, where manufacturing returns to developed economies in jobless, automated forms.112 These deindustrialisation trends are taking hold across the developing economies of Latin America, sub-Saharan Africa and most of Asia.113 Even in countries where manufacturing employment has increased in absolute terms, there have been significant decreases in the labour-intensity of the process.114 The result of all of this is not only an incomplete transition to a significant working class, but also the stymying of the expected employment path for the workforce.

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This novelty means that we should expect a delay in the response of productivity figures, as the technologies are adopted and then adapted into the way businesses run.42 Finally, and most importantly, our argument here relies largely on a normative claim rather than a descriptive one. Full automation is something that can and should be achieved, regardless of whether it is yet being carried out. For instance, out of the US companies that could benefit from incorporating industrial robots, less than 10 per cent have done so.43 This is but one area for full automation to take hold in, and this reiterates the importance of making full automation a political demand, rather than assuming it will come about from economic necessity. A variety of policies can help in this project: more state investment, higher minimum wages and research devoted to technologies that replace rather than augment workers.

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Erik Brynjolfsson, Andrew McAfee and Michael Spence, ‘New World Order’, Foreign Affairs, August 2014. 108.Manfred Elfstrom and Sarosh Kuruvilla, ‘The Changing Nature of Labor Unrest in China’, ILR Review 67: 2 (2014) 109.Real wages rose by 300 per cent between 2000 and 2010. ILO, Global Wage Report 2012/13: Wages and Equitable Growth (Geneva: International Labour Organization, 2013), pdf available at ilo.org, p. 20. 110.ILO, Global Employment Trends 2014, p. 29. 111.International Federation of Robotics, World Robotics: Industrial Robots 2014 (Frankfurt: International Federation of Robotics, 2014), pdf available at worldrobotics.org, p. 19; Lee Chyen Yee and Clare Jim, ‘Foxconn to Rely More on Robots; Could Use 1 Million in 3 Years’, Reuters, 1 August 2011; ‘Guangzhou Spurs Robot Use amid Rising Labor Costs’, China Daily, 16 April 2014, at chinadaily.com.cn; Angelo Young, ‘Nike Unloads Contract Factory Workers, Showing How Automation Is Costing Jobs of Vulnerable Emerging Market Laborers’, International Business Times, 20 May 2014. 112.Majority of Large Manufacturers Are Now Planning or Considering ‘Reshoring’ from China to the US, Boston Consulting Group, 24 September 2013, at bcg.com; Stephanie Clifford, ‘US Textile Plants Return, with Floors Largely Empty of People’, New York Times, 19 September 2013. 113.Dani Rodrik, Premature Deindustrialization, BREAD Working Paper No. 439, Bureau for Research and Economic Analysis of Development, 2015, at ipl.econ.duke.edu, p. 2. 114.Fiona Tregenna, Manufacturing Productivity, Deindustrialization, and Reindustrialization, World Institute for Development Economics Research, 2011, at econstor.eu, p. 11. 115.Out of a labour force of 481 million, approximately 1 million work in this sector.

Climbing Mount Improbable by Richard Dawkins, Lalla Ward

Boeing 747, Buckminster Fuller, computer age, Drosophila, Fellow of the Royal Society, industrial robot, invention of radio, John von Neumann, Menlo Park, phenotype, Robert X Cringely, stem cell, the long tail, trade route

The appropriate kind of output device for the TRIP is not a 3-D printer at all. It is an industrial robot. It has a pincer or some equivalent of a hand, capable of grasping objects. The ‘hand’ must be on the end of an arm-equivalent and it must have a universal joint or a set of joints capable of moving it in all three planes. It has the equivalent of sense organs, capable of guiding it towards the next object that must be picked up, and capable of steering that object towards its desired destination so that it can be fastened in position by an appropriate means. Industrial robots of this kind do exist in modern factories (Figure 9.1).

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Industrial robots of this kind do exist in modern factories (Figure 9.1). They do work, provided each one has a very particular task to perform at a particular point in an assembly line. But a normal industrial robot is still not adequate to run the TRIP program. It can put parts together—assemble them—if those parts are handed to it in a fixed orientation, or regimented past it on a production line. But the whole point of our exercise is to get away from things being handed in fixed orientation, ‘on a plate’. Our robot has somehow to find the raw materials for making the parts before it can begin to assemble them together. In order to do this it has to move around the world, actively seeking raw materials, mining them, gathering them up.

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In order to do this it has to move around the world, actively seeking raw materials, mining them, gathering them up. It has to have the means to travel—something like caterpillar tracks or legs. Figure 9.1 Industrial robot from Nissan car factory. Yokohama. There are robots that do have legs, or other means of moving around the world in a quasi-purposeful way. The one in Figure 9.2 happens to be rather insect-like, except that it has four legs instead of six. It is provided with sucker feet like a fly, because its parlour trick is climbing up vertical surfaces. A favourite game of its makers is teasing it by placing a hand in just the place where the robot wants to step.

Free Money for All: A Basic Income Guarantee Solution for the Twenty-First Century by Mark Walker

3D printing, 8-hour work day, additive manufacturing, Affordable Care Act / Obamacare, basic income, Baxter: Rethink Robotics, behavioural economics, Capital in the Twenty-First Century by Thomas Piketty, commoditize, confounding variable, driverless car, financial independence, full employment, guns versus butter model, happiness index / gross national happiness, industrial robot, intangible asset, invisible hand, Jeff Bezos, job automation, job satisfaction, John Markoff, Kevin Kelly, laissez-faire capitalism, late capitalism, longitudinal study, market clearing, means of production, military-industrial complex, new economy, obamacare, off grid, off-the-grid, plutocrats, precariat, printed gun, profit motive, Ray Kurzweil, rent control, RFID, Rodney Brooks, Rosa Parks, science of happiness, Silicon Valley, surplus humans, The Future of Employment, the market place, The Wealth of Nations by Adam Smith, too big to fail, transaction costs, universal basic income, warehouse robotics, working poor

They are by no means perfect but certainly much better at vacuuming than your average teenager. They also work cheaper and do not complain. Another example of robotic progress is Baxter from Rethink Robotics. Baxter is an industrial robot designed by Rodney Brooks, inventor of the Roomba robot. Let us consider the cost first. Unimate is usually credited with the installation of the first industrial robot in 1961.13 This robotic arm worked at a General Motors factory with hot die cast metal sorting and stacking. Unimate sold the robot at a loss: it cost $65 million to make and Unimate sold it for a paltry $18 million.

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Baxter costs more than 1,000 times less, retailing at $22,000. Even compared to many of its contemporary competitors, Baxter is a giant leap forward. Often the price of a robot is a fraction of the PEACE, ROBOTS, AND TECHNOLOGICAL UNEMPLOYMENT 99 total cost of its operation. For example, a typical industrial robot that costs $100,000 at present might use an additional $400,000 in labor fees to have programmers write and debug code to instruct the robot how to perform its task. Baxter, in contrast, can be trained by factory workers: it is simply a matter of guiding Baxter’s arm to show it what needs to be done.

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The reality is that we are almost at a tipping point where robots are cheaper even in an industry known for its low-cost labor.19 Indeed, what is disturbing is that even in China, with its notoriously low wages and harsh working conditions, there is a move to robotics. The chairman of Hon Hai (also known as Foxcon), manufacturers of Apple’s iPhone and other electronic devices, announced a few years back that the company’s goal is to have a million industrial robots in use by 2014.20 The plan has hit some snags but is still proceeding at an aggressive pace.21 Some analysts say the price of robots 100 FREE MONEY FOR ALL is still too high for it to make economic sense for Hon Hai, suggesting that the price per robot would have to fall to $25,000 from their current $50,000–$200,000 level.

The End of Indexing: Six Structural Mega-Trends That Threaten Passive Investing by Niels Jensen

Alan Greenspan, Basel III, Bear Stearns, declining real wages, deglobalization, disruptive innovation, diversification, Donald Trump, driverless car, eurozone crisis, falling living standards, fixed income, full employment, Greenspan put, income per capita, index fund, industrial robot, inflation targeting, job automation, John Nash: game theory, liquidity trap, low interest rates, moral hazard, offshore financial centre, oil shale / tar sands, old age dependency ratio, passive investing, Phillips curve, purchasing power parity, pushing on a string, quantitative easing, regulatory arbitrage, rising living standards, risk free rate, risk tolerance, Robert Solow, secular stagnation, South China Sea, total factor productivity, working-age population, zero-sum game

Germany, on the other hand, is in a much better place, despite the two countries sharing largely the same demographic profile. Angela Merkel’s decision to allow many migrants to settle in her country, combined with a rapidly rising penetration of industrial robots (see exhibit 10.2 again) and very strong public finances could quite possibly make the ageing of the German populace manageable. Moreover, Germany’s commitment to industrial robots will further enhance German industry’s already sublime level of competitiveness, making the German equity market one of my favourite candidates to outperform global averages in the years to come. I expect nothing extraordinary from US equity markets – at least for the next 10 years or so, when US demographics begin to improve again (much sooner than European demographics will).

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Over the decades, few jobs have been lost as a consequence of better and more sophisticated technology. What has instead happened is that the workforce has up-skilled. However, the fear factor is what drives behaviour, not facts, and many workers are fearful of losing out to robots. I have found virtually no correlation between the use of robots and employment in the manufacturing industry. Robots don’t cost jobs (at least not on a grand scale) – poor competitiveness does. Brexit will lead to improved competitiveness and hence more jobs, many Brexiters argue, but I would suggest you take a sneak preview of exhibit 10.2, which depicts the penetration of advanced robotics around the world.

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A shrinking workforce will force robots to be installed if we want to keep industry alive, partly because we won’t have enough people to fill the manufacturing floors, and partly because those who are left will be too expensive to do the job. The best line of defence against Chinese competition is therefore likely to be more automation. Exhibit 10.2: Number of multi-purpose industrial robots (all types) per 10,000 employees in the manufacturing industry, 2015 Source: International Federation of Robotics (2017). A likely side effect of increased automation is low (possibly negative) inflation. Modest inflation is a desirable outcome, but deflation certainly isn’t when we are about to drown in debt.

Seriously Curious: The Facts and Figures That Turn Our World Upside Down by Tom Standage

"World Economic Forum" Davos, agricultural Revolution, augmented reality, autonomous vehicles, Big Tech, blood diamond, business logic, corporate governance, CRISPR, deep learning, Deng Xiaoping, Donald Trump, Dr. Strangelove, driverless car, Elon Musk, failed state, financial independence, gender pay gap, gig economy, Gini coefficient, high net worth, high-speed rail, income inequality, index fund, industrial robot, Internet of things, invisible hand, it's over 9,000, job-hopping, Julian Assange, life extension, Lyft, M-Pesa, Mahatma Gandhi, manufacturing employment, mega-rich, megacity, Minecraft, mobile money, natural language processing, Nelson Mandela, plutocrats, post-truth, price mechanism, private spaceflight, prosperity theology / prosperity gospel / gospel of success, purchasing power parity, ransomware, reshoring, ride hailing / ride sharing, Ronald Coase, self-driving car, Silicon Valley, Snapchat, South China Sea, speech recognition, stem cell, supply-chain management, transaction costs, Uber and Lyft, uber lyft, undersea cable, US Airways Flight 1549, WikiLeaks, zoonotic diseases

If the pull of work is not strong enough to overcome the desire to game, the first response should be to ask whether more can be done to prepare young people for good jobs – and to make sure that there are some around when those young people enter the workforce. What do robots do all day? You have probably never heard of FANUC, the world’s largest maker of industrial robots. But the chances are that you own a product built by one of its 400,000 machines. Established in 1956, the Japanese company supplies robots that build cars for Ford and Tesla, and metal iPhone cases for Apple. The firm distinguishes itself from competitors by the colour of its robots’ whizzing mechanical arms, which are painted bright yellow.

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The firm distinguishes itself from competitors by the colour of its robots’ whizzing mechanical arms, which are painted bright yellow. Its factories, offices and employee uniforms all share the same hue. FANUC is at the forefront of a booming market for robots that shows little sign of slowing. According to the International Federation of Robotics, unit sales of industrial robots grew by 15% in 2015, while revenues increased 9% to $11bn. In 2016 turnover in North America rose by 14%, to $1.8bn. ABI Research, a consultancy, reckons that the industry’s sales will triple by 2025. The popular narrative about robots is that they are stealing human workers’ jobs. A paper published by the National Bureau of Economic Research broadly supports this belief, estimating that each additional robot in the American economy reduces employment by 5.6 workers.

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Barclays, a bank, thinks that between 2016 and 2020, sales of these machines will increase more than tenfold. Adopting robots has made it economical for some manufacturers in high-wage countries to “re-shore” production from poorer countries. In 2017 Adidas, a sportswear firm, began producing running shoes in a German factory staffed by robots and 160 new workers. The life robotic Global industrial robots Source: International Federation of Robotics FANUC is not taking its dominance for granted. The company is working on smarter, more customisable robots and is investing heavily in artificial intelligence. Its efforts to adapt in the rapidly evolving robotics industry can be seen even in the firm’s new approach to colours.

All Day Long: A Portrait of Britain at Work by Joanna Biggs

Anton Chekhov, bank run, banking crisis, Bullingdon Club, call centre, Chelsea Manning, credit crunch, David Graeber, Desert Island Discs, Downton Abbey, emotional labour, Erik Brynjolfsson, financial independence, future of work, G4S, glass ceiling, industrial robot, job automation, land reform, low skilled workers, mittelstand, Northern Rock, payday loans, Right to Buy, scientific management, Second Machine Age, Sheryl Sandberg, six sigma, Steve Jobs, trickle-down economics, unpaid internship, wages for housework, Wall-E

But when the Robots kill their creators, and have reaped the world’s corn and turned the world’s cotton into cloth, there’s no next generation to appreciate the corn mountains. Čapek’s Robots, who want only something to do, reveal that work for work’s sake is pointless. The early twentieth-century robot panic was followed thirty years later by the first industrial robots, modelled on arms. (It has been historically difficult to create walking robots, so they have tended to have either arms or legs, not both.) The first industrial robot, the Unimate, was developed by George Devol and Joseph Engelberger in 1959, and sold at a loss in 1961 to General Motors, where it stacked pieces of hot metal. It could only complete simple tasks because its memory was stored on a magnetic drum, which turned and instructed the arm in a sequence of 200 different steps.

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There have been advances in pointe-shoemaking since 1929: US-based Gaynor Minden produces shoes with an ‘elastomeric’ toe of urethane foam which is supposed to never soften and St Petersburg’s Grishko adds silver to their shoes for its antibacterial properties. Both companies emphasise that, despite innovation, they make their shoes by hand. Making pointe shoes isn’t yet something robots can do. Industrial robot arm, 2 years, Swindon Light comes through the glass panels in the roof of MINI Plant Swindon and bounces off the silvery bonnets the robots are making: we can tell it’s morning even if the robots can’t. They work twenty-two-hour shifts, with a two-hour pause in the early morning for maintenance, penned inside a high grey fence in groups called cells.

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Advances were made by Hitachi (the first robot that could undo bolts in 1973) and Kawasaki (the first arc-welding robot in 1974) in Japan; the German firm KUKA (the first robot with six electromagnetically driven axes in 1973); Olivetti in Italy (the first robot with two hands in 1975) and ABB in Sweden (a robot that could pick food from a conveyor belt faster than a human hand in 1998). In 1973, 3,000 industrial robots were at work; by 1983, 66,000 welded, picked and stacked in factories across the globe. Robot-length days mean that the machines last for ten human years of continuous work. The newest cells at Swindon, which make doors, were installed in 2014: they can be adapted to make any of the doors for the different models, they laser-weld, they change their own welding tips, and they insert the finished doors in pallets.

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

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

The only obstacles to scale are consumer interest and curiosity. The types of rapid adoption curves seen in the digital sector also characterize physical goods and their manufacturing process. A new generation of industrial robots with enhanced perception, dexterity, and intelligence is being developed thanks to advances in machine vision and communication, sensors, and artificial intelligence. Sales of industrial robots grew by 170 percent in just two years between 2009 and 2011, and the industry’s annual revenues are expected to exceed $40 billion by 2020.38 The pace of this change will continue to accelerate.

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Seth Fiegerman, “Apple App Store tops 75 billion downloads,” Mashable, June 2, 2014, http://mashable.com/2014/06/02/apple-app-store-stats-2014. 38. Manyika et al., Disruptive technologies,; Nirmalya Chatterjee, “Global industrial robotics market (products, functions, applications and geography)—global analysis, industry growth, trends, size, share, opportunities and forecast—2013–2020,” Allied Market Research, May 2014, www.alliedmarketresearch.com/industrial-robotics-market. 39. “Cisco Visual Networking Index: Forecast and methodology, 2013–2018,” Cisco Systems, June 10, 2014. 40. Matthieu Pélissié du Rausas, James Manyika, Eric Hazan, Jacques Bughin, Michael Chui, and Rémi Said, Internet matters: The Net’s sweeping impact on growth, jobs, and prosperity, McKinsey Global Institute, May 2011. 41.

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More than five hundred years passed between Gutenberg’s printing press and the first computer printer. It then took only another thirty years for the 3-D printer to be invented. Two hundred years separated the spinning jenny, the yarn-producing machine invented in 1764, from GM’s Unimate, the world’s first industrial robot.13 It took only a quarter of that time for Shaft, the world’s most advanced humanoid robot, to be invented. As W. Brian Arthur, a former Stanford economist, who pioneered the study of positive feedback and wrote The Nature of Technology, noted, “With the coming of the Industrial Revolution—roughly from the 1760s, when Watt’s steam engine appeared, through around 1850 and beyond—the economy developed a muscular system in the form of machine power.

The Future of Technology by Tom Standage

air freight, Alan Greenspan, barriers to entry, business process, business process outsourcing, call centre, Clayton Christensen, computer vision, connected car, corporate governance, creative destruction, disintermediation, disruptive innovation, distributed generation, double helix, experimental economics, financial engineering, Ford Model T, full employment, hydrogen economy, hype cycle, industrial robot, informal economy, information asymmetry, information security, interchangeable parts, job satisfaction, labour market flexibility, Larry Ellison, Marc Andreessen, Marc Benioff, market design, Menlo Park, millennium bug, moral hazard, natural language processing, Network effects, new economy, Nicholas Carr, optical character recognition, PalmPilot, railway mania, rent-seeking, RFID, Salesforce, seminal paper, Silicon Valley, Silicon Valley ideology, Silicon Valley startup, six sigma, Skype, smart grid, software as a service, spectrum auction, speech recognition, stem cell, Steve Ballmer, Steve Jurvetson, technological determinism, technology bubble, telemarketer, transcontinental railway, vertical integration, Y2K

W Hand-built by robots Although the dream of the home robot has not died, robots have had their greatest impact in factories. Industrial robots go back over 40 years, when they first began to be used by carmakers. Unimate, the first industrial robot, went to work for General Motors in 1961. Even at a time 332 ROBOTS AND ARTIFICIAL INTELLIGENCE when computing power was costly, robots made excellent workers and proved that machines controlled by computers could perform some tasks better than humans. In addition, robots can work around the clock and never go on strike. There are now about 800,000 industrial robots around the world, and orders for new robots in the first half of 2003 were up a record 26% from the same period in 2002, according to the unece.

…

There are six-legged timber cutters, tree-climbing fruit-pickers, robots that milk cows, and others that wash windows, trucks and aircraft. Industrial robotics is a $5.6 billion industry, growing by around 7% a year. But the unece report predicts that the biggest growth over the next few years will be in domestic rather than industrial robots. Sales of such devices, it predicts – from toys to lawnmowers to, yes, vacuum cleaners – will grow ten-fold between 2002 and 2006, overtaking the market for industrial robots. The broader application of robotics is becoming possible thanks to the tumbling cost of computing power, says Takeo Kanade of Carnegie Mellon University’s Robotics Institute, who has built robots on both sides of the Pacific.

Stakeholder Capitalism: A Global Economy That Works for Progress, People and Planet by Klaus Schwab, Peter Vanham

"Friedman doctrine" OR "shareholder theory", "World Economic Forum" Davos, 3D printing, additive manufacturing, agricultural Revolution, air traffic controllers' union, Anthropocene, Apple II, Asian financial crisis, Asperger Syndrome, basic income, Berlin Wall, Big Tech, biodiversity loss, bitcoin, Black Lives Matter, blockchain, blue-collar work, Branko Milanovic, Bretton Woods, British Empire, business process, capital controls, Capital in the Twenty-First Century by Thomas Piketty, car-free, carbon footprint, carbon tax, centre right, clean tech, clean water, cloud computing, collateralized debt obligation, collective bargaining, colonial rule, company town, contact tracing, contact tracing app, Cornelius Vanderbilt, coronavirus, corporate governance, corporate social responsibility, COVID-19, creative destruction, Credit Default Swap, credit default swaps / collateralized debt obligations, cryptocurrency, cuban missile crisis, currency peg, cyber-physical system, decarbonisation, demographic dividend, Deng Xiaoping, Diane Coyle, digital divide, don't be evil, European colonialism, Fall of the Berlin Wall, family office, financial innovation, Francis Fukuyama: the end of history, future of work, gender pay gap, general purpose technology, George Floyd, gig economy, Gini coefficient, global supply chain, global value chain, global village, Google bus, green new deal, Greta Thunberg, high net worth, hiring and firing, housing crisis, income inequality, income per capita, independent contractor, industrial robot, intangible asset, Intergovernmental Panel on Climate Change (IPCC), Internet of things, invisible hand, James Watt: steam engine, Jeff Bezos, job automation, joint-stock company, Joseph Schumpeter, Kenneth Rogoff, Khan Academy, Kickstarter, labor-force participation, lockdown, low interest rates, low skilled workers, Lyft, manufacturing employment, Marc Benioff, Mark Zuckerberg, market fundamentalism, Marshall McLuhan, Martin Wolf, means of production, megacity, microplastics / micro fibres, Mikhail Gorbachev, mini-job, mittelstand, move fast and break things, neoliberal agenda, Network effects, new economy, open economy, Peace of Westphalia, Peter Thiel, precariat, Productivity paradox, profit maximization, purchasing power parity, race to the bottom, reserve currency, reshoring, ride hailing / ride sharing, Ronald Reagan, Salesforce, San Francisco homelessness, School Strike for Climate, self-driving car, seminal paper, shareholder value, Shenzhen special economic zone , Shenzhen was a fishing village, Silicon Valley, Simon Kuznets, social distancing, Social Responsibility of Business Is to Increase Its Profits, special economic zone, Steve Jobs, Steve Wozniak, synthetic biology, TaskRabbit, The Chicago School, The Future of Employment, The inhabitant of London could order by telephone, sipping his morning tea in bed, the various products of the whole earth, the scientific method, TikTok, Tim Cook: Apple, trade route, transfer pricing, Uber and Lyft, uber lyft, union organizing, universal basic income, War on Poverty, We are the 99%, women in the workforce, working poor, working-age population, Yom Kippur War, young professional, zero-sum game

It was Dansk Metal, the union representing blue-collar workers in the Danish metal manufacturing and processing industry. It was clear that the union was proud of this achievement: “An increasing number of employees in the industry work side by side with robots,” the press release read. “Dansk Metal has a target of rounding 10,000 industrial robots in Denmark by 2020.” I was intrigued by this stance. From visiting other parts of the world, and reading about other times in history, I knew of many more instances where workers opposed new technologies, especially when they threatened to replace their jobs. The most famous case may have been that of the Luddites in England, a group of textile workers in 19th century England who destroyed the new machinery that was disrupting their industry.

…

Møller–Mærsk (Denmark), 167–168, 199–201, 202–207, 208, 213, 215 Appellate Judges (World Trade Organization), 197 Apple Computer, 126, 137 Apple (US), 59, 127, 128, 137, 209, 211 Arab Spring (2011), 40 Ardern, Jacinda, 219, 220–223, 236 Argentina “reefer ships” (1870s) bringing wealth to, 104, 110 “21st century socialism” of, 225 Artificial intelligence (AI), 143–144, 145, 161 ASEAN nations Chinese economy and emerging markets of, 63–66, 70–72 environmental degradation and economic growth of, 72 IMF forecast on 2020 economic growth of, 71 as an international community stakeholder, 178 national income inequality increasing in, 40 tech unicorns in the, 66, 67fig “The Asian Century,” 70–71fig Asian countries capitalism vs. communism ideological battle in, 7 post-war economy of, 6 severe financial crisis (1997) in, 16, 98, 109 WHO on unsafe air (2019) in, 72 Asian financial crisis (1997), 16, 98, 109 Asian Tigers GDP growth contributions (1980s) by, 13 globalization and economic growth of, 98 influence on China's economy by, 57 shift to producing goods for export, 58 See also Hong Kong; Singapore; South Korea; Taiwan AT&T monopoly, 127, 135 Audi (German manufacturer), 9 Aufstehen movement (Germany), 88 Australia efforts to reduce emissions in, 166–167 mining exports to China, 64 Austrian populist parties (2000, 2017–2019), 84fig Auto industry city of Detroit, 110–111 Ford Motor Company, 33 lack of regulatory scrutiny of the, 136 Mercedes, 9 Automation Dansk Metal's industrial robots, 115, 117 labor market and challenge of, 115–126 Axis nations (World War II), 5 B Baby boom (1950s and 1960s), 8, 9, 105, 135, 154, 160 Bah, Aziz, 238 Bai Chong-En, 225–226 Baidu (US), 143 Bain, 66 Baker, George Pierce, 11 Baldwin, Richard, 64, 113 Bandung entrepreneurs story (2012), 93–94 Bangladesh unsafe air (2019), 72 Bank of America, 214, 215, 249 Bank of England, 162 Bay of Pigs, 76 Belgium declining income inequality in, 41 digital economy embraced by, 113–114 economic loss due to closed car plants in, 111 First Industrial Revolution spreading to, 131 stakeholder approach solving disagreements in, 195 stakeholder concept adopted in, 174 Bell Company.

…

See World Economic Forum Annual Meetings Davos (Switzerland), 11 Deaton, Angus, 42 Debt China's increased total debt–to–GDP ratio, 62 high-quality vs. low-quality, 29 increasing rates of, 28–31 low inflation rates and impact on, 33 Decision making Davos Manifesto (1973) on stakeholder-centered, 13–14, 88, 213 history of stakeholder concept on, 174–175 need for checks and balances in, 185, 193–198 reaching environment, social, and governance (ESG) objectives, 185, 193 separating consultative process from, 198 stakeholder model on, 13, 173, 175–198 subsidiarity principle of, 181–183 “Decoupling” of wages, 34 Deloitte (US), 215, 250 Democracy Economist Intelligence Unit's Singapore ranking (2019), 233 global drop in voter turnout for elections, 188 respecting local customs and traditions, 195–196 stakeholder model applied to, 185, 193–198 See also Political divisions Demographic changes, 160–161 Deng Xiaoping, 56, 57 Denmark “Active Labour Market Policies” of, 120–121 A.P. Møller–Maersk of, 167–168, 199–201, 202–207, 208, 213, 215 comparison of labor approach in US vs., 117–120, 123 constructive relationship between workers and companies in, 117–120 Dansk Metal's industrial robots, 115, 117 digital economy embraced by, 113–114 female-led government leadership during COVID-19 pandemic in, 224 “flexicurity” model of, 119 high union membership in, 240 income equality in, 119, 186 MAN Energy Solutions, 117–118 stakeholder concept adopted in, 174 Destiny Disrupted (Ansary), 195–196 Detroit (Michigan), 110–111, 159 Deutsche Bahn (DB) [Germany], 163 Deutsche Demokratische Republik (DDR).

Stakeholder Capitalism: A Global Economy That Works for Progress, People and Planet by Klaus Schwab

"Friedman doctrine" OR "shareholder theory", "World Economic Forum" Davos, 3D printing, additive manufacturing, agricultural Revolution, air traffic controllers' union, Anthropocene, Apple II, Asian financial crisis, Asperger Syndrome, basic income, Berlin Wall, Big Tech, biodiversity loss, bitcoin, Black Lives Matter, blockchain, blue-collar work, Branko Milanovic, Bretton Woods, British Empire, business process, capital controls, Capital in the Twenty-First Century by Thomas Piketty, car-free, carbon footprint, carbon tax, centre right, clean tech, clean water, cloud computing, collateralized debt obligation, collective bargaining, colonial rule, company town, contact tracing, contact tracing app, Cornelius Vanderbilt, coronavirus, corporate governance, corporate social responsibility, COVID-19, creative destruction, Credit Default Swap, credit default swaps / collateralized debt obligations, cryptocurrency, cuban missile crisis, currency peg, cyber-physical system, decarbonisation, demographic dividend, Deng Xiaoping, Diane Coyle, digital divide, don't be evil, European colonialism, Fall of the Berlin Wall, family office, financial innovation, Francis Fukuyama: the end of history, future of work, gender pay gap, general purpose technology, George Floyd, gig economy, Gini coefficient, global supply chain, global value chain, global village, Google bus, green new deal, Greta Thunberg, high net worth, hiring and firing, housing crisis, income inequality, income per capita, independent contractor, industrial robot, intangible asset, Intergovernmental Panel on Climate Change (IPCC), Internet of things, invisible hand, James Watt: steam engine, Jeff Bezos, job automation, joint-stock company, Joseph Schumpeter, Kenneth Rogoff, Khan Academy, Kickstarter, labor-force participation, lockdown, low interest rates, low skilled workers, Lyft, manufacturing employment, Marc Benioff, Mark Zuckerberg, market fundamentalism, Marshall McLuhan, Martin Wolf, means of production, megacity, microplastics / micro fibres, Mikhail Gorbachev, mini-job, mittelstand, move fast and break things, neoliberal agenda, Network effects, new economy, open economy, Peace of Westphalia, Peter Thiel, precariat, Productivity paradox, profit maximization, purchasing power parity, race to the bottom, reserve currency, reshoring, ride hailing / ride sharing, Ronald Reagan, Salesforce, San Francisco homelessness, School Strike for Climate, self-driving car, seminal paper, shareholder value, Shenzhen special economic zone , Shenzhen was a fishing village, Silicon Valley, Simon Kuznets, social distancing, Social Responsibility of Business Is to Increase Its Profits, special economic zone, Steve Jobs, Steve Wozniak, synthetic biology, TaskRabbit, The Chicago School, The Future of Employment, The inhabitant of London could order by telephone, sipping his morning tea in bed, the various products of the whole earth, the scientific method, TikTok, Tim Cook: Apple, trade route, transfer pricing, Uber and Lyft, uber lyft, union organizing, universal basic income, War on Poverty, We are the 99%, women in the workforce, working poor, working-age population, Yom Kippur War, young professional, zero-sum game

It was Dansk Metal, the union representing blue-collar workers in the Danish metal manufacturing and processing industry. It was clear that the union was proud of this achievement: “An increasing number of employees in the industry work side by side with robots,” the press release read. “Dansk Metal has a target of rounding 10,000 industrial robots in Denmark by 2020.” I was intrigued by this stance. From visiting other parts of the world, and reading about other times in history, I knew of many more instances where workers opposed new technologies, especially when they threatened to replace their jobs. The most famous case may have been that of the Luddites in England, a group of textile workers in 19th century England who destroyed the new machinery that was disrupting their industry.

…

Møller–Mærsk (Denmark), 167–168, 199–201, 202–207, 208, 213, 215 Appellate Judges (World Trade Organization), 197 Apple Computer, 126, 137 Apple (US), 59, 127, 128, 137, 209, 211 Arab Spring (2011), 40 Ardern, Jacinda, 219, 220–223, 236 Argentina “reefer ships” (1870s) bringing wealth to, 104, 110 “21st century socialism” of, 225 Artificial intelligence (AI), 143–144, 145, 161 ASEAN nations Chinese economy and emerging markets of, 63–66, 70–72 environmental degradation and economic growth of, 72 IMF forecast on 2020 economic growth of, 71 as an international community stakeholder, 178 national income inequality increasing in, 40 tech unicorns in the, 66, 67fig “The Asian Century,” 70–71fig Asian countries capitalism vs. communism ideological battle in, 7 post-war economy of, 6 severe financial crisis (1997) in, 16, 98, 109 WHO on unsafe air (2019) in, 72 Asian financial crisis (1997), 16, 98, 109 Asian Tigers GDP growth contributions (1980s) by, 13 globalization and economic growth of, 98 influence on China's economy by, 57 shift to producing goods for export, 58 See also Hong Kong; Singapore; South Korea; Taiwan AT&T monopoly, 127, 135 Audi (German manufacturer), 9 Aufstehen movement (Germany), 88 Australia efforts to reduce emissions in, 166–167 mining exports to China, 64 Austrian populist parties (2000, 2017–2019), 84fig Auto industry city of Detroit, 110–111 Ford Motor Company, 33 lack of regulatory scrutiny of the, 136 Mercedes, 9 Automation Dansk Metal's industrial robots, 115, 117 labor market and challenge of, 115–126 Axis nations (World War II), 5 B Baby boom (1950s and 1960s), 8, 9, 105, 135, 154, 160 Bah, Aziz, 238 Bai Chong-En, 225–226 Baidu (US), 143 Bain, 66 Baker, George Pierce, 11 Baldwin, Richard, 64, 113 Bandung entrepreneurs story (2012), 93–94 Bangladesh unsafe air (2019), 72 Bank of America, 214, 215, 249 Bank of England, 162 Bay of Pigs, 76 Belgium declining income inequality in, 41 digital economy embraced by, 113–114 economic loss due to closed car plants in, 111 First Industrial Revolution spreading to, 131 stakeholder approach solving disagreements in, 195 stakeholder concept adopted in, 174 Bell Company.

…

See World Economic Forum Annual Meetings Davos (Switzerland), 11 Deaton, Angus, 42 Debt China's increased total debt–to–GDP ratio, 62 high-quality vs. low-quality, 29 increasing rates of, 28–31 low inflation rates and impact on, 33 Decision making Davos Manifesto (1973) on stakeholder-centered, 13–14, 88, 213 history of stakeholder concept on, 174–175 need for checks and balances in, 185, 193–198 reaching environment, social, and governance (ESG) objectives, 185, 193 separating consultative process from, 198 stakeholder model on, 13, 173, 175–198 subsidiarity principle of, 181–183 “Decoupling” of wages, 34 Deloitte (US), 215, 250 Democracy Economist Intelligence Unit's Singapore ranking (2019), 233 global drop in voter turnout for elections, 188 respecting local customs and traditions, 195–196 stakeholder model applied to, 185, 193–198 See also Political divisions Demographic changes, 160–161 Deng Xiaoping, 56, 57 Denmark “Active Labour Market Policies” of, 120–121 A.P. Møller–Maersk of, 167–168, 199–201, 202–207, 208, 213, 215 comparison of labor approach in US vs., 117–120, 123 constructive relationship between workers and companies in, 117–120 Dansk Metal's industrial robots, 115, 117 digital economy embraced by, 113–114 female-led government leadership during COVID-19 pandemic in, 224 “flexicurity” model of, 119 high union membership in, 240 income equality in, 119, 186 MAN Energy Solutions, 117–118 stakeholder concept adopted in, 174 Destiny Disrupted (Ansary), 195–196 Detroit (Michigan), 110–111, 159 Deutsche Bahn (DB) [Germany], 163 Deutsche Demokratische Republik (DDR).

Hit Refresh: The Quest to Rediscover Microsoft's Soul and Imagine a Better Future for Everyone by Satya Nadella, Greg Shaw, Jill Tracie Nichols

3D printing, AlphaGo, Amazon Web Services, anti-globalists, artificial general intelligence, augmented reality, autonomous vehicles, basic income, Bretton Woods, business process, cashless society, charter city, cloud computing, complexity theory, computer age, computer vision, corporate social responsibility, crowdsourcing, data science, DeepMind, Deng Xiaoping, Donald Trump, Douglas Engelbart, driverless car, Edward Snowden, Elon Musk, en.wikipedia.org, equal pay for equal work, everywhere but in the productivity statistics, fault tolerance, fulfillment center, Gini coefficient, global supply chain, Google Glasses, Grace Hopper, growth hacking, hype cycle, industrial robot, Internet of things, Jeff Bezos, job automation, John Markoff, John von Neumann, knowledge worker, late capitalism, Mars Rover, Minecraft, Mother of all demos, Neal Stephenson, NP-complete, Oculus Rift, pattern recognition, place-making, Richard Feynman, Robert Gordon, Robert Solow, Ronald Reagan, Salesforce, Second Machine Age, self-driving car, side project, Silicon Valley, Skype, Snapchat, Snow Crash, special economic zone, speech recognition, Stephen Hawking, Steve Ballmer, Steve Jobs, subscription business, TED Talk, telepresence, telerobotics, The Rise and Fall of American Growth, The Soul of a New Machine, Tim Cook: Apple, trade liberalization, two-sided market, universal basic income, Wall-E, Watson beat the top human players on Jeopardy!, young professional, zero-sum game

To help us investigate this question, MIT economist Daron Acemoglu visited our campus to report on his research into the effects of technology automation on labor. He found that new intelligent machines, particularly industrial robots, could have very consequential effects on the labor market. His estimates suggest that, on average, each additional industrial robot reduces employment by about three workers. This suggests that, without any countervailing changes, the spread of industrial robots could have very adverse consequences for jobs and wages. Nevertheless, Acemoglu argues that other powerful changes triggered by this onslaught could at least partly reverse these consequences.

The Rare Metals War by Guillaume Pitron

Albert Einstein, Berlin Wall, carbon footprint, circular economy, clean tech, cloud computing, collapse of Lehman Brothers, commodity super cycle, connected car, David Attenborough, decarbonisation, degrowth, deindustrialization, dematerialisation, Deng Xiaoping, Donald Trump, driverless car, dual-use technology, Elon Musk, energy transition, Fairphone, full employment, green new deal, green transition, industrial robot, Internet of things, invisible hand, Jeff Bezos, Kickstarter, knowledge economy, Lyft, mittelstand, offshore financial centre, oil shale / tar sands, planetary scale, planned obsolescence, Silicon Valley, smart cities, smart grid, smart meter, South China Sea, spinning jenny, Tesla Model S, Yom Kippur War

(Machine tools are used for factory work automation, from basic milling machines to ultra-connected machining centres.) The Mittelstand acted pre-emptively by gradually replacing humans with robots, allowing it to remain competitive to the extent that German industry still represents 30 per cent of the country’s GDP.27 Except that industrial robots require terrific amounts of tungsten. China has always produced this rare metal in abundance, but there are other tungsten mines around the world, ensuring supply diversity for manufacturers. During the 1990s, the Chinese machined their own cutting tools — ‘Some hammers, a few drills … really crumby tools,’ said an Australian consultant.28 But they wanted to move up the value chain in this area as well.

…

See ‘Central Enterprises Launch a New Wave of Investments in Inner Mongolia, Signing Contracts Worth RMB 402 Million Yuan at an Informal Meeting’, PR Newswire, 1 March 2017. The city of Baotou is still pursuing its ambitions by developing an industrial area of 470 square kilometres dedicated to rare earths. See ‘Huge Rare Earth Industrial Park Coming to Inner Mongolia’, China Daily, 29 August 2017. Interview with Dudley Kingsnorth, 2016. Industrial robots are in fact the cornerstone of tomorrow’s smart and ultra-connected ‘4.0 factories’, where Germany has the lead. In 2015, the German machine tool industry generated over €15 billion, exported three-quarters of its production and had a headcount of nearly 70,000 employees. It is a pillar of the national economy.

…

For a more detailed explanation, see the French Geological Survey’s public report: ‘Panorama du marché du tungstène’ [‘View of the Tungsten Market’], BRGM, July 2012. Interview with Chris Ecclestone, 2016. The Mittelstand may have won the battle, but they did not win the war. China has a keen interest in some of Germany’s star industrial robots, such as KUKA. See ‘Allemagne: le “Mittelstand” face à l’offensive chinoise’ [‘Germany: the Mittelstand faces the Chinese offensive’], Le Monde, 4 June 2016. Graphene’s applications are astounding: bendy mobile phones, see-through laptops, ultra-powerful nanoprocessors, or nanochips that can be inserted into the human body to detect cancers, and so on.

The AI Economy: Work, Wealth and Welfare in the Robot Age by Roger Bootle

"World Economic Forum" Davos, 3D printing, agricultural Revolution, AI winter, Albert Einstein, AlphaGo, Alvin Toffler, anti-work, antiwork, autonomous vehicles, basic income, Ben Bernanke: helicopter money, Bernie Sanders, Bletchley Park, blockchain, call centre, Cambridge Analytica, Capital in the Twenty-First Century by Thomas Piketty, Carl Icahn, Chris Urmson, computer age, Computing Machinery and Intelligence, conceptual framework, corporate governance, correlation does not imply causation, creative destruction, David Ricardo: comparative advantage, deep learning, DeepMind, deindustrialization, Demis Hassabis, deskilling, Dr. Strangelove, driverless car, Elon Musk, en.wikipedia.org, Erik Brynjolfsson, everywhere but in the productivity statistics, facts on the ground, fake news, financial intermediation, full employment, future of work, Future Shock, general purpose technology, Great Leap Forward, Hans Moravec, income inequality, income per capita, industrial robot, Internet of things, invention of the wheel, Isaac Newton, James Watt: steam engine, Jeff Bezos, Jeremy Corbyn, job automation, job satisfaction, John Markoff, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, John von Neumann, Joseph Schumpeter, Kevin Kelly, license plate recognition, low interest rates, machine translation, Marc Andreessen, Mark Zuckerberg, market bubble, mega-rich, natural language processing, Network effects, new economy, Nicholas Carr, Ocado, Paul Samuelson, Peter Thiel, Phillips curve, positional goods, quantitative easing, RAND corporation, Ray Kurzweil, Richard Florida, ride hailing / ride sharing, rising living standards, road to serfdom, Robert Gordon, Robert Shiller, Robert Solow, Rutger Bregman, Second Machine Age, secular stagnation, self-driving car, seminal paper, Silicon Valley, Silicon Valley billionaire, Simon Kuznets, Skype, social intelligence, spinning jenny, Stanislav Petrov, Stephen Hawking, Steven Pinker, synthetic biology, technological singularity, The Future of Employment, The Wealth of Nations by Adam Smith, Thomas Malthus, trade route, universal basic income, US Airways Flight 1549, Vernor Vinge, warehouse automation, warehouse robotics, Watson beat the top human players on Jeopardy!, We wanted flying cars, instead we got 140 characters, wealth creators, winner-take-all economy, world market for maybe five computers, Y2K, Yogi Berra

A sequel, Blade Runner 2049, appeared in 2017, again depicting a similar dystopian future. Robots disappoint Meanwhile, in the real world, the performance of robots has disappointed early hopes. You could be forgiven for thinking that they appeared on the scene only recently. In fact, General Motors introduced the first industrial robot, called Unimate, in 1961. Even now, about a half of the robots in industrial use are employed in automotive manufacturing, where the closely defined tasks and rigid environment perfectly match what robots are best at.27 Interestingly, while automobile plants routinely employ robots to install windscreens on vehicles, if a car owner suffers a damaged windscreen and goes to a car repair shop to have it fixed they will find that this work is done by a human technician.

…

(Tying a shoelace is another example of something that is still beyond a robot’s capacity.) Consequently, the much-vaunted employment of robots as independent domestic helpers, as distinct from tools to assist human helpers, is a very long way off, if, indeed, it is ever achieved. Researchers in Singapore have been trying to teach an industrial robot to assemble an IKEA flatpack chair. The good news is that they have succeeded. The bad news is that it took two of them, preprogramed by humans, more than 20 minutes. It is alleged that a human could accomplish this task in a fraction of the time – although this particular human might well take much longer, or would give up, in frustration, before the task was finished.28 Google’s research and development company/group, now known as X, recently ran a project to identify images of cats on YouTube.

…

But Baxters are, in fact, not very capable and are not in much demand. They may be cheap to run but they cost $22,000 and upward to buy. Sales of Baxters have not picked up, and in December 2013 Baxter’s manufacturer, a firm called Rethink, laid off a quarter of its staff.39 According to Kevin Kelly, it costs $100,000 or more to buy an industrial robot but you may need to spend four times that amount over a lifespan to program, train, and maintain it, making a total bill over the robot’s “lifetime” of half a million dollars or more.40 So, employing a robot will involve a fixed investment. And this investment will be subject to all the usual factors that govern whether an investment is worthwhile: the cost of the equipment and any maintenance costs, the rate of return, the cost of finance, and the risk, including the risk of obsolescence.

Emotional design: why we love (or hate) everyday things by Donald A. Norman

A Pattern Language, crew resource management, Dean Kamen, industrial robot, job automation, language acquisition, Neal Stephenson, Rodney Brooks, Vernor Vinge, Yogi Berra

Even simple machines such as elevators and garage doors have sensors that stop them from closing on people. Today's robots try to avoid bumping into people or objects. Lawn mower and vacuum cleaner TLFeBOOK 198 Emotional Design robots have sensing mechanisms that cause them to stop or back away whenever they bump into anything or come too close to an edge, such as a stairway. Industrial robots are often fenced off, so that people can't get near them when they are operating. Some have people detectors, so they stop when they detect someone nearby. Home robots have many mechanisms to minimize the chance of damage; but at the moment, most of them are so underpowered that they couldn't hurt even if they tried to.

…

Note that DWIM (Do What I Mean) is a very old concept: Warren Teitelman introduced it into the command interpretation system of the LISP computer programming system in 1972. When it works, it is very, very nice. 202 "Asimov's main failure" A good review of the work on emergent systems, that is, against central control, is in Johnson's book Emergence (Johnson, 2001). 203 "There already are some safety regulations that apply to robots" {Industrial Robots and Robot System Safety. Occupational Safety and Health Administration, US Department of Labor, OSHA Technical Manual (TED 1-0.15A), 1999) Epilogue: We Are All Designers 215 "You may recall Victor Papanek's short book" (Papanek & Hennessey, 1977) 220 "Stuart Brand ... has shown" (Brand, 1994) 223 "John Seymour's wonderful description" (Seymour, 2001) 224 "Steve Harrison and Paul Dourish" (Harrison & Dourish, 1996) 226 "My own web site."

…

Washington, DC: The National Academies Press. Hinton, L., Nichols, J., & Ohala, J. J. (1994). Sound symbolism. Cambridge, UK: Cambridge University Press. Hughes-Morgan, M. (2002, February 25). Net effect of computer rage. This is London, http://www.thisislondon.com/dynamic/news/story.html?in_review_ id=506466&in_review_text_id=469291. Industrial Robots and Robot System Safety. Occupational Safety and Health Administration, US Department of Labor, OSHA Technical Manual (TED 1—0.15A). (1999). http://www.osha.gov/SLTC/machineguarding/publications.html. Section V entitled "Control and Safeguarding Personnel" outlines specific means for safeguarding robot systems.

In Our Own Image: Savior or Destroyer? The History and Future of Artificial Intelligence by George Zarkadakis

3D printing, Ada Lovelace, agricultural Revolution, Airbnb, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, animal electricity, anthropic principle, Asperger Syndrome, autonomous vehicles, barriers to entry, battle of ideas, Berlin Wall, bioinformatics, Bletchley Park, British Empire, business process, carbon-based life, cellular automata, Charles Babbage, Claude Shannon: information theory, combinatorial explosion, complexity theory, Computing Machinery and Intelligence, continuous integration, Conway's Game of Life, cosmological principle, dark matter, data science, deep learning, DeepMind, dematerialisation, double helix, Douglas Hofstadter, driverless car, Edward Snowden, epigenetics, Flash crash, Google Glasses, Gödel, Escher, Bach, Hans Moravec, income inequality, index card, industrial robot, intentional community, Internet of things, invention of agriculture, invention of the steam engine, invisible hand, Isaac Newton, Jacquard loom, Jacques de Vaucanson, James Watt: steam engine, job automation, John von Neumann, Joseph-Marie Jacquard, Kickstarter, liberal capitalism, lifelogging, machine translation, millennium bug, mirror neurons, Moravec's paradox, natural language processing, Nick Bostrom, Norbert Wiener, off grid, On the Economy of Machinery and Manufactures, packet switching, pattern recognition, Paul Erdős, Plato's cave, post-industrial society, power law, precautionary principle, prediction markets, Ray Kurzweil, Recombinant DNA, Rodney Brooks, Second Machine Age, self-driving car, seminal paper, Silicon Valley, social intelligence, speech recognition, stem cell, Stephen Hawking, Steven Pinker, Strategic Defense Initiative, strong AI, Stuart Kauffman, synthetic biology, systems thinking, technological singularity, The Coming Technological Singularity, The Future of Employment, the scientific method, theory of mind, Turing complete, Turing machine, Turing test, Tyler Cowen, Tyler Cowen: Great Stagnation, Vernor Vinge, Von Neumann architecture, Watson beat the top human players on Jeopardy!, Y2K

Even in China, where labour costs are rising and losing their global competitiveness, factory bosses today are beginning to commission armies of industrial robots to take over. Foxconn, a manufacturer of electronics and gaming consoles, made the news in 2012 by announcing it will replace a million workers with a million robots (aptly named ‘Foxbots’). According to the Frankfurt-based International Federation of Robotics, China will become the biggest consumer of industrial robots by 2014. Chinese factories will thus continue to increase their productivity and the quality of their products at a lower cost. It makes perfect sense if you are the CEO or the owner of the factory, despite the fact that your economic astuteness will put a good many people out of work.

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Nevertheless, with his last book Wittgenstein takes an empirical position: meaning is embedded in the use of language, it does not – and cannot – exist outside a social context. Meaning happens only when we communicate with another person who understands our language. Timeline: A brief history of Artificial Intelligence 1According to: http://spectrum.ieee.org/automaton/robotics/industrial-robots/041410-world-robot-population 2According to research by Forrester Group. ACKNOWLEDGEMENTS My journey in Artificial Intelligence and the scientific study of consciousness began almost three decades ago. Through-out this time I was fortunate to encounter many brilliant minds that influenced my thinking and opened new vistas of enquiry.

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Ross 175, 176 Asimov, Isaac 51, 58 Asperger syndrome 301 attention 156–7, 160–1 Augustine, St 126 australopithecines 5, 6, 22 autism 300, 301 autocatalysis 183–4, 295 automata 217–18 autopoiesis concept 294–5 awareness 144–6, 156–7, 160–1, 162–3 see also self-awareness Babbage, Charles 62, 221–5 Analytical Engine 225–7, 235 Difference Engine 217, 223–5, 227 Bach, Johann Sebastian 186, 187 Bacon, Francis (1561–1626) 102 Bacon, Roger (c. 1214–1292) 35–6 barber paradox 204 Baron-Cohen, Simon 301 Bateson, Gregory 175 Baudrillard, Jean 76–8 behavioural psychology 50 behaviourism 154 Bell, Alexander Graham 230 Berger, Hans 159 Berkeley, George (Anglican bishop) 139–40 Berners-Lee, Sir Tim 241 Bicentennial Man (1999 film), robot Andrew 55, 57 big bang of the modern mind 10, 12–15 big data economy 249–55 binary arithmetic 149 binary logic 198 bioinformatics 123, 249 Blade Runner (1982 film) 53–4, 57, 72 Bletchley Park codebreakers 234–6 body, role in consciousness 169–71 body–mind dualism 124 and the simulated universe 126–9 problems for AI 129–31 body-mind problem 32, 114–19, 129–31 Bonaparte, Napoleon 37 Boole, George 197, 229 Boolean logic 197–200, 230 Borges, Jorge Luis 241–2, 294–5 Bostrom, Nick 129 brain (human) architecture in early humans 13 as a cybernetic system 175–9 as a guide for AI development 280–2 as a second-order cybernetic system 185–6 as a self-referencing entity 186–9 development in childhood 10–11 Human Brain Project (HBP) xiv–xvi, 164–5, 287 imaging techniques 158–60 research effort 163–5 structure of brain cells (neurons) 42–3 brain anatomy, the interpreter 24 brain-based devices (BBDs) 284–5 BRAIN project 287 brain size australopithecines 6 enlargement over time 13 Homo erectus 7 Homo habilis 6 modern humans 8 Neanderthals (H. neanderthalensis) 7, 8 Braitenberg, Valentino 175 brazen head stories 35–6, 58 Brooks, Rodney 275–6, 288 Butler, Samuel 289–90 Byrne, David 19 Byron, Lord 60, 62, 63–4, 226 Byzantine automata 33–4 calculating machines 219–27 Cameron, James 66 Capgras Syndrome 70–3 Cars (film) 20 cave paintings 9, 10, 16, 17, 20–1, 23 cellular automata 295–6 Chabris, Christopher 160 Chalmers, David xiv–xvi, 121 Chambers, John 252 Changeux, Jean-Pierre 166–7 chemistry, organic and inorganic 39–40 chess-playing automaton 37 chess-playing computer, Deep Blue 263 child development 10–11 chimpanzees 5, 12, 13 China, increasing use of industrial robots 267–8 Chomsky, Noam 13 Christianity, influence of Plato 101–2 Chua, Leon 286 Clarke, Arthur C. 193, 257 client-server architectures 245–9 cloud technologies 246 Clynes, Manfred 79 coding of information 149–52 cogito ergo sum (I think therefore I am) (Descartes) 112–13, 120, 131, 188 cognitive archaeology 75 cognitive psychology 154–5, 157–8 Cold War 236–8, 240–1, 257 Colossus (first programmable electronic computer) 235 Colossus: The Forbin Project (1970 film) 65–6 Columbus, Chris 55 coma 307 complex systems, emergent properties 41 computational theory of mind 210–16 computer metaphor for life 123–5 for the brain 43–4, 146 computer simulation, possibility of living in 127–9 computers as algorithms 210–11 as philosophical zombies (p-zombies) 122 creation of ‘electronic brains’ 51–3 computing history 217–31 advent of personal computers 237–8 automata 217–18 business-specific computer languages 237 calculating machines 219–27 Cold War developments 236–8, 240–1 digital revolution 243–8 distinction between machine and program 221, 225–9 first email 241 hardware development 229–30, 237 mobile devices 245 origins of the Internet 238–43 Second World War developments 234–6 servers 245–9 software development 229 telecommunications development 238–43 conflicting beliefs, inability of AI to cope with 277–8 conscious artefacts as objects of love 48–59 consciousness and the body–mind problem 114–19 as pure information 123–5 definition 156–7 emergence through self-referencing 188–9 empirical approach 143–6 nature of 91–4 problem in AI xi–xviii qualia of 120–3, 157–8 quantum hypothesis 106–9 role of the body 169–71 scientific study of 154–65 signatures of 158, 161–3 the hard problem of 120–3, 157–8 three states of 156–7 towards a theory of 166–71 uploading into a computer 91, 119, 146 view of Aristotle 137–8 Cook, Matthew 296 Cooke, Sir William Fothergill 42 Coppélia (ballet) 61–2 Cowen, Tyler 266, 269, 300, 313 creation myths 114 creationism 289 creativity, lacking in AI 276–7 Crick, Francis xiii, 155, 158 cultural relativism 114 cybernetic prostheses 79–84 cybernetic systems, first-and second-order 185–6 cybernetics disciplines spawned from 174–5 emergence of order 184–6 emergent properties of systems 182–3 lessons from 306–8 nature of cybernetic systems 172–5 origins of 175–83 cyberspace, human existence in 146–7 cyborgs (cybernetic organisms) 79–85 Damasio, Antonio 306–7 Darwin, Charles 289–90 Darwin, Erasmus 61 David (android in AI) 56–7 deductive logic 196, 197 Deep Blue (chess-playing IBM computer) 263 Dehaene, Stanislas 158, 161–3, 177, 185 Dehaene–Changeux theory of consciousness 166–7 Dennett, Daniel 12, 143–6 Descartes, René 36–42, 86–7, 92, 112–19, 139, 154–5 cogito ergo sum (I think therefore I am) 112–13, 120, 131, 188 Dick, Philip K. 36, 54, 71–2 Dickens, Charles 40 digital Artificial Life 105–6 digital biological data 123–4 digital heaven 125–9 digital lives 124–5 digital revolution 243–8 digital transformation 232–4 drivers for 254–5 risks associated with 250–3 DNA printing 123–4 DNA structure, discovery of 180–1 Doctor Mirabilis 35 Dow Jones Flash Crash (6 May 2010) 247–8 Dr Faustus myth 63 Dracula (Bram Stoker) 62 Drake equation 132–3 dreaming 110 Drexler, Eric 288–9 Dreyfus, Hubert 278 drugs, mind-altering 110, 111 du Bois-Reymond, Emil 39 du Vaucanson, Jacques 218 dualism Cartesian 37–42, 113–19 computer metaphor for the brain 43–4 cyborgs 83 versus monism 92–3 see also body–mind dualism dualist thinking 18, 25–6 Dunbar, Robin 14 Dune (Frank Herbert) 290 dwellings, construction by Homo sapiens 9 dynamic fluids metaphor for life 31–3 Dyson, Freeman 291 Eccles, Sir John 117–119 Edelman, Gerald 167, 282–5 Edison, Thomas 230 Einstein, Albert 166 Eisenhower, President Dwight D. 240 élan vital (spirit of life) 40–1 electric metaphor for life 38–40 electroencephalography (EEG) 159, 160, 161 email 241 emergence in complex systems 41 of order out of chaos 184–6 of self-awareness in AI 273–5 emergent properties of systems 182–3 empathy 11 empiricism 32, 102–3, 138–42, 196 employment, occupations at risk of automation 266–9 endorphins 170 enhancing cybertechnology 81–4 ENIAC computer 235–6 Enigma code 234–5 Enlightenment 139 Eno, Brian 19 entropy 128, 149–50 Epimenides’ paradox 204–5 Erewhon (Samuel Butler) 290 Escher, M.

The Nature of Software Development: Keep It Simple, Make It Valuable, Build It Piece by Piece by Ron Jeffries

Amazon Web Services, anti-pattern, bitcoin, business cycle, business intelligence, business logic, business process, c2.com, call centre, cloud computing, continuous integration, Conway's law, creative destruction, dark matter, data science, database schema, deep learning, DevOps, disinformation, duck typing, en.wikipedia.org, fail fast, fault tolerance, Firefox, Hacker News, industrial robot, information security, Infrastructure as a Service, Internet of things, Jeff Bezos, Kanban, Kubernetes, load shedding, loose coupling, machine readable, Mars Rover, microservices, Minecraft, minimum viable product, MITM: man-in-the-middle, Morris worm, move fast and break things, OSI model, peer-to-peer lending, platform as a service, power law, ransomware, revision control, Ruby on Rails, Schrödinger's Cat, Silicon Valley, six sigma, software is eating the world, source of truth, SQL injection, systems thinking, text mining, time value of money, transaction costs, Turing machine, two-pizza team, web application, zero day

The “control plane” refers to software that exists to help manage the infrastructure and applications rather than directly delivering user functionality. Logging, monitoring, schedulers, scalers, load balancers, and configuration management are all parts of the control plane. The common thread running through these failures is that the automation is not being used to simply enact the will of a human administrator. Rather, it’s more like industrial robotics: the control plane senses the current state of the system, compares it to the desired state, and effects changes to bring the current state into the desired state. In the Reddit failure, ZooKeeper held a representation of the desired state. That representation was (temporarily) incorrect. In the case of the discovery service, the partitioned node was not able to correctly sense the current state.

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That will smart when the Amazon Web Services bill arrives! Controls and Safeguards The United States has a government agency called the Occupational Safety and Health Administration (OSHA). We don’t see them too often in the software field, but we can still learn from their safety advice for robots.[13] Industrial robots have multiple layers of safeguards to prevent damage to people, machines, and facilities. In particular, limiting devices and sensors detect when the robot is not operating in a “normal” condition. For example, suppose a robot arm has a rotating joint. There are limits on how far the arm is allowed to rotate based on the expected operating envelope.

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Apply hysteresis. (See ​Governor​.) Start machines quickly, but shut them down slowly. Starting new machines is safer than shutting old ones off. When the gap between expected state and observed state is large, signal for confirmation. This is equivalent to a big yellow rotating warning lamp on an industrial robot. Systems that consume resources should be stateful enough to detect if they’re trying to spin up infinity instances. Build in deceleration zones to account for momentum. Suppose your control plane senses excess load every second, but it takes five minutes to start a virtual machine to handle the load.

Surviving AI: The Promise and Peril of Artificial Intelligence by Calum Chace

3D printing, Ada Lovelace, AI winter, Airbnb, Alvin Toffler, artificial general intelligence, augmented reality, barriers to entry, basic income, bitcoin, Bletchley Park, blockchain, brain emulation, Buckminster Fuller, Charles Babbage, cloud computing, computer age, computer vision, correlation does not imply causation, credit crunch, cryptocurrency, cuban missile crisis, deep learning, DeepMind, dematerialisation, Demis Hassabis, discovery of the americas, disintermediation, don't be evil, driverless car, Elon Musk, en.wikipedia.org, epigenetics, Erik Brynjolfsson, everywhere but in the productivity statistics, Flash crash, friendly AI, Geoffrey Hinton, Google Glasses, hedonic treadmill, hype cycle, industrial robot, Internet of things, invention of agriculture, job automation, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, John von Neumann, Kevin Kelly, life extension, low skilled workers, machine translation, Mahatma Gandhi, means of production, mutually assured destruction, Neil Armstrong, Nicholas Carr, Nick Bostrom, paperclip maximiser, pattern recognition, peer-to-peer, peer-to-peer model, Peter Thiel, radical life extension, Ray Kurzweil, Robert Solow, Rodney Brooks, Second Machine Age, self-driving car, Silicon Valley, Silicon Valley ideology, Skype, South Sea Bubble, speech recognition, Stanislav Petrov, Stephen Hawking, Steve Jobs, strong AI, technological singularity, TED Talk, The future is already here, The Future of Employment, theory of mind, Turing machine, Turing test, universal basic income, Vernor Vinge, wage slave, Wall-E, zero-sum game

In the late 20th century, automation came mainly in the form of robots, particularly in the automotive and electrical / electronic industries – and this is set to accelerate. Robots are peripherals – physical extensions of AI systems. Despite the recession, sales of robots grew at 10% a year from 2008 to 2013, when 178,000 industrial robots were sold worldwide. China became the biggest market, installing 37,000 robots compared with 30,000 in the USA. (18) So the process of automation has been familiar in manual labour jobs for many years. It has also rendered obsolete large numbers of clerical jobs. As we saw in chapter 1, the word “computer” originally meant a person who does calculations, but the days when offices were filled with battalions of young (usually male) human computers are long gone.

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ENDNOTES (1) The term economic singularity was first used (as far as I can tell) by the economist Robin Hanson: http://mason.gmu.edu/~rhanson/fastgrow.html (2) http://arxiv.org/pdf/0712.3329v1.pdf (3) http://skyview.vansd.org/lschmidt/Projects/The%20Nine%20Types%20of%20Intelligence.html (4) The term AGI has been popularised by AI researcher Ben Goertzel, although he gives credit for its invention to Shane Legg and others: http://wp.goertzel.org/who-coined-the-term-agi/ (5) The Shape of Automation for Men and Management by Herbert Simon, 1965 (6) Computation: Finite and Infinite Machines by Marvin Minsky, 1967 (7) http://www.internetlivestats.com/google-search-statistics/ (8) http://en.wikipedia.org/wiki/High-frequency_trading (9) The Big Switch by Nicholas Carr (p 212) (10) https://en.wikipedia.org/wiki/People%27s_Liberation_Army#Third_Department (11) The Big Switch by Nicholas Carr (p 212) (12) https://www.youtube.com/watch?v=Skfw282fJak (13) The Economist, December 4, 2003 (14) Douglas Adams, The Salmon of Doubt (15) http://www.wired.com/2014/10/future-of-artificial-intelligence/ (16) http://lazooz.org/ (17) https://www.hrw.org/reports/2012/11/19/losing-humanity (18) http://www.ifr.org/industrial-robots/statistics/ (19) “Economic possibilities for our grandchildren”: http://www.econ.yale.edu/smith/econ116a/keynes1.pdf (20) https://www.youtube.com/watch?v=HW5Fvk8FNOQ (21) http://www.oxfordmartin.ox.ac.uk/downloads/academic/The_Future_of_Employment.pdf (22) http://www.dailymail.co.uk/sciencetech/article-2981946/Self-driving-cars-30-cities-2017-Pilot-projects-aims-mass-roll-driverless-vehicles-safe-they.html (23) http://www.alltrucking.com/faq/truck-drivers-in-the-usa/ (24) http://www.bls.gov/ooh/transportation-and-material-moving/bus-drivers.htm (25) http://www.bls.gov/ooh/transportation-and-material-moving/taxi-drivers-and-chauffeurs.htm (26) http://www.cristo-barrios.com/discografia/iamus-2/?

The Economics of Belonging: A Radical Plan to Win Back the Left Behind and Achieve Prosperity for All by Martin Sandbu

air traffic controllers' union, Airbnb, Alan Greenspan, autonomous vehicles, balance sheet recession, bank run, banking crisis, basic income, Berlin Wall, Bernie Sanders, Big Tech, Boris Johnson, Branko Milanovic, Bretton Woods, business cycle, call centre, capital controls, carbon footprint, carbon tax, Carmen Reinhart, centre right, collective bargaining, company town, debt deflation, deindustrialization, deskilling, Diane Coyle, Donald Trump, Edward Glaeser, eurozone crisis, Fall of the Berlin Wall, financial engineering, financial intermediation, full employment, future of work, gig economy, Gini coefficient, green new deal, hiring and firing, income inequality, income per capita, industrial robot, intangible asset, job automation, John Maynard Keynes: technological unemployment, Kenneth Rogoff, knowledge economy, knowledge worker, labour market flexibility, liquidity trap, longitudinal study, low interest rates, low skilled workers, manufacturing employment, Martin Wolf, meta-analysis, mini-job, Money creation, mortgage debt, new economy, offshore financial centre, oil shock, open economy, pattern recognition, pink-collar, precariat, public intellectual, quantitative easing, race to the bottom, Richard Florida, Robert Shiller, Robert Solow, Ronald Reagan, secular stagnation, social intelligence, TaskRabbit, total factor productivity, universal basic income, very high income, winner-take-all economy, working poor

Bradford DeLong, “NAFTA and Other Trade Deals Have Not Gutted American Manufacturing—Period,” Vox, 24 January 2017, https://www.vox.com/the-big-idea/2017/1/24/14363148/trade-deals-nafta-wto-china-job-loss-trump. 12. See Robert D. Atkinson, “Which Nations Really Lead in Industrial Robot Adoption?,” Information Technology and Innovation Foundation, November 2018, http://www2.itif.org/2018-industrial-robot-adoption.pdf. 13. Some of the highest estimates of factory jobs lost in the West because of trade with poor countries are those of Adrian Wood in “1990s Trade and Wages Debate.” He suggests that in 2014, there were twelve million fewer manufacturing jobs in the OECD because of trade with non-OECD countries.

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Without offshoring labour-intensive production tasks to low-wage economies, the pressure on companies to invest in more labour-saving technological upgrades at home would have been even stronger. Indeed, the high-income economies that have retained the strongest manufacturing sectors—Korea, Germany, Japan, Sweden—are those that have invested the most in industrial robots.12 Perhaps a greater share of the world’s industrial output could have been sourced in the West today if it had denied poorer countries a place in supply chains, but the effect on jobs would have been marginal (and less trade would also have meant fewer new factory jobs created in manufacturing for export).13 While I have focused on jobs, the same goes for wages.

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

A Declaration of the Independence of Cyberspace, AI winter, airport security, Andy Rubin, Apollo 11, Apple II, artificial general intelligence, Asilomar, augmented reality, autonomous vehicles, backpropagation, basic income, Baxter: Rethink Robotics, Bill Atkinson, Bill Duvall, bioinformatics, Boston Dynamics, Brewster Kahle, Burning Man, call centre, cellular automata, Charles Babbage, Chris Urmson, Claude Shannon: information theory, Clayton Christensen, clean water, cloud computing, cognitive load, collective bargaining, computer age, Computer Lib, computer vision, crowdsourcing, Danny Hillis, DARPA: Urban Challenge, data acquisition, Dean Kamen, deep learning, DeepMind, deskilling, Do you want to sell sugared water for the rest of your life?, don't be evil, Douglas Engelbart, Douglas Engelbart, Douglas Hofstadter, Dr. Strangelove, driverless car, dual-use technology, Dynabook, Edward Snowden, Elon Musk, Erik Brynjolfsson, Evgeny Morozov, factory automation, Fairchild Semiconductor, Fillmore Auditorium, San Francisco, From Mathematics to the Technologies of Life and Death, future of work, Galaxy Zoo, General Magic , Geoffrey Hinton, Google Glasses, Google X / Alphabet X, Grace Hopper, Gunnar Myrdal, Gödel, Escher, Bach, Hacker Ethic, Hans Moravec, haute couture, Herbert Marcuse, hive mind, hype cycle, hypertext link, indoor plumbing, industrial robot, information retrieval, Internet Archive, Internet of things, invention of the wheel, Ivan Sutherland, Jacques de Vaucanson, Jaron Lanier, Jeff Bezos, Jeff Hawkins, job automation, John Conway, John Markoff, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, John Perry Barlow, John von Neumann, Kaizen: continuous improvement, Kevin Kelly, Kiva Systems, knowledge worker, Kodak vs Instagram, labor-force participation, loose coupling, Marc Andreessen, Mark Zuckerberg, Marshall McLuhan, medical residency, Menlo Park, military-industrial complex, Mitch Kapor, Mother of all demos, natural language processing, Neil Armstrong, new economy, Norbert Wiener, PageRank, PalmPilot, pattern recognition, Philippa Foot, pre–internet, RAND corporation, Ray Kurzweil, reality distortion field, Recombinant DNA, Richard Stallman, Robert Gordon, Robert Solow, Rodney Brooks, Sand Hill Road, Second Machine Age, self-driving car, semantic web, Seymour Hersh, shareholder value, side project, Silicon Valley, Silicon Valley startup, Singularitarianism, skunkworks, Skype, social software, speech recognition, stealth mode startup, Stephen Hawking, Steve Ballmer, Steve Jobs, Steve Wozniak, Steven Levy, Stewart Brand, Strategic Defense Initiative, strong AI, superintelligent machines, tech worker, technological singularity, Ted Nelson, TED Talk, telemarketer, telepresence, telepresence robot, Tenerife airport disaster, The Coming Technological Singularity, the medium is the message, Thorstein Veblen, Tony Fadell, trolley problem, Turing test, Vannevar Bush, Vernor Vinge, warehouse automation, warehouse robotics, Watson beat the top human players on Jeopardy!, We are as Gods, Whole Earth Catalog, William Shockley: the traitorous eight, zero-sum game

In some cases I discovered that the designers resist thinking deeply about the paradoxical relationship between artificial intelligence and intelligence augmentation. Often, it comes down to a simple matter of economics. There is now a burgeoning demand for robots with abilities that far exceed those of the early industrial robots of the last half century. Even in already highly automated industries like agriculture, a new wave of “ag robots” are now driving tractors and harvesters, irrigating and weeding fields, conducting surveillance from the air, and generally increasing farm productivity. There are also many instances where the researchers think deeply about the paradox, and many of those researchers place themselves squarely in Engelbart’s camp.

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A crowd of 150 people in appropriate alien-themed costumes had gathered, including Google cofounder Sergey Brin, who wore a dress. In the basement of the sprawling mansion where the party was held, a robot arm grabbed small boxes one at a time and gaily tossed the souvenirs to an appreciative crowd. The robot itself consisted of a standard Japanese-made industrial robot arm outfitted with a suction gripper hand driven by a noisy air compressor. It helped that the robot could “see” the party favors it was picking up. For eyes—actually a single “eye”—the robot used the same sensor Microsoft originally added to the Xbox to capture the gestures of video game players in the living room.

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Eventually, Konolige didn’t even bother to show up at one of the meetings—he went kayaking instead. For a while Bradski tried to be a team player, but then he realized he was in danger of reentering the world of compromises that he had left at Intel. “What the hell,” he thought. “This isn’t me. I need to do what I want.” He started thinking about potential applications for industrial robotics integration, from moving boxes to picking up products with robot arms. After discussing robotics extensively with people in industry, he confirmed that companies were hungry for robots. He told Willow’s CEO that it was essential to have a plan B in case the home robot developments didn’t pan out.

The Innovation Illusion: How So Little Is Created by So Many Working So Hard by Fredrik Erixon, Bjorn Weigel

Airbnb, Alan Greenspan, Albert Einstein, American ideology, asset allocation, autonomous vehicles, barriers to entry, Basel III, Bernie Madoff, bitcoin, Black Swan, blockchain, Blue Ocean Strategy, BRICs, Burning Man, business cycle, Capital in the Twenty-First Century by Thomas Piketty, Cass Sunstein, classic study, Clayton Christensen, Colonization of Mars, commoditize, commodity super cycle, corporate governance, corporate social responsibility, creative destruction, crony capitalism, dark matter, David Graeber, David Ricardo: comparative advantage, discounted cash flows, distributed ledger, Donald Trump, Dr. Strangelove, driverless car, Elon Musk, Erik Brynjolfsson, Fairchild Semiconductor, fear of failure, financial engineering, first square of the chessboard / second half of the chessboard, Francis Fukuyama: the end of history, general purpose technology, George Gilder, global supply chain, global value chain, Google Glasses, Google X / Alphabet X, Gordon Gekko, Greenspan put, Herman Kahn, high net worth, hiring and firing, hockey-stick growth, Hyman Minsky, income inequality, income per capita, index fund, industrial robot, Internet of things, Jeff Bezos, job automation, job satisfaction, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, joint-stock company, Joseph Schumpeter, Just-in-time delivery, Kevin Kelly, knowledge economy, laissez-faire capitalism, low interest rates, Lyft, manufacturing employment, Mark Zuckerberg, market design, Martin Wolf, mass affluent, means of production, middle-income trap, Mont Pelerin Society, Network effects, new economy, offshore financial centre, pensions crisis, Peter Thiel, Potemkin village, precautionary principle, price mechanism, principal–agent problem, Productivity paradox, QWERTY keyboard, RAND corporation, Ray Kurzweil, rent-seeking, risk tolerance, risk/return, Robert Gordon, Robert Solow, Ronald Coase, Ronald Reagan, savings glut, Second Machine Age, secular stagnation, Silicon Valley, Silicon Valley startup, Skype, sovereign wealth fund, Steve Ballmer, Steve Jobs, Steve Wozniak, subprime mortgage crisis, technological determinism, technological singularity, TED Talk, telemarketer, The Chicago School, The Future of Employment, The Nature of the Firm, The Rise and Fall of American Growth, The Wealth of Nations by Adam Smith, too big to fail, total factor productivity, transaction costs, transportation-network company, tulip mania, Tyler Cowen, Tyler Cowen: Great Stagnation, uber lyft, University of East Anglia, unpaid internship, Vanguard fund, vertical integration, Yogi Berra

Paul Krugman calls it “the big meh,” suggesting that much of the new technology is “more fun than fundamental” and hence does not boost the economy as much as the media and tech developers claim.5 It is easy to agree with that view. Mobile gaming, for instance, has grown much faster than industrial robotics. While some observers might fret that “robots are coming,” the real concern is that industrial robots are not employed more widely. When people become anxious about rapid growth in the use of robots in services and industrial production in the future, they do not appreciate that growth is starting from low levels in absolute terms and that growth will need to accelerate much more if Western economies are to avoid supply disruptions.

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Robots may in fact be more part of the solution than the problem. Robots increase productivity and create jobs. For every industrial robot introduced, between three and five jobs are created, according to an industry study, and if indirect jobs are added that number notches up.82 That is perhaps an exaggeration, but there is plenty of research other than industry studies pointing in the same direction. For example, economists George Graetz and Guy Michaels found that industrial robots increased growth rates, wages, and total factor productivity in their study of the impact of utilizing robots in 17 countries between 1993 and 2007.

Click Here to Kill Everybody: Security and Survival in a Hyper-Connected World by Bruce Schneier

23andMe, 3D printing, air gap, algorithmic bias, autonomous vehicles, barriers to entry, Big Tech, bitcoin, blockchain, Brian Krebs, business process, Citizen Lab, cloud computing, cognitive bias, computer vision, connected car, corporate governance, crowdsourcing, cryptocurrency, cuban missile crisis, Daniel Kahneman / Amos Tversky, David Heinemeier Hansson, disinformation, Donald Trump, driverless car, drone strike, Edward Snowden, Elon Musk, end-to-end encryption, fault tolerance, Firefox, Flash crash, George Akerlof, incognito mode, industrial robot, information asymmetry, information security, Internet of things, invention of radio, job automation, job satisfaction, John Gilmore, John Markoff, Kevin Kelly, license plate recognition, loose coupling, market design, medical malpractice, Minecraft, MITM: man-in-the-middle, move fast and break things, national security letter, Network effects, Nick Bostrom, NSO Group, pattern recognition, precautionary principle, printed gun, profit maximization, Ralph Nader, RAND corporation, ransomware, real-name policy, Rodney Brooks, Ross Ulbricht, security theater, self-driving car, Seymour Hersh, Shoshana Zuboff, Silicon Valley, smart cities, smart transportation, Snapchat, sparse data, Stanislav Petrov, Stephen Hawking, Stuxnet, supply-chain attack, surveillance capitalism, The Market for Lemons, Timothy McVeigh, too big to fail, Uber for X, Unsafe at Any Speed, uranium enrichment, Valery Gerasimov, Wayback Machine, web application, WikiLeaks, Yochai Benkler, zero day

Darlene Storm (27 Apr 2015), “Researchers hijack teleoperated surgical robot: Remote surgery hacking threats,” Computerworld, https://www.computerworld.com/article/2914741/cybercrime-hacking/researchers-hijack-teleoperated-surgical-robot-remote-surgery-hacking-threats.html. 86and industrial robots: Thomas Fox-Brewster (3 May 2017), “Catastrophe warning: Watch an industrial robot get hacked,” Forbes, https://www.forbes.com/sites/thomasbrewster/2017/05/03/researchers-hack-industrial-robot-making-a-drone-rotor. 86Autonomous military systems deserve: Paul Scharre (24 Apr 2017), Army of None: Autonomous Weapons and the Future of War, W. W. Norton, https://books.google.com/books?id=sjMsDwAAQBAJ. 86The US Department of Defense defines: Heather Roff (9 Feb 2016), “Distinguishing autonomous from automatic weapons,” Bulletin of the Atomic Scientists, http://thebulletin.org/autonomous-weapons-civilian-safety-and-regulation-versus-prohibition/distinguishing-autonomous-automatic-weapons. 86If they are autonomous: Paul Scharre (29 Feb 2016), “Autonomous weapons and operational risk,” Center for a New American Security, https://www.cnas.org/publications/reports/autonomous-weapons-and-operational-risk. 86Technologists Bill Gates, Elon Musk, and Stephen Hawking: Michael Sainato (19 Aug 2015), “Stephen Hawking, Elon Musk, and Bill Gates warn about artificial intelligence,” Observer, http://observer.com/2015/08/stephen-hawking-elon-musk-and-bill-gates-warn-about-artificial-intelligence. 86The risks might be remote: Stuart Russell et al. (11 Jan 2015), “An open letter: Research priorities for robust and beneficial artificial intelligence,” Future of Life Institute, https://futureoflife.org/ai-open-letter. 86I am less worried about AI: These two essays talk about that: Ted Chiang (18 Dec 2017), “Silicon Valley is turning into its own worst fear,” BuzzFeed, https://www.buzzfeed.com/tedchiang/the-real-danger-to-civilization-isnt-ai-its-runaway.

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It is not the if, it’s only the when to me.” Robots offer the most evocative example of software autonomy combined with physical agency. Researchers have already exploited vulnerabilities in robots to remotely take control of them, and have found vulnerabilities in teleoperated surgical robots and industrial robots. Autonomous military systems deserve special mention. The US Department of Defense defines an autonomous weapon as one that selects a target and fires without intervention from a human operator. All weapons systems are lethal, and they are all prone to accidents. Adding autonomy increases the risk of accidental death significantly.

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

3D printing, additive manufacturing, Affordable Care Act / Obamacare, Airbnb, Albert Einstein, barriers to entry, Baxter: Rethink Robotics, behavioural economics, benefit corporation, Bretton Woods, business climate, business process, call centre, Capital in the Twenty-First Century by Thomas Piketty, carbon footprint, circular economy, cloud computing, collaborative consumption, collaborative economy, Computer Numeric Control, connected car, corporate social responsibility, creative destruction, crowdsourcing, disruptive innovation, driverless car, Elon Musk, fail fast, financial exclusion, financial innovation, gamification, global supply chain, IKEA effect, income inequality, industrial robot, intangible asset, Internet of things, job satisfaction, Khan Academy, Kickstarter, late fees, Lean Startup, low cost airline, M-Pesa, Mahatma Gandhi, Marc Benioff, megacity, minimum viable product, more computing power than Apollo, new economy, payday loans, peer-to-peer lending, Peter H. Diamandis: Planetary Resources, planned obsolescence, precision agriculture, race to the bottom, reshoring, risk tolerance, Ronald Coase, Salesforce, scientific management, self-driving car, shareholder value, sharing economy, Silicon Valley, Silicon Valley startup, six sigma, smart grid, smart meter, software as a service, standardized shipping container, Steve Jobs, supply-chain management, tacit knowledge, TaskRabbit, TED Talk, The Fortune at the Bottom of the Pyramid, the long tail, The Nature of the Firm, Tony Fadell, transaction costs, Travis Kalanick, unbanked and underbanked, underbanked, value engineering, vertical integration, women in the workforce, work culture , X Prize, yield management, Zipcar

In addition to 3D printing, the plummeting cost of industrial robots – such as Baxter, a $25,000 humanoid robot sold by Rethink Robotics – is unleashing a wave of automation in factories that could not only boost manufacturers’ productivity and quality but also their agility. SRI International, a research institute based in Silicon Valley, is working on a project funded by DARPA (Defence Advanced Research Projects Agency) to develop nimbler, smaller and lighter robotic arms that will be ten times cheaper and consume 20 times less energy than existing industrial robots, and yet perform complex tasks in dynamic settings more reliably.

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SRI International, a research institute based in Silicon Valley, is working on a project funded by DARPA (Defence Advanced Research Projects Agency) to develop nimbler, smaller and lighter robotic arms that will be ten times cheaper and consume 20 times less energy than existing industrial robots, and yet perform complex tasks in dynamic settings more reliably. Low-cost robotics is used particularly in Germany and Japan, where factory workforces are ageing rapidly. Indeed, Japan is already a robotics world leader, with over 300,000 robots operating in its factories. It is predicted that over 1 million industrial robots will be in use in the country by 2025. Given that a single robot can perform the work of ten humans, these 1 million robots would be equivalent to 15% of Japan’s 2012 workforce (approximately 65.3 million, according to World Bank data). “Robots are the cornerstone of Japan’s international competitiveness,” says Shunichi Uchiyama, head of manufacturing policymaking at Japan’s trade ministry.

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

2013 Report for America's Infrastructure - American Society of Civil Engineers - 19 March 2013, 3D printing, access to a mobile phone, additive manufacturing, Airbnb, Alan Greenspan, Albert Einstein, Amazon Mechanical Turk, Amazon Web Services, American Society of Civil Engineers: Report Card, Any sufficiently advanced technology is indistinguishable from magic, autonomous vehicles, barriers to entry, basic income, Baxter: Rethink Robotics, Boston Dynamics, British Empire, business cycle, business intelligence, business process, call centre, carbon tax, Charles Lindbergh, Chuck Templeton: OpenTable:, clean water, combinatorial explosion, computer age, computer vision, congestion charging, congestion pricing, corporate governance, cotton gin, creative destruction, crowdsourcing, data science, David Ricardo: comparative advantage, digital map, driverless car, employer provided health coverage, en.wikipedia.org, Erik Brynjolfsson, factory automation, Fairchild Semiconductor, falling living standards, Filter Bubble, first square of the chessboard / second half of the chessboard, Frank Levy and Richard Murnane: The New Division of Labor, Freestyle chess, full employment, G4S, game design, general purpose technology, global village, GPS: selective availability, Hans Moravec, happiness index / gross national happiness, illegal immigration, immigration reform, income inequality, income per capita, indoor plumbing, industrial robot, informal economy, intangible asset, inventory management, James Watt: steam engine, Jeff Bezos, Jevons paradox, jimmy wales, job automation, John Markoff, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, Joseph Schumpeter, Kevin Kelly, Khan Academy, Kiva Systems, knowledge worker, Kodak vs Instagram, law of one price, low skilled workers, Lyft, Mahatma Gandhi, manufacturing employment, Marc Andreessen, Mark Zuckerberg, Mars Rover, mass immigration, means of production, Narrative Science, Nate Silver, natural language processing, Network effects, new economy, New Urbanism, Nicholas Carr, Occupy movement, oil shale / tar sands, oil shock, One Laptop per Child (OLPC), pattern recognition, Paul Samuelson, payday loans, post-work, power law, price stability, Productivity paradox, profit maximization, Ralph Nader, Ray Kurzweil, recommendation engine, Report Card for America’s Infrastructure, Robert Gordon, Robert Solow, Rodney Brooks, Ronald Reagan, search costs, Second Machine Age, self-driving car, sharing economy, Silicon Valley, Simon Kuznets, six sigma, Skype, software patent, sovereign wealth fund, speech recognition, statistical model, Steve Jobs, Steven Pinker, Stuxnet, supply-chain management, TaskRabbit, technological singularity, telepresence, The Bell Curve by Richard Herrnstein and Charles Murray, the Cathedral and the Bazaar, the long tail, The Signal and the Noise by Nate Silver, The Wealth of Nations by Adam Smith, total factor productivity, transaction costs, Tyler Cowen, Tyler Cowen: Great Stagnation, Vernor Vinge, warehouse robotics, Watson beat the top human players on Jeopardy!, winner-take-all economy, Y2K

We spoke with inventors, investors, entrepreneurs, engineers, scientists, and many others who make technology and put it to work. Thanks to their openness and generosity, we had some futuristic experiences in today’s incredible environment of digital innovation. We’ve ridden in a driverless car, watched a computer beat teams of Harvard and MIT students in a game of Jeopardy!, trained an industrial robot by grabbing its wrist and guiding it through a series of steps, handled a beautiful metal bowl that was made in a 3D printer, and had countless other mind-melting encounters with technology. Where We Are This work led us to three broad conclusions. The first is that we’re living in a time of astonishing progress with digital technologies—those that have computer hardware, software, and networks at their core.

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What’s more, Brooks envisions creating robots that won’t need to be programmed by high-paid engineers; instead, the machines can be taught to do a task (or retaught to do a new one) by shop floor workers, each of whom need less than an hour of training to learn how to instruct their new mechanical colleagues. Brooks’s machines are cheap, too. At about $20,000, they’re a small fraction of the cost of current industrial robots. We got a sneak peek at these potential paradox-busters shortly before Rethink’s public unveiling of their first line of robots, named Baxter. Brooks invited us to the company’s headquarters in Boston to see these automatons, and to see what they could do. Baxter is instantly recognizable as a humanoid robot.

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In fact, in a list of all the candidates for this classification compiled by the economist Alexander Field, only steam power got more votes than ICT, which was tied with electricity as the second most commonly accepted GPT.9 If we are all in agreement, then why the debate over whether ICTs are ushering in a new golden age of innovation and growth? Because, the argument goes, their economic benefits have already been captured and now most new ‘innovation’ involves entertaining ourselves inexpensively online. According to Robert Gordon: The first industrial robot was introduced by General Motors in 1961. Telephone operators went away in the 1960s. . . . Airline reservations systems came in the 1970s, and by 1980 bar-code scanners and cash machines were spreading through the retail and banking industries. . . . The first personal computers arrived in the early 1980s with their word processing, word wrap, and spreadsheets. . . .

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

3D printing, additive manufacturing, adjacent possible, Airbnb, Amazon Mechanical Turk, Amazon Web Services, Apollo 11, augmented reality, autonomous vehicles, Boston Dynamics, Charles Lindbergh, cloud computing, company town, creative destruction, crowdsourcing, Daniel Kahneman / Amos Tversky, data science, deal flow, deep learning, dematerialisation, deskilling, disruptive innovation, driverless car, Elon Musk, en.wikipedia.org, Exxon Valdez, fail fast, Fairchild Semiconductor, fear of failure, Firefox, Galaxy Zoo, Geoffrey Hinton, Google Glasses, Google Hangouts, gravity well, hype cycle, ImageNet competition, industrial robot, information security, Internet of things, Jeff Bezos, John Harrison: Longitude, John Markoff, Jono Bacon, Just-in-time delivery, Kickstarter, Kodak vs Instagram, Law of Accelerating Returns, Lean Startup, life extension, loss aversion, Louis Pasteur, low earth orbit, Mahatma Gandhi, Marc Andreessen, Mark Zuckerberg, Mars Rover, meta-analysis, microbiome, minimum viable product, move fast and break things, Narrative Science, Netflix Prize, Network effects, Oculus Rift, OpenAI, optical character recognition, packet switching, PageRank, pattern recognition, performance metric, Peter H. Diamandis: Planetary Resources, Peter Thiel, pre–internet, Ray Kurzweil, recommendation engine, Richard Feynman, ride hailing / ride sharing, risk tolerance, rolodex, Scaled Composites, self-driving car, sentiment analysis, shareholder value, Sheryl Sandberg, Silicon Valley, Silicon Valley startup, skunkworks, Skype, smart grid, SpaceShipOne, stem cell, Stephen Hawking, Steve Jobs, Steven Levy, Stewart Brand, Stuart Kauffman, superconnector, Susan Wojcicki, synthetic biology, technoutopianism, TED Talk, telepresence, telepresence robot, Turing test, urban renewal, Virgin Galactic, Wayback Machine, web application, X Prize, Y Combinator, zero-sum game

Grab one of his arms, for example, and Baxter will turn his head in your direction, the tablet computer displaying a pair of wide-open eyes to demonstrate interest. But what is most exciting about Baxter is his user interface. Unlike most industrial robots, Baxter is human-safe. Getting in a room with a typical six-axis car-building robot is a good way to get dead—which explains why most industrial robots are cordoned off from humans. But Baxter doesn’t need a cage. Sensors detect when the robot hits something unexpected and stops the motion immediately, so “he” can’t hurt you. Moreover, Baxter has an elegant and simple user interface.

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And with AI soon coming online, it won’t be long before putting Baxter through his motions will be replaced by simply having a conversation with him. “Hey, Baxter, could you put this tire on that car?” “Baxter is a big step forward,” says Dr. Dan Barry,48 head of robotics at SU. “It’s the first robot that bridges the gap between mindless, repetitive, robust, single-purpose industrial robots and intelligent, widely sensing, situationally aware, computationally complex, delicate research robots.” More important, Baxter is the kind of robot that entrepreneurs can now build businesses around. Case in point: Digital Apparel, a Bay Area clothing start-up, plans to do 3-D scans of their customer’s bodies, then use those scans as a pattern for cutting and stitching denim to make perfect custom-fitting jeans.

Futureproof: 9 Rules for Humans in the Age of Automation by Kevin Roose

"World Economic Forum" Davos, adjacent possible, Airbnb, Albert Einstein, algorithmic bias, algorithmic management, Alvin Toffler, Amazon Web Services, Atul Gawande, augmented reality, automated trading system, basic income, Bayesian statistics, Big Tech, big-box store, Black Lives Matter, business process, call centre, choice architecture, coronavirus, COVID-19, data science, deep learning, deepfake, DeepMind, disinformation, Elon Musk, Erik Brynjolfsson, factory automation, fake news, fault tolerance, Frederick Winslow Taylor, Freestyle chess, future of work, Future Shock, Geoffrey Hinton, George Floyd, gig economy, Google Hangouts, GPT-3, hiring and firing, hustle culture, hype cycle, income inequality, industrial robot, Jeff Bezos, job automation, John Markoff, Kevin Roose, knowledge worker, Kodak vs Instagram, labor-force participation, lockdown, Lyft, mandatory minimum, Marc Andreessen, Mark Zuckerberg, meta-analysis, Narrative Science, new economy, Norbert Wiener, Northpointe / Correctional Offender Management Profiling for Alternative Sanctions, off-the-grid, OpenAI, pattern recognition, planetary scale, plutocrats, Productivity paradox, QAnon, recommendation engine, remote working, risk tolerance, robotic process automation, scientific management, Second Machine Age, self-driving car, Shoshana Zuboff, Silicon Valley, Silicon Valley startup, social distancing, Steve Jobs, Stuart Kauffman, surveillance capitalism, tech worker, The Future of Employment, The Wealth of Nations by Adam Smith, TikTok, Travis Kalanick, Uber and Lyft, uber lyft, universal basic income, warehouse robotics, Watson beat the top human players on Jeopardy!, work culture

Do you ever look back at pictures or videos from years ago and feel like you’re seeing not just a skinnier or fresher-faced version of you, but a more surprising version of you, one who thought more independently, engaged more deeply with ideas, and ventured further out of the mainstream? I’ll go first. I feel all of these things, all of the time. And I don’t just think it’s the haze of nostalgia. I think it’s about the machines. So far in this book, we’ve talked mainly about external forms of automation—industrial robots, machine learning algorithms, back-office AI software. But there is a kind of internalized automation taking place inside many of us that, in some ways, is much more dangerous. This kind of automation burrows into our brains and affects our inner lives—changing how we think, what we desire, whom we trust.

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Kawai wanted to be like the Kami-sama someday, and he’d sought out a job in the local Toyota plant’s forging division, where he could spend every day practicing taking glowing-hot rods out of a furnace, placing them on his anvil, and carefully hammering them into crankshafts. Auto manufacturing was a solid, middle-class job, but it was increasingly looking like an endangered one. A few years earlier, General Motors—then the biggest automaker in the world—had installed the world’s first industrial robot: a four-thousand-pound, one-armed behemoth known as the Unimate. The Unimate became a pop culture sensation, even appearing on The Tonight Show with Johnny Carson, where it wowed the audience by showing off various tricks it had been programmed to do, including putting a golf ball, pouring itself a glass of beer, and conducting the Tonight Show band.

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

3D printing, AI winter, algorithmic management, algorithmic trading, AlphaGo, Amazon Mechanical Turk, Amazon Robotics, augmented reality, autonomous vehicles, blockchain, business process, call centre, carbon footprint, circular economy, cloud computing, computer vision, correlation does not imply causation, crowdsourcing, data science, deep learning, DeepMind, digital twin, disintermediation, Douglas Hofstadter, driverless car, en.wikipedia.org, Erik Brynjolfsson, fail fast, friendly AI, fulfillment center, future of work, Geoffrey Hinton, Hans Moravec, industrial robot, Internet of things, inventory management, iterative process, Jeff Bezos, job automation, job satisfaction, knowledge worker, Lyft, machine translation, Marc Benioff, natural language processing, Neal Stephenson, personalized medicine, precision agriculture, Ray Kurzweil, recommendation engine, RFID, ride hailing / ride sharing, risk tolerance, robotic process automation, Rodney Brooks, Salesforce, Second Machine Age, self-driving car, sensor fusion, sentiment analysis, Shoshana Zuboff, Silicon Valley, Snow Crash, software as a service, speech recognition, tacit knowledge, telepresence, telepresence robot, text mining, the scientific method, uber lyft, warehouse automation, warehouse robotics

That specific task was part of a rigid, fixed chain of work that would generally include humans doing other predefined tasks—for instance, inspecting the stamped metal parts in order to discard defects. Contrast that traditional assembly line with a factory where robots are much smaller and more flexible, able to work alongside humans. A factory where those robots and other types of machinery are using embedded sensors and sophisticated AI algorithms. Unlike earlier generations of industrial robotics—which were typically bulky, unintelligent, and somewhat dangerous pieces of machinery—these new types of collaborative robots are equipped with the ability to sense their environment, comprehend, act, and learn, thanks to machine-learning software and other related AI technologies. All this then enables the work processes to be self-adapting, with fixed assembly lines giving way to flexible human-machine teams that can be put together on the fly.

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What’s more, people seemed to be less consistent at the task than they were at others.10 Now a person loosely fits the door panel and then the door moves along the line to the nearby cobot to finish the job. The cobot is outfitted with cameras and other sensors so it can tell when a person is close. Unlike traditional industrial robots that perform set movements over and over without awareness of their surroundings, the cobot in the BMW plant deftly avoids knocking into people or getting in the way. Furthermore, these robots can be reprogrammed by nonprogrammers using a tablet. No coding skills are needed. And because they are lightweight, they can be moved anywhere in a warehouse and perform various tasks, depending on the need.11 The human-robot system then acts as an extender of people’s ability to work; they’re now less likely to get fatigued or injured.

The Rise and Fall of Nations: Forces of Change in the Post-Crisis World by Ruchir Sharma

"World Economic Forum" Davos, Asian financial crisis, backtesting, bank run, banking crisis, Berlin Wall, Bernie Sanders, BRICs, business climate, business cycle, business process, call centre, capital controls, Capital in the Twenty-First Century by Thomas Piketty, Carmen Reinhart, central bank independence, centre right, colonial rule, commodity super cycle, corporate governance, creative destruction, crony capitalism, currency peg, dark matter, debt deflation, deglobalization, deindustrialization, demographic dividend, demographic transition, Deng Xiaoping, Doha Development Round, Donald Trump, driverless car, Edward Glaeser, Elon Musk, eurozone crisis, failed state, Fall of the Berlin Wall, falling living standards, financial engineering, Francis Fukuyama: the end of history, Freestyle chess, Gini coefficient, global macro, Goodhart's law, guns versus butter model, hiring and firing, hype cycle, income inequality, indoor plumbing, industrial robot, inflation targeting, Internet of things, Japanese asset price bubble, Jeff Bezos, job automation, John Markoff, Joseph Schumpeter, junk bonds, Kenneth Rogoff, Kickstarter, knowledge economy, labor-force participation, Larry Ellison, lateral thinking, liberal capitalism, low interest rates, Malacca Straits, Mark Zuckerberg, market bubble, Mary Meeker, mass immigration, megacity, megaproject, Mexican peso crisis / tequila crisis, middle-income trap, military-industrial complex, mittelstand, moral hazard, New Economic Geography, North Sea oil, oil rush, oil shale / tar sands, oil shock, open immigration, pattern recognition, Paul Samuelson, Peter Thiel, pets.com, plutocrats, Ponzi scheme, price stability, Productivity paradox, purchasing power parity, quantitative easing, Ralph Waldo Emerson, random walk, rent-seeking, reserve currency, Ronald Coase, Ronald Reagan, savings glut, secular stagnation, Shenzhen was a fishing village, Silicon Valley, Silicon Valley startup, Simon Kuznets, smart cities, Snapchat, South China Sea, sovereign wealth fund, special economic zone, spectrum auction, Steve Jobs, tacit knowledge, tech billionaire, The Future of Employment, The Wisdom of Crowds, Thomas Malthus, total factor productivity, trade liberalization, trade route, tulip mania, Tyler Cowen: Great Stagnation, unorthodox policies, Washington Consensus, WikiLeaks, women in the workforce, work culture , working-age population

While the robotics revolution could come faster than most previous technology revolutions, it is likely to be gradual enough to complement rather than destroy the human workforce. A huge gap still exists between the size of the world’s industrial robot population—about 1.6 million—and the global industrial labor force of about 320 million humans. Most of these industrial robots are currently unintelligent machines, committed to a single task like turning a bolt or painting a car door, and indeed nearly half of them work in the car industry, which is still the single largest employer (of humans) in the United States.

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The job picture has been particularly strong in Germany, Japan, and South Korea—which are also the industrial countries that employ the most robots. Admittedly, the automaton invasion is in its early stages and picking up speed, but both historical and current evidence suggests humans will come to some agreeable arrangement with these invaders of their own creation. One of the new trends is cobots, industrial robots with swing arms safe enough to work alongside and in cooperation with people, rather than inside cages. The techno-optimists believe robots will be our servants, not our replacements, and will free us for lives of pampered leisure in retirement. Be that as it may, a strong practical argument can be made that the answer to fewer young people is more robots.

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“In China, the robots are going to come just in time” to rescue the country from population decline.14 In the future, economists may count growth in the working robot population as a positive sign for economic growth, the same way that today they analyze growth in the working-age human population. Whether by design or happy accident, many of the countries with the most rapidly aging populations also have the largest robot populations. According to the International Federation of Robots, the highest density of robots in the world can be found in South Korea, which in 2013 had 437 industrial robots per 10,000 employees, followed by Japan with 323, and Germany with 282. China was way behind with only 14, but on the bright side—arguably—it also had the world’s fastest-growing robot population, up by 36,000 in 2013. I am optimistic on automation in the workplace because I believe that the laws that govern the economic world are similar to those that govern the physical world, in which nothing is ever lost, nothing is gained, and everything is transformed.

Visual Thinking: The Hidden Gifts of People Who Think in Pictures, Patterns, and Abstractions by Temple Grandin, Ph.D.

2013 Report for America's Infrastructure - American Society of Civil Engineers - 19 March 2013, 3D printing, a long time ago in a galaxy far, far away, air gap, Albert Einstein, American Society of Civil Engineers: Report Card, Apollo 11, Apple II, ASML, Asperger Syndrome, autism spectrum disorder, autonomous vehicles, Black Lives Matter, Boeing 737 MAX, Captain Sullenberger Hudson, clean water, cloud computing, computer vision, Computing Machinery and Intelligence, coronavirus, cotton gin, COVID-19, defense in depth, Drosophila, Elon Musk, en.wikipedia.org, GPT-3, Gregor Mendel, Greta Thunberg, hallucination problem, helicopter parent, income inequality, industrial robot, invention of movable type, Isaac Newton, James Webb Space Telescope, John Nash: game theory, John von Neumann, Jony Ive, language acquisition, longitudinal study, Mark Zuckerberg, Mars Rover, meta-analysis, Neil Armstrong, neurotypical, pattern recognition, Peter Thiel, phenotype, ransomware, replication crisis, Report Card for America’s Infrastructure, Robert X Cringely, Saturday Night Live, self-driving car, seminal paper, Silicon Valley, Skinner box, space junk, stem cell, Stephen Hawking, Steve Jobs, Steve Wozniak, Tacoma Narrows Bridge, TaskRabbit, theory of mind, TikTok, twin studies, unpaid internship, upwardly mobile, US Airways Flight 1549, warehouse automation, warehouse robotics, web application, William Langewiesche, Y Combinator

“Work, Skills, Community: Restoring Opportunity for the Working Class.” Opportunity America, American Enterprise Institute, and Brookings Institution, 2018. https://www.aei.org/wp-content/uploads/2018/11/Work-Skills-Community-FINAL-PDF.pdf?x91208. Chakravarty, S. “World’s Top 10 Industrial Robot Manufacturers.” Market Research Reports, 2019. https://www.marketresearchreports.com/blog/2019/05/08/world’s-top-10-industrial-robot-manufacturers. Chang, C. “Can Apprenticeships Help Reduce Youth Unemployment?” Century Foundation, November 15, 2015. https://tcf.org/content/report/apprenticeships/. Collins, M. “Why America Has a Shortage of Skilled Workers.”

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In the most highly automated systems, there will always be a need for highly skilled people to install and repair the machines, the service that makes rapid delivery to your doorstep possible. American companies such as Amazon, Walmart, and Frito-Lay are customers. The most advanced robotic warehouse comes from the UK, and Japan reigns supreme for automated machine tools. According to Market Research Reports, the top five manufacturers of industrial robots are located in Switzerland, Japan, and Germany. In addition to making most of the world’s iPhones, China builds the clever machines that put the popular chocolate swirls in soft-serve ice cream cones. As of 2014, Europe had 37 percent of the elevator-modernization market and the United States only 17 percent.

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

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

Giant red OFF buttons, of the sort commonly depicted in movies, were placed in strategic locations in case of an emergency. Industrial robots have evolved significantly over the decades, but most of the advances have been in the precision of their control, strength, and durability as well as reduced weight and cost. As a general matter, their working environments have to be designed around them, rather than the other way around. Because they typically can’t see, hear, or otherwise sense their surroundings, those surroundings have to be simple and predictable. If an industrial robot arm is expecting a bolt to be in a particular position at a particular moment, it damn well better be exactly where it’s supposed to be or the entire process has to be restarted.

Industrial Internet by Jon Bruner

air gap, autonomous vehicles, barriers to entry, Boeing 747, commoditize, computer vision, data acquisition, demand response, electricity market, en.wikipedia.org, factory automation, Google X / Alphabet X, industrial robot, Internet of things, job automation, loose coupling, natural language processing, performance metric, Silicon Valley, slashdot, smart grid, smart meter, statistical model, the Cathedral and the Bazaar, web application

Cheap, easy-to-program microcontrollers; powerful open-source software; and the support of hardware collectives and innovation labs[41] make it possible for enthusiasts and minimally-funded entrepreneurs to create sophisticated projects of the sort that would have been available only to well-funded electrical engineers just a few years ago — anything from autonomous cars to small-scale industrial robots. In the same way that expertise in software isn’t necessary to create a successful Web app, expertise barriers will fall in software-machine interfaces, opening innovation to a big, broad, smart community. Neil Gershenfeld, director of the Center for Bits and Atoms at MIT, compares the development of the amateur hardware movement to the development of the computer from mainframe to minicomputer to hobbyist computer and then to the ubiquitous personal computer.

Wired for War: The Robotics Revolution and Conflict in the 21st Century by P. W. Singer

agricultural Revolution, Albert Einstein, Alvin Toffler, Any sufficiently advanced technology is indistinguishable from magic, Atahualpa, barriers to entry, Berlin Wall, Bill Joy: nanobots, Bletchley Park, blue-collar work, borderless world, Boston Dynamics, Charles Babbage, Charles Lindbergh, clean water, Craig Reynolds: boids flock, cuban missile crisis, digital divide, digital map, Dr. Strangelove, en.wikipedia.org, Ernest Rutherford, failed state, Fall of the Berlin Wall, Firefox, Ford Model T, Francisco Pizarro, Frank Gehry, friendly fire, Future Shock, game design, George Gilder, Google Earth, Grace Hopper, Hans Moravec, I think there is a world market for maybe five computers, if you build it, they will come, illegal immigration, industrial robot, information security, interchangeable parts, Intergovernmental Panel on Climate Change (IPCC), invention of gunpowder, invention of movable type, invention of the steam engine, Isaac Newton, Jacques de Vaucanson, job automation, Johann Wolfgang von Goethe, junk bonds, Law of Accelerating Returns, Mars Rover, Menlo Park, mirror neurons, Neal Stephenson, New Urbanism, Nick Bostrom, no-fly zone, PalmPilot, paperclip maximiser, pattern recognition, precautionary principle, private military company, RAND corporation, Ray Kurzweil, RFID, robot derives from the Czech word robota Czech, meaning slave, Rodney Brooks, Ronald Reagan, Schrödinger's Cat, Silicon Valley, social intelligence, speech recognition, Stephen Hawking, Strategic Defense Initiative, strong AI, technological singularity, The Coming Technological Singularity, The Wisdom of Crowds, Timothy McVeigh, Turing test, Vernor Vinge, Virgin Galactic, Wall-E, warehouse robotics, world market for maybe five computers, Yogi Berra

Computers were delivering well past expectations, with the military seeking to integrate them in all possible manners. But robotics wasn’t completely dormant. In 1956, the world’s first robot company, Unimation (Universal Automation), was founded, and in 1962, the first industrial robot, Unimate, was placed on a production line at General Motors. In 1973, the first industrial robot controlled by a computer was installed by Unimation’s only competitor, the Cincinnati Milacron Corp. It was called T3 (The Tomorrow Tool). The first real mobile robot, not bound to an assembly line or lab, came in 1968. Shakey was built at the Stanford Research Institute and was novel for being able to move down a hallway without bumping into the walls.

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On the first day of trading, iRobot’s public value hit $620 million. At the market’s close, a PackBot rang the bell at the New York Stock Exchange, the first robot ever to do so. THE iROBOT WAY iRobot’s business model splits its sales effort between a consumer division that targets robots for the home and a government and industrial robots division that mainly targets the military. The military business currently makes up about a third of revenue, but market analysts are “really excited by it” and predict it will soon become about half the company’s revenue. iRobot also has a vibrant research team led by Andrew Bennett, who was part of the team that raced to New York on 9/11.

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We invest small seed money in stuff we think might have promise.... Basically it’s like prospecting.” When he first was sent to Japan, Sonntag tells how he wondered, “Why the hell do we have an office in Japan? It’s expensive. It’s tough on the family.” But now he describes it as “essential” to his job. About a third of all the world’s industrial robots are in Japan. These raw numbers aside, the best visual evidence of Japan’s knack for robots comes at the “Big Sight” complex in Tokyo. A massive convention center with ten major halls, it is the host of IREX, the International Robotics Exhibition. Held since 1973, the convention now has some one thousand booths of robot exhibitors that range from factory robots to “life assistance” robots (nursebots).

Radical Technologies: The Design of Everyday Life by Adam Greenfield

3D printing, Airbnb, algorithmic bias, algorithmic management, AlphaGo, augmented reality, autonomous vehicles, bank run, barriers to entry, basic income, bitcoin, Black Lives Matter, blockchain, Boston Dynamics, business intelligence, business process, Californian Ideology, call centre, cellular automata, centralized clearinghouse, centre right, Chuck Templeton: OpenTable:, circular economy, cloud computing, Cody Wilson, collective bargaining, combinatorial explosion, Computer Numeric Control, computer vision, Conway's Game of Life, CRISPR, cryptocurrency, David Graeber, deep learning, DeepMind, dematerialisation, digital map, disruptive innovation, distributed ledger, driverless car, drone strike, Elon Musk, Ethereum, ethereum blockchain, facts on the ground, fiat currency, fulfillment center, gentrification, global supply chain, global village, Goodhart's law, Google Glasses, Herman Kahn, Ian Bogost, IBM and the Holocaust, industrial robot, informal economy, information retrieval, Internet of things, Jacob Silverman, James Watt: steam engine, Jane Jacobs, Jeff Bezos, Jeff Hawkins, job automation, jobs below the API, John Conway, John Markoff, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, John Perry Barlow, John von Neumann, joint-stock company, Kevin Kelly, Kickstarter, Kiva Systems, late capitalism, Leo Hollis, license plate recognition, lifelogging, M-Pesa, Mark Zuckerberg, means of production, megacity, megastructure, minimum viable product, money: store of value / unit of account / medium of exchange, natural language processing, Network effects, New Urbanism, Nick Bostrom, Occupy movement, Oculus Rift, off-the-grid, PalmPilot, Pareto efficiency, pattern recognition, Pearl River Delta, performance metric, Peter Eisenman, Peter Thiel, planetary scale, Ponzi scheme, post scarcity, post-work, printed gun, proprietary trading, RAND corporation, recommendation engine, RFID, rolodex, Rutger Bregman, Satoshi Nakamoto, self-driving car, sentiment analysis, shareholder value, sharing economy, Shenzhen special economic zone , Sidewalk Labs, Silicon Valley, smart cities, smart contracts, social intelligence, sorting algorithm, special economic zone, speech recognition, stakhanovite, statistical model, stem cell, technoutopianism, Tesla Model S, the built environment, The Death and Life of Great American Cities, The Future of Employment, Tony Fadell, transaction costs, Uber for X, undersea cable, universal basic income, urban planning, urban sprawl, vertical integration, Vitalik Buterin, warehouse robotics, When a measure becomes a target, Whole Earth Review, WikiLeaks, women in the workforce

Whether most of us quite realize it or not, we already live in a time in which technical systems have learned at least some skills that have always been understood as indices of the deepest degree of spiritual attainment. These questions have rarely been more present than they are in the case of a Yaskawa industrial robot, trained in 2015 to perform precision feats with a Japanese fighting sword as part of a promotional campaign called the Bushido Project.7 To accomplish this act of training, master swordsman and Guinness world record-holder Isao Machii was garbed in a full-body motion-capture suit, and recorded in high resolution as he performed the basic moves of his chosen art.8 (The narration of the promotional video Yaskawa released is careful to refer to this art as iaijutsu, the technical craft of swordfighting, as opposed to iaido, the Way of the Sword; as we’ll see, the distinction will become important.)

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., “Mastering the Game of Go with Deep Neural Networks and Tree Search,” Nature, Volume 529, Issue 7587, pp. 484–9, January 28, 2016. 4.Younggil An and David Ormerod, Relentless: Lee Sedol vs Gu Li, Go Game Guru, 2016. 5.Nature Video, “The Computer That Mastered Go,” January 27, 2016, YouTube.com. 6.Ormerod, David. “Alphago Shows Its True Strength in 3rd Victory Against Lee Sedol,” Go Game Guru, March 12, 2016, gogameguru.com. 7.Yaskawa Electric Corporation, “YASKAWA BUSHIDO PROJECT: Industrial Robot vs Sword Master,” June 4, 2015, YouTube.com. 8.See Machii’s official website at http://nihontou.jp/syuushinryuu/intro.htm. 9.Cade Metz, “The Sadness and Beauty of Watching Google’s AI Play Go,” Wired, March 11, 2016. 10.Jo Liss, tweet, December 8, 2015, twitter.com/jo_liss/status/674332649226436613 11.Hector J.

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See Google Siemens, 52–4, 56 Silk Road exchange, 131 Silver, David, 265 Simone, Nina, 261 Sipilä, Juha, 204 Sirer, Emin Gün, 178 Siri virtual assistant, 39 Situationism, 64, 190 Slock.it, 156, 170, 175–6 slow jam (music genre), 221 Slum– and Shackdwellers International, 169 smart city, 33, 48, 52, 52, 55, 59 smart contracts, 115, 147, 150, 153–7, 163, 166, 168, 170, 172, 306 smart home, 33, 36, 38, 46, 48 smartphone, 3, 8–33, 38, 49, 64, 67, 72, 77, 133, 137, 273, 285–6, 313 as “network organ,” 27–9 as platform for augmented reality, 67, 72 as platform for financial transactions, 133, 137 environmental implications of, 18–19 incompleteness at time of purchase, 17 teardown of, 14–16 ubiquity of, 313 smart property, 149–53 Smith, Zachary, 103, 105 Snæfellsjökull glacier, 83 Snaptrends, 227–8, 231, 254 Sobibor, 61 social credit, 285, 311 social dividend, 204 social media, 26, 192, 227–8, 276, 286 Sociometric Solutions, 197 Solanas, Valerie, 191 South Sea Company, the, 165 Soylent nutrient slurry, 35 SpatialKey, 227 Spielberg, Steven, 227 Spivak, Gayatri Chakravorty, 311 Srnicek, Nick, 88, 90–1, 111, 190, 203, 205, 303 Stacks, 275, 277, 280–1, 283–6, 292–5, 299, 313–14 Stanford Dogs Dataset, 219 Stanford University, 283 startups, 13, 118, 137, 145–6, 280–2, 286 Stavrides, Stavros, 173 Sterling, Bruce, 275 Stolpersteine, 72, 74 Stratasys, 103–4, 108 Summers, Larry, 201 Super Sad True Love Story (Shteyngart), 246 Superstudio, 191 supervised learning, 216 SWaCH wastepickers’ collective, 98–9 Swedish death metal (music genre), 221 SweepTheStreets, 170 Szabo, Nick, 150, 303, 306 Target (retail chain), 196 Taylor, Frederick, 35 Taylor, Simon, 160 technolibertarians, 140, 150, 283 Tencent, 285 Tešanovic, Jasmina, 62 Tesla, 166, 193, 222–5, 243, 254, 264, 270, 285 Autopilot feature, 222–5, 243, 254, 256, 270 Model S, 222–4 Model X, 222 operating system 7.0, 222 tetrapods, 301–7 Theatro, 196–7 Theory of Self–Reproducing Automata (Neumann), 86 “Theses on Feuerbach” (Marx), 305 Thiel, Peter, 148 Thingiverse, 103, 105 Tide laundry detergent, 46–47 Topography of Terror, Berlin museum, 70 touchscreen, 15–16, 38, 43, 194 travel-to-crime, 231 Tual, Stephan, 170 Twitter, 51, 137, 268 Uber, 4, 40, 41, 193, 245, 270, 276, 285, 293 driverless cars, 193, 270 Ultimaker 3D printer, 88, 101, 104, 295 United States Constitution, 230, 235 universal basic income, UBI, 203–5, 288, 292, 294 universal constructor, 86 Universal Declaration of Human Rights, 91 University College London, 85 unnecessariat, 181, 206, 297 unsupervised deep learning, 220 Urban Dynamics (Forrester), 56 Utrecht, 204 value network, 264 van Rijn, Rembrandt Harmenszoon, 262 Vélib, 2 Velvet Underground, the, 228 Venezuelan bolívar, 122 Venmo, 41 Verlan, 311 Virginia Company, the, 165 virtual assistants, 38, 41–2, 286 virtual reality, 65, 82–3, 275, 296 Visa, 120, 136, 159 Vitality, 36 Vkontakte, 241 von Furstenberg, Diane, 84 von Neumann, John, 86 “wake word,” interface command, 41 Washington State, 192 Waterloo University, 148 Watt, James, 104 Wendy’s, 197 Wernick, Miles, 233 Westegren, Tim, 220 Western Union, 120 WhatsApp, 281 Whole Earth Review (magazine), 34 WiFi, 11, 17, 25, 46, 66 Wiggins, Shayla, 63–5 WikiLeaks, 120, 137 Williams, Alex, 190, 203 Williams, Raymond, 315 Wilson, Cody, 108, 111 Winograd Schema, 270 The Wire (TV series), 54 Wired (magazine), 34 Wolf, Gary, 34 World Bank, 133 World Economic Forum, 194 Yahoo, 219 yamato–damashii, 267 Yaskawa Motoman MH24 industrial robot, 266 yuan (currency), 135 Zamfir, Vlad, 177 Zen Buddhism, 34, 284 ZeroBlock application, 131 The Zero Marginal Cost Society (Rifkin), 88, 205

Shadow Work: The Unpaid, Unseen Jobs That Fill Your Day by Craig Lambert

airline deregulation, Asperger Syndrome, banking crisis, Barry Marshall: ulcers, big-box store, business cycle, carbon footprint, cashless society, Clayton Christensen, cognitive dissonance, collective bargaining, Community Supported Agriculture, corporate governance, crowdsourcing, data science, disintermediation, disruptive innovation, emotional labour, fake it until you make it, financial independence, Galaxy Zoo, ghettoisation, gig economy, global village, helicopter parent, IKEA effect, industrial robot, informal economy, Jeff Bezos, job automation, John Maynard Keynes: Economic Possibilities for our Grandchildren, Mark Zuckerberg, new economy, off-the-grid, pattern recognition, plutocrats, pneumatic tube, recommendation engine, Schrödinger's Cat, Silicon Valley, single-payer health, statistical model, the strength of weak ties, The Theory of the Leisure Class by Thorstein Veblen, Thorstein Veblen, Turing test, unpaid internship, Vanguard fund, Vilfredo Pareto, you are the product, zero-sum game, Zipcar

Downsizing is an in-house breed of shadow work created by thinning out both senior people and support staff. Second, automation replaces employees with machines. This has gone on for centuries, at least since the Industrial Revolution and probably longer. Automation pervades manufacturing and many service industries. Robots do not draw salaries, belong to labor unions, or receive fringe benefits. They need maintenance but don’t require vacation time, sick time, maternity leave, or, best of all, health insurance. Robots are impeccable “team players,” with no personal agendas. They’ll work round the clock and on weekends at their regular hourly rate.

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Equally superfluous, but amusing to its creator, is an alarm clock that automatically fills a dish of water for your cat. Or try a unicycle whose spokes light up with LEDs. These diversions, again, are hobbies, not shadow work. In contrast, the technology of 3-D printing is opening tracts of shadow work that will grow exponentially. A 3-D printer is a type of industrial robot that has become affordable to consumers, with some priced well under $1,000. Such printers can manufacture three-dimensional objects of nearly any shape by “printing out” a design from a digital file. Websites like Thingiverse.com offer thousands of such designs. The 3-D printer builds up the object by an additive process, laying down successive layers of a material (typically plastic, though ceramics and even steel are available at the high end) under computer control.

Humans Are Underrated: What High Achievers Know That Brilliant Machines Never Will by Geoff Colvin

Ada Lovelace, autonomous vehicles, Baxter: Rethink Robotics, behavioural economics, Black Swan, call centre, capital asset pricing model, commoditize, computer age, corporate governance, creative destruction, deskilling, driverless car, en.wikipedia.org, flying shuttle, Freestyle chess, future of work, Google Glasses, Grace Hopper, Hans Moravec, industrial cluster, industrial robot, interchangeable parts, job automation, knowledge worker, low skilled workers, Marc Andreessen, meta-analysis, Narrative Science, new economy, rising living standards, self-driving car, sentiment analysis, Silicon Valley, Skype, social intelligence, Steve Jobs, Steve Wozniak, Steven Levy, Steven Pinker, theory of mind, Tim Cook: Apple, transaction costs, Tyler Cowen

Many more examples are appearing. You can train a Baxter robot (from Rethink Robotics) to do all kinds of things—pack or unpack boxes, take items to or from a conveyor belt, fold a T-shirt, carry things around, count them, inspect them—just by moving its arms and hands (“end-effectors”) in the desired way. Many previous industrial robots had to be surrounded by safety cages because they could do just one thing in one way, over and over, and that’s all they knew; if you got between a welding robot and the piece it was welding, you were in deep trouble. But Baxter doesn’t hurt anyone as it hums about the shop floor; it adapts its movements to its environment by sensing everything around it, including people.

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Census Bureau, http://www.census.gov/people/io/files/acs08_detailedoccupations.pdf. You can train a Baxter robot . . . http://www.rethinkrobotics.com/baxter/. Robots went into the wreckage . . . “Meet the Robots of Fukushima Daiichi,” IEEE Spectrum, 28 February 2014, http://spectrum.ieee.org/slideshow/robotics/industrial-robots/meet-the-robots-of-fukushima-daiichi. By 2008 about 12,000 combat robots . . . “Pushing the Boundaries of Traditional HRI,” Science and Technology Innovations, Fall 2013, p. 7. Published by the University of Central Florida Institute for Simulation and Training. Some, barely larger than a shoebox . . .

Makers by Chris Anderson

3D printing, Airbnb, Any sufficiently advanced technology is indistinguishable from magic, Apple II, autonomous vehicles, barriers to entry, Buckminster Fuller, Build a better mousetrap, business process, carbon tax, commoditize, company town, Computer Numeric Control, crowdsourcing, dark matter, David Ricardo: comparative advantage, deal flow, death of newspapers, dematerialisation, digital capitalism, DIY culture, drop ship, Elon Musk, factory automation, Firefox, Ford Model T, future of work, global supply chain, global village, hockey-stick growth, hype cycle, IKEA effect, industrial robot, interchangeable parts, Internet of things, inventory management, James Hargreaves, James Watt: steam engine, Jeff Bezos, job automation, Joseph Schumpeter, Kickstarter, Lean Startup, manufacturing employment, Mark Zuckerberg, means of production, Menlo Park, Neal Stephenson, Network effects, planned obsolescence, private spaceflight, profit maximization, QR code, race to the bottom, Richard Feynman, Ronald Coase, Rubik’s Cube, Scaled Composites, self-driving car, Sheryl Sandberg, side project, Silicon Valley, Silicon Valley startup, Skype, slashdot, South of Market, San Francisco, SpaceShipOne, spinning jenny, Startup school, stem cell, Steve Jobs, Steve Wozniak, Steven Levy, Stewart Brand, supply-chain management, the long tail, The Nature of the Firm, The Wealth of Nations by Adam Smith, TikTok, Tragedy of the Commons, transaction costs, trickle-down economics, vertical integration, Virgin Galactic, Whole Earth Catalog, X Prize, Y Combinator

Sometimes this comes from management techniques, but the really powerful changes come from new tools. And there is no tool more powerful than the computer itself. Rather than just driving the modern factory, the computer is becoming the model for it. Infinitely flexible and adaptable, general-purpose industrial robots can be combined to create the universal Making Machine. And like computers, they work at any scale, from the mile-long NUMMI plant to your desktop. That—not just the rise of advanced technology, but also its democratization—is the real revolution. Chapter 9 The Open Organization To make things a new way, you need to make companies a new way, too.

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Even Chinese firms are moving toward more robotic production, not just to insulate firms from rising salary pressure, but also to avoid the labor condition controversies that dogged Foxconn and Apple for the past few years. Not everything can be automated, of course, and there is a still a lot of handwork in your iPad. But industrial robots are getting cheaper and better all the time, while humans are getting more expensive. So the decision on where to make things has become less about salaries. Yet China still has a sizable advantage in everything from electronics to toys and textiles, as the labels on your clothes and gadgets prove.

The Turing Option by Harry Harrison, Marvin Minsky

industrial robot, pattern recognition, Silicon Valley, telepresence, telerobotics, theory of mind, Turing test, undersea cable, VTOL

Bug-Off seems to know the behavior of every insect described in this book." Brian handed Ben a large volume entitled Handbook of Insect Ethology, 2018 Edition. "But how can Bug-Off tell which insect it is dealing with? They all look the same to me." "A good question—since pattern recognition has been the bane of AI from the very first day that research began. Industrial robots were never very good at recognizing and assembling parts if they weren't presented in a certain way. There are thousands of different signals involved in seeing a human face, then recognizing who it is. If you wrote a program for picking bugs off bushes you would have to program in every bug in the world, and size and rotation position and everything else.

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" "A sample of what?" "A robot. This is a machine I have developed that I plan to show to some private investors." "Their names?" "I cannot reveal that. A confidential business matter." Fennelly made another note while Brian unlocked the box and opened the lid. "This is a basic model of an industrial robot. It can answer simple questions and take verbal input. That is how it is controlled." Even the garda by the door was interested in this, turning his head to look. The detective gazed down at the unassembled parts with a baffled expression. "Shall I turn it on?" Brian asked. "It can talk—but not very well."

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"It can talk—but not very well." Sven would love that. He reached down and pressed one of the latches. "Can you hear me?" "Yes—I can—hear—you." A great job of ham acting, scratchy and monotone like a cheap toy. At least it caught the attention of the lawmen. "What are you?" "I am—an industrial—robot. I follow—instructions." "If that is enough, Lieutenant, I will turn it off." "Just a moment, if you please. What is that?" He pointed to the hollow plastic head. "To make the demonstration more interesting I occasionally mount that on the robot. It draws attention. If you don't mind I'll turn if off, the battery you know."

The Rent Is Too Damn High: What to Do About It, and Why It Matters More Than You Think by Matthew Yglesias

Edward Glaeser, falling living standards, gentrification, Home mortgage interest deduction, income inequality, industrial robot, Jane Jacobs, land reform, mortgage tax deduction, New Urbanism, pets.com, rent control, rent-seeking, restrictive zoning, Robert Gordon, Robert Shiller, San Francisco homelessness, Saturday Night Live, Silicon Valley, statistical model, transcontinental railway, transit-oriented development, urban sprawl, white picket fence

More diligent workers might be able to work at a faster-paced assembly line or dig coal out of the ground more quickly. At a visit to a factory in Germany, I saw a relatively small number of highly productive workers churn out an amazing quantity of solar panels with the assistance of a dazzling array of industrial robots. The real issue isn’t the quantity of widgets a worker makes, but the value of his output. The workers at a coal mine may be no better at pulling stuff out of the ground than the workers at a gold mine on the other side of the continent, but gold is more valuable than coal, so the gold miners are producing more output.

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

23andMe, 3D printing, Airbnb, Amazon Mechanical Turk, Amazon Web Services, anti-fragile, augmented reality, autonomous vehicles, Baxter: Rethink Robotics, behavioural economics, Ben Horowitz, bike sharing, bioinformatics, bitcoin, Black Swan, blockchain, Blue Ocean Strategy, book value, Burning Man, business intelligence, business process, call centre, chief data officer, Chris Wanstrath, circular economy, Clayton Christensen, clean water, cloud computing, cognitive bias, collaborative consumption, collaborative economy, commoditize, corporate social responsibility, cross-subsidies, crowdsourcing, cryptocurrency, dark matter, data science, Dean Kamen, deep learning, DeepMind, dematerialisation, discounted cash flows, disruptive innovation, distributed ledger, driverless car, Edward Snowden, Elon Musk, en.wikipedia.org, Ethereum, ethereum blockchain, fail fast, game design, gamification, Google Glasses, Google Hangouts, Google X / Alphabet X, gravity well, hiring and firing, holacracy, Hyperloop, industrial robot, Innovator's Dilemma, intangible asset, Internet of things, Iridium satellite, Isaac Newton, Jeff Bezos, Joi Ito, Kevin Kelly, Kickstarter, knowledge worker, Kodak vs Instagram, Law of Accelerating Returns, Lean Startup, life extension, lifelogging, loose coupling, loss aversion, low earth orbit, Lyft, Marc Andreessen, Mark Zuckerberg, market design, Max Levchin, means of production, Michael Milken, minimum viable product, natural language processing, Netflix Prize, NetJets, Network effects, new economy, Oculus Rift, offshore financial centre, PageRank, pattern recognition, Paul Graham, paypal mafia, peer-to-peer, peer-to-peer model, Peter H. Diamandis: Planetary Resources, Peter Thiel, Planet Labs, prediction markets, profit motive, publish or perish, radical decentralization, Ray Kurzweil, recommendation engine, RFID, ride hailing / ride sharing, risk tolerance, Ronald Coase, Rutger Bregman, Salesforce, Second Machine Age, self-driving car, sharing economy, Silicon Valley, skunkworks, Skype, smart contracts, Snapchat, social software, software is eating the world, SpaceShipOne, speech recognition, stealth mode startup, Stephen Hawking, Steve Jobs, Steve Jurvetson, subscription business, supply-chain management, synthetic biology, TaskRabbit, TED Talk, telepresence, telepresence robot, the long tail, Tony Hsieh, transaction costs, Travis Kalanick, Tyler Cowen, Tyler Cowen: Great Stagnation, uber lyft, urban planning, Virgin Galactic, WikiLeaks, winner-take-all economy, X Prize, Y Combinator, zero-sum game

As former astronaut Dan Barry says of a toy drone helicopter available on Amazon for seventeen dollars, “It has a gyro in it that space shuttle engineers would have spent $100 million to have thirty years ago.” And that’s just biotech and robotics. We are also seeing plummeting costs across a host of other technologies, including the following: 3D printing Cost (averages) for equivalent functionality: $40,000 (2007) to $100 (2014) Scale: 400x in 7 years Industrial robots Cost: $500,000 (2008) to $22,000 (2013) Scale: 23x in 5 years Drones Cost: $100,000 (2007) to $700 (2013) Scale: 142x in 6 years Solar Cost: $30 per kWh (1984) to $0.16 per kWh (2014) Scale: 200x in 20 years Sensors (3D LIDAR sensor) Cost: $20,000 (2009) to $79 (2014) Scale: 250x in 5 years Biotech (DNA sequencing of one whole human DNA profile) Cost: $10 million (2007) to $1,000 (2014) Scale: 10,000x in 7 years Neurotech (BCI devices) Cost: $4,000 (2006) to $90 (2011) Scale: 44x in 5 years Medicine (full body scan) Cost: $10,000 (2000) to $500 (2014) Scale: 20x in 14 years In each of these domains, at least one aspect is being information-enabled, which then catapults it onto the bullet train of Moore’s Law as the pace of development accelerates into a doubling pattern.

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The best part is that, thanks to the drastically lower costs of many accelerating technologies today, it doesn’t cost all that much to set up an advanced laboratory. As outlined in our Chapter One table on falling technology costs, ten years ago it cost $100,000 to establish a DNA synthesis lab; today that price is down to about $5,000. And while an industrial robot would set you back a million bucks a decade ago, the latest model of that same robot (Rethink Robotics’ Baxter robot) is now available for $22,000. In the realm of MEMS sensors, the outlay for accelerometers, microphones, gyroscopes, cameras and magnetometers has dropped 80 percent or more compared to five years ago, according to McKinsey.

The Glass Cage: Automation and Us by Nicholas Carr

Airbnb, Airbus A320, Andy Kessler, Atul Gawande, autonomous vehicles, Bernard Ziegler, business process, call centre, Captain Sullenberger Hudson, Charles Lindbergh, Checklist Manifesto, cloud computing, cognitive load, computerized trading, David Brooks, deep learning, deliberate practice, deskilling, digital map, Douglas Engelbart, driverless car, drone strike, Elon Musk, Erik Brynjolfsson, Evgeny Morozov, Flash crash, Frank Gehry, Frank Levy and Richard Murnane: The New Division of Labor, Frederick Winslow Taylor, future of work, gamification, global supply chain, Google Glasses, Google Hangouts, High speed trading, human-factors engineering, indoor plumbing, industrial robot, Internet of things, Ivan Sutherland, Jacquard loom, James Watt: steam engine, job automation, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, Kevin Kelly, knowledge worker, low interest rates, Lyft, machine readable, Marc Andreessen, Mark Zuckerberg, means of production, natural language processing, new economy, Nicholas Carr, Norbert Wiener, Oculus Rift, pattern recognition, Peter Thiel, place-making, plutocrats, profit motive, Ralph Waldo Emerson, RAND corporation, randomized controlled trial, Ray Kurzweil, recommendation engine, robot derives from the Czech word robota Czech, meaning slave, scientific management, Second Machine Age, self-driving car, Silicon Valley, Silicon Valley ideology, software is eating the world, Stephen Hawking, Steve Jobs, systems thinking, tacit knowledge, TaskRabbit, technological determinism, technological solutionism, technoutopianism, TED Talk, The Wealth of Nations by Adam Smith, turn-by-turn navigation, Tyler Cowen, US Airways Flight 1549, Watson beat the top human players on Jeopardy!, William Langewiesche

That’s not so. The total number of worldwide manufacturing jobs has been falling for years, even in industrial powerhouses like China, while overall manufacturing output has grown sharply.31 Machines are replacing factory workers faster than economic expansion creates new manufacturing positions. As industrial robots become cheaper and more adept, the gap between lost and added jobs will almost certainly widen. Even the news that companies like GE and Apple are bringing some manufacturing work back to the United States is bittersweet. One of the reasons the work is returning is that most of it can be done without human beings.

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The dot-com bubble of the late 1990s, when for a few euphoric years riches flooded out of computer networks and into personal brokerage accounts, seemed to herald the start of a golden age of unlimited economic opportunity—what technology boosters dubbed a “long boom.” But the good times proved fleeting. Now we’re seeing that, as Norbert Wiener predicted, automation doesn’t play favorites. Computers are as good at analyzing symbols and otherwise parsing and managing information as they are at directing the moves of industrial robots. Even the people who operate complex computer systems are losing their jobs to software, as data centers, like factories, become increasingly automated. The vast server farms operated by companies like Google, Amazon, and Apple essentially run themselves. Thanks to virtualization, an engineering technique that uses software to replicate the functions of hardware components like servers, the facilities’ operations can be monitored and controlled by algorithms.

The Autonomous Revolution: Reclaiming the Future We’ve Sold to Machines by William Davidow, Michael Malone

2013 Report for America's Infrastructure - American Society of Civil Engineers - 19 March 2013, agricultural Revolution, Airbnb, AlphaGo, American Society of Civil Engineers: Report Card, Automated Insights, autonomous vehicles, basic income, benefit corporation, bitcoin, blockchain, blue-collar work, Bob Noyce, business process, call centre, Cambridge Analytica, cashless society, citizen journalism, Clayton Christensen, collaborative consumption, collaborative economy, collective bargaining, creative destruction, crowdsourcing, cryptocurrency, deep learning, DeepMind, disintermediation, disruptive innovation, distributed ledger, en.wikipedia.org, Erik Brynjolfsson, fake news, Filter Bubble, Ford Model T, Francis Fukuyama: the end of history, general purpose technology, Geoffrey West, Santa Fe Institute, gig economy, Gini coefficient, high-speed rail, holacracy, Hyperloop, income inequality, industrial robot, Internet of things, invention of agriculture, invention of movable type, invention of the printing press, invisible hand, Jane Jacobs, job automation, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, Joseph Schumpeter, license plate recognition, low interest rates, Lyft, Mark Zuckerberg, mass immigration, Network effects, new economy, peer-to-peer lending, QWERTY keyboard, ransomware, Richard Florida, Robert Gordon, robo advisor, Ronald Reagan, Second Machine Age, self-driving car, sharing economy, Shoshana Zuboff, Silicon Valley, Simon Kuznets, Skinner box, Snapchat, speech recognition, streetcar suburb, Stuxnet, surveillance capitalism, synthetic biology, TaskRabbit, The Death and Life of Great American Cities, The Rise and Fall of American Growth, the scientific method, trade route, Turing test, two and twenty, Uber and Lyft, uber lyft, universal basic income, uranium enrichment, urban planning, vertical integration, warehouse automation, zero day, zero-sum game, Zipcar

Brian, 29, 97–98, 103, 194 artificial intelligence: in behavior prediction and modification, 117 history and evolution of, 45–47 job loss with, 43, 110 in law enforcement, 115 nonmonetizable productivity of, 60 substitutional equivalences with, 15–16, 45 threats from, xi, xii, 4, 16, 43, 48–49, 110, 117 Assante, Michael, 174 authoritarianism, 115, 158–159, 161–162, 180, 193 automatons/automation: in airline industry, 72, 97–98, 103–104 benefits possible from, xii, 4–5, 7, 14, 19 economy impacted by, 12–13 in financial industry, 10, 43, 77–78, 81–83, 102 government service and, 105 health care impacts with, 14, 48 human knowledge pursuit impacted by, xi, 16 job displacement predictions with, 98, 105–106 job market impacts from, 7, 11, 12, 31, 34, 43, 47–49, 73, 77–78, 95–106, 108, 187–189 vehicle, 84, 99–102 ZEVs created with, 12, 48–49 automobile industry: autonomous vehicle evolution and impact on, 84, 99–102 car-sharing impact on, 70, 84–86, 100, 101–102 Ford Motor Company production in, xii, 22, 33, 53, 103 horse-related industry impacted by, 54 Industrial Revolution role of, 53–54, 152 industrial robots and early use in, xii infrastructures as result of, 107–108 innovations leading up to, 52–53 social phase change with, 32, 53–54 Autonomous Economy, 60–61, 96–98 Autonomous Revolution: abundance available with, 7, 14, 67, 94, 188, 194–195 action-oriented approach to, 7, 14, 17, 19, 20, 94, 107, 180 Agricultural Revolution contrasted with, 25–26 cultural norms in adaptation to, 151, 153–157, 159 defining and key factors of, 6, 11, 34, 58, 95 early impacts of, 7, 11, 12 optimism and, 193–195 rate of change in, 13, 17–18, 34, 37, 192–193 recommendations for offsetting negative impacts of, 107–112 substitutional equivalence forms and examples of, 15–17, 42–50.

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See cyber currencies cultural lag, 38, 181, 187, 189–190, 192 cultural norms: of Agricultural Revolution, 151–152 Autonomous Revolution’s requirement of new, 151, 153–157, 159 of Industrial Revolution, 152–153, 182–183 customers/consumers: algorithmic prisons for, 126, 127 data collection protections for, 127–128 industrial robots in relation to, xii information equivalences for, 43–44 as products, 120–123. See also retail sector cybercrime and security, 132, 153–154 credit card, 74–76 cyber currencies, 78–80, 177–178 evolution of, 172–173 fake news classification as, 169–170 financial, 39–40, 75–76, 78–80, 171–172, 177–178 global effort needed for, 179 government response to, 172–176, 179 public utilities threat with, 173, 174 response rate relation to rate of, 171–172 Russia-based, 174 cyber currencies, 10, 83 blockchain technology of, 79, 80 electricity and miners involved with, 176 governance rules and systems, 176–178 government regulation needed for, 176–177 security with, 78–80, 177–178 as spatial equivalence, 16 cyber weapons, 16, 172–173, 174, 176 Daimler, Gottlieb, 53 Data and Goliath (Schneier), 127 Data Protection Directive, 129 data tracking/collection: advertising revenues’ role in, 89, 90, 120–123 algorithmic prisons with, 13, 114, 123–128 behavior manipulation in, 117, 121, 123 consumer protections against, 127–128 cookies’ role in, 89, 116, 117–118, 128 of credit rating agencies, 118–119 evolution and factors behind abuses of, 116–118 freemium business model role in, 121–123, 129–130 government agencies purchasing, 119, 131 information fiduciaries as protection for, 129–131 laws and regulations on, 128–130 liberty threats to and factors with, 13, 116–117, 123–128 privacy threat evolution with, 116–119 from social networking sites, 116, 118 transparency of, 127 Death and Life of Great American Cities, The (Jacobs), 109 Deep Blue, 46–47 delivery services, 102 democracy: authoritarianism threat to, 158–159 collective identity of citizens key to, 163, 166, 168 income inequality in relation to, 163–164 social media/networking threats to, 7, 18, 168–169 depression, 147–148, 166 Dichter, Ernest, 135 discrimination, 162–163, 165–166 displacement: business, 71, 72–73, 99 job, with job creation historically, 51–54, 106 job, without new job creation, 43, 51, 60–64, 98–99, 105–106 Distracted Minds (Gazzaley), 155 Echo, 119 economic policy and metrics: Depression-era, 67, 160 on monetizable productivity, 58–59 non-monetizable productivity in relation to, 52, 58–59, 66, 67, 68 unemployment rates in relation to, 106–107 “Economic Possibilities for Our Grandchildren” (Keynes), 187–189 economy: automation impacts on, 12–13 Autonomous, 60–61, 96–98 entrepreneurship, 110 gig, 7, 34, 63, 84, 85, 94 Second Economy contrasted with traditional, 97–98, 103 sharing, 70, 83–87, 100, 101–102 social empathy decline with decline of, 164–165 traditional compared to Autonomous, 96 elder care, 111 election tampering, 89, 167, 180, 186 electricity: cyber currency mining use of, 176 invention of, 29, 182 ELIZA, 46 Elsevier, Reed, 119 email, 60–61, 150 emotion detection technology, 115–116 empires, rise and fall of, 6–7, 24–25 End of History and the Last Man, The (Fukuyama), 158 Enlightenment, xii, 2, 22, 152 entrepreneurship, rates of, 110 Epic of Gilgamesh, The, 24, 183–184, 185 Equifax, 75–76, 118, 126, 130 Estonia, 174 ethnicity.

Skyjack: The Hunt for D. B. Cooper by Geoffrey Gray

airport security, Boeing 747, company town, D. B. Cooper, Google Earth, industrial robot, off-the-grid

Over the years, they’ve included: a doggy-proof latch for dog cages; a machine that makes a gizmo to mix paint; an air compressor that sprays paint on objects like gumballs; several recreational objects built from fiberglass, like hang gliders, water skis, canoes. The industrial robot age, in the early eighties, should have been his moment. To learn about advanced computer systems, Tom crashed a robot convention like an undercover agent. Pretending to be a buyer, he asked salespeople how the robots worked and recorded their answers with a hidden tape recorder. He transcribed the conversations and built his own industrial robot in his mother’s basement. But before his company went public, his investors put all their money in handheld breathalyzers.

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

This means that even if strategic industrial policy were to bring the factories home, it would not bring the factory jobs home because they were not taken by the Chinese and Mexicans but by R2-D2 and C-3PO. The Chinese and Mexicans are also acquiring more and more robots. Since 2010, Chinese companies have increased the number of industrial robots from 50,000 to 800,000.4 That’s why they can be more productive and competitive. This does not mean that we will run out of jobs – just like the spinning machine, mechanical looms, the steam engine, the car, the computer, the ATM and other innovations didn’t kill all jobs. Instead, automation creates complementary industries and frees up purchasing power to hire more people.

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This applies to many forms of manufacturing work but also to clerks responsible for registers and warehouses or bank and postal tellers who handled invoices or received, counted and handed over banknotes. These were jobs that required precision and accuracy but not improvisation and social intelligence – just the kind of work industrial robots, computers and ATMs are good at. Yet this does not mean the total number of jobs declines. The money we previously spent on this type of work remains and is now used to buy other types of work in what is sometimes called ‘the new middle-class jobs’, such as in transport, healthcare, education, entertainment and culture.

Physics of the Future: How Science Will Shape Human Destiny and Our Daily Lives by the Year 2100 by Michio Kaku

agricultural Revolution, AI winter, Albert Einstein, Alvin Toffler, Apollo 11, Asilomar, augmented reality, Bill Joy: nanobots, bioinformatics, blue-collar work, British Empire, Brownian motion, caloric restriction, caloric restriction, cloud computing, Colonization of Mars, DARPA: Urban Challenge, data science, delayed gratification, digital divide, double helix, Douglas Hofstadter, driverless car, en.wikipedia.org, Ford Model T, friendly AI, Gödel, Escher, Bach, Hans Moravec, hydrogen economy, I think there is a world market for maybe five computers, industrial robot, Intergovernmental Panel on Climate Change (IPCC), invention of movable type, invention of the telescope, Isaac Newton, John Markoff, John von Neumann, Large Hadron Collider, life extension, Louis Pasteur, Mahatma Gandhi, Mars Rover, Mars Society, mass immigration, megacity, Mitch Kapor, Murray Gell-Mann, Neil Armstrong, new economy, Nick Bostrom, oil shale / tar sands, optical character recognition, pattern recognition, planetary scale, postindustrial economy, Ray Kurzweil, refrigerator car, Richard Feynman, Rodney Brooks, Ronald Reagan, Search for Extraterrestrial Intelligence, Silicon Valley, Simon Singh, social intelligence, SpaceShipOne, speech recognition, stem cell, Stephen Hawking, Steve Jobs, synthetic biology, telepresence, The future is already here, The Wealth of Nations by Adam Smith, Thomas L Friedman, Thomas Malthus, trade route, Turing machine, uranium enrichment, Vernor Vinge, Virgin Galactic, Wall-E, Walter Mischel, Whole Earth Review, world market for maybe five computers, X Prize

We are still at the stage where Mother Nature’s lowliest creatures can outsmart our most intelligent robots. EXPERT SYSTEMS Today, many people have simple robots in their homes that can vacuum their carpets. There are also robot security guards patrolling buildings at night, robot guides, and robot factory workers. In 2006, it was estimated that there were 950,000 industrial robots and 3,540,000 service robots working in homes and buildings. But in the coming decades, the field of robotics may blossom in several directions. But these robots won’t look like the ones of science fiction. The greatest impact may be felt in what are called expert systems, software programs that have encoded in them the wisdom and experience of a human being.

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The Japanese have also excelled at producing robots that can interact socially with humans. In Nagoya, there is the robot chef that can create a standard fast-food dinner in a few minutes. You simply punch in what you want from a menu and the robot chef produces your meal in front of you. Built by Aisei, an industrial robotics company, this robot can cook noodles in 1 minute and 40 seconds and can serve 80 bowls on a busy day. The robot chef looks very much like ones on the automobile assembly lines in Detroit. You have two large mechanical arms, which are precisely programmed to move in a certain sequence. Instead of screwing and welding metal in a factory, however, these robotic fingers grab ingredients from a series of bowls containing dressing, meat, flour, sauces, spices, etc.

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Abrahams, “A World Without Work,” in Denning and Metcalfe, p. 136. ­ ­6 “Today, you can buy chess programs for $49”: Richard Strozzi Heckler, “Somatics in Cyberspace,” in Denning, p. 281. ­ ­7 “To this day, AI programs”: Sheffield et al., p. 30. ­ ­8 “100 million things, about the number a typical person knows”: Kurzweil, p. 267. ­ ­9 In 2006, it was estimated that there were 950,000 industrial robots: World Robotics 2007, IFR Statistical Department (Frankfurt: International Federation of Robotics, 2007). 10 “Discovering how the brain works”: Fred Hapgood, “Reverse Engineering the Brain,” Technology Review, July 11, 2006, www.­technologyreview.­com/­read_­article.­aspx­?id=17111. 11 He was in a semiconscious state for several weeks: John M.

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

3D printing, active measures, additive manufacturing, Airbnb, autonomous vehicles, back-to-the-land, benefit corporation, big-box store, bike sharing, bioinformatics, bitcoin, business logic, business process, Chris Urmson, circular economy, clean tech, clean water, cloud computing, collaborative consumption, collaborative economy, commons-based peer production, Community Supported Agriculture, Computer Numeric Control, computer vision, crowdsourcing, demographic transition, distributed generation, DIY culture, driverless car, Eben Moglen, electricity market, en.wikipedia.org, Frederick Winslow Taylor, Free Software Foundation, Garrett Hardin, general purpose technology, global supply chain, global village, Hacker Conference 1984, Hacker Ethic, industrial robot, informal economy, information security, Intergovernmental Panel on Climate Change (IPCC), intermodal, Internet of things, invisible hand, Isaac Newton, James Watt: steam engine, job automation, John Elkington, John Markoff, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, Julian Assange, Kickstarter, knowledge worker, longitudinal study, low interest rates, machine translation, Mahatma Gandhi, manufacturing employment, Mark Zuckerberg, market design, mass immigration, means of production, meta-analysis, Michael Milken, mirror neurons, natural language processing, new economy, New Urbanism, nuclear winter, Occupy movement, off grid, off-the-grid, oil shale / tar sands, pattern recognition, peer-to-peer, peer-to-peer lending, personalized medicine, phenotype, planetary scale, price discrimination, profit motive, QR code, RAND corporation, randomized controlled trial, Ray Kurzweil, rewilding, RFID, Richard Stallman, risk/return, Robert Solow, Rochdale Principles, Ronald Coase, scientific management, search inside the book, self-driving car, shareholder value, sharing economy, Silicon Valley, Skype, smart cities, smart grid, smart meter, social web, software as a service, spectrum auction, Steve Jobs, Stewart Brand, the built environment, the Cathedral and the Bazaar, the long tail, The Nature of the Firm, The Structural Transformation of the Public Sphere, The Wealth of Nations by Adam Smith, The Wisdom of Crowds, Thomas Kuhn: the structure of scientific revolutions, Thomas L Friedman, too big to fail, Tragedy of the Commons, transaction costs, urban planning, vertical integration, warehouse automation, Watson beat the top human players on Jeopardy!, web application, Whole Earth Catalog, Whole Earth Review, WikiLeaks, working poor, Yochai Benkler, zero-sum game, Zipcar

John Markoff, “Skilled Work, without the Worker,” New York Times, August 18, 2012, http://www.nytimes.com/2012/08/19/business/new-wave-of-adept-robots-is-changing-global-indus try.html?pagewanted=all&_r=0 (accessed July 1, 2013). 16. Ibid. 17. “World Robotics 2012 Industrial Robots,” International Federation of Robotics, http://www.ifr .org/industrial-robots/statistics/ (accessed May 26, 2013). 18. Russell Roberts, “Obama vs. ATMs: Why Technology Doesn’t Destroy Jobs,” Wall Street Journal, June 22, 2011, http://online.wsj.com/article/SB10001424052702304070104576399704275 939640.html (accessed May 26, 2013). 19.

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The ground plastic is then fed into a hopper and into a barrel where it is melted down by a heating coil. The molten plastic then travels through nozzles and is sent through sizing rollers to create plastic filaments which are stored on a spool for printing. An assembled Filabot costs $649.18 A Dutch student, Dirk Vander Kooij, reprogrammed an industrial robot to print customized furniture in a continuous line using plastic material from old refrigerators. The robot can print out a chair in multiple colors and designs in less than three hours. His 3D printer can turn out 4,000 customized chairs a year.19 Other printers of furniture are using recycled glass, wood, fabrics, ceramics, and even stainless steel as feedstock, demonstrating the versatility in recycled feedstocks that can be employed in the new infofacturing process.

Gods and Robots: Myths, Machines, and Ancient Dreams of Technology by Adrienne Mayor

AlphaGo, Any sufficiently advanced technology is indistinguishable from magic, Asilomar, autonomous vehicles, caloric restriction, caloric restriction, classic study, deep learning, driverless car, Elon Musk, industrial robot, Islamic Golden Age, Jacquard loom, life extension, Menlo Park, Nick Bostrom, Panopticon Jeremy Bentham, popular electronics, self-driving car, Silicon Valley, Stephen Hawking, Thales and the olive presses, Thales of Miletus, theory of mind, TikTok, Turing test

Among the thaumata, “wonders,” were tripodes de automatoi and automated cupbearers that attended royal banquets. As many modern historians have remarked, the self-moving tripods serving the Olympian gods call to mind modern self-propelled, laborsaving machines, driverless cars, and military-industrial robots. Homer’s myth reminds us that the impulse to “automate” is extremely ancient.20 Wheeled tripods do not appear in surviving ancient Greek art, and archaeological examples are unknown. However, many ornately decorated four-wheeled bronze carts for transporting cauldrons have been excavated in Mediterranean sites, dating to the Bronze Age (thirteenth to twelfth century BC).

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“If every tool could perform its own work when ordered to do so or in anticipation of the need, like the statues of Daedalus or the tripods of Hephaestus, which the poet tells us could of their own accord move into the assembly of the gods,” and “if in the same manner, shuttles could weave and picks could play kitharas (stringed lyres) by themselves, then craftsmen would have no need of servants and masters would have no need of slaves.”39 Today, the ancient speculative fantasy that machines could free many workers from drudgery and replace slaves has become a commonplace reality in many parts of the world. Ironically, however, industrial robotics technologies now threaten to abolish human wage earners’ livelihoods, leaving masses of idle, unpaid workers. Meanwhile, dystopian science fictions paint nightmarish scenarios of a new, rising “servile class” of automaton-slaves that ultimately will rebel. The idea that creations of superior masters might revolt against their makers is also quite ancient.

The Meritocracy Trap: How America's Foundational Myth Feeds Inequality, Dismantles the Middle Class, and Devours the Elite by Daniel Markovits

8-hour work day, activist fund / activist shareholder / activist investor, affirmative action, algorithmic management, Amazon Robotics, Anton Chekhov, asset-backed security, assortative mating, basic income, Bernie Sanders, big-box store, business cycle, capital asset pricing model, Capital in the Twenty-First Century by Thomas Piketty, Carl Icahn, carried interest, collateralized debt obligation, collective bargaining, compensation consultant, computer age, corporate governance, corporate raider, crony capitalism, David Brooks, deskilling, Detroit bankruptcy, disruptive innovation, Donald Trump, Edward Glaeser, Emanuel Derman, equity premium, European colonialism, everywhere but in the productivity statistics, fear of failure, financial engineering, financial innovation, financial intermediation, fixed income, Ford paid five dollars a day, Frederick Winslow Taylor, fulfillment center, full employment, future of work, gender pay gap, gentrification, George Akerlof, Gini coefficient, glass ceiling, Glass-Steagall Act, Greenspan put, helicopter parent, Herbert Marcuse, high net worth, hiring and firing, income inequality, industrial robot, interchangeable parts, invention of agriculture, Jaron Lanier, Jeff Bezos, job automation, job satisfaction, John Maynard Keynes: Economic Possibilities for our Grandchildren, junk bonds, Kevin Roose, Kiva Systems, knowledge economy, knowledge worker, Kodak vs Instagram, labor-force participation, Larry Ellison, longitudinal study, low interest rates, low skilled workers, machine readable, manufacturing employment, Mark Zuckerberg, Martin Wolf, mass incarceration, medical residency, meritocracy, minimum wage unemployment, Myron Scholes, Nate Silver, New Economic Geography, new economy, offshore financial centre, opioid epidemic / opioid crisis, Paul Samuelson, payday loans, plutocrats, Plutonomy: Buying Luxury, Explaining Global Imbalances, precariat, purchasing power parity, rent-seeking, Richard Florida, Robert Gordon, Robert Shiller, Robert Solow, Ronald Reagan, Rutger Bregman, savings glut, school choice, shareholder value, Silicon Valley, Simon Kuznets, six sigma, Skype, stakhanovite, stem cell, Stephen Fry, Steve Jobs, stock buybacks, supply-chain management, telemarketer, The Bell Curve by Richard Herrnstein and Charles Murray, The Theory of the Leisure Class by Thorstein Veblen, Thomas Davenport, Thorstein Veblen, too big to fail, total factor productivity, transaction costs, traveling salesman, universal basic income, unpaid internship, Vanguard fund, War on Poverty, warehouse robotics, Winter of Discontent, women in the workforce, work culture , working poor, Yochai Benkler, young professional, zero-sum game

See also Waters and Inagaki, “Investment Surge,” reporting study by economic research group IDC. in Europe and Asia: See International Federation of Robotics, World Robotics Report 2016, September 29, 2016, Figure 2.9, https://ifr.org/ifr-press-releases/news/world-robotics-report-2016, and James Carroll, “Industrial Robots in the United States on the Rise,” Vision Systems Design, September 6, 2016, www.vision-systems.com/articles/2016/12/industrial-robots-in-the-united-states-on-the-rise.html. since the late 1970s: Total manufacturing employment peaked in the late 1970s, when roughly 19.5 million Americans held manufacturing jobs. See, e.g., Martin Neil Baily and Barry P.

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Over the past forty years, computers, robots, and other new technologies have changed how goods are made and services delivered. These disruptive technologies (invented by interested innovators and tailored to suit skills that meritocratic education makes newly available) shift the center of production away from mid-skilled and toward super-skilled labor. Automated industrial robots, for example, replace mid-skilled manufacturing workers with super-skilled workers who design and program the robots. Innovations in distribution, warehousing, and e-commerce displace middle-class independent merchants with subordinate Walmart greeters and Amazon warehouse workers at the bottom, and super-rich owners of megastores—including the world’s richest family (the Waltons of Walmart) and the world’s richest person (Jeff Bezos of Amazon)—at the very top.

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Manning, “Dean’s Welcome,” Harvard Law School, 2018, accessed June 6, 2018, https://hls.harvard.edu/about/deans-welcome/. “quite simply, the finest”: Robert Post, “Yale Law School Graduation Speech,” May 18, 2015, accessed June 6, 2018, https://law.yale.edu/system/files/area/department/studentaffairs/document/postspeech.pdf. Automated industrial robots: See Chapter 6. Innovations in distribution: See Chapter 6. Derivatives and other new financial technologies: See Chapter 6. And new management techniques: See Chapter 6. “there are . . . approximately”: American Bar Association Committee on Economics of Law Practice, The Lawyer’s Handbook (St.

Trust: The Social Virtue and the Creation of Prosperity by Francis Fukuyama

Alvin Toffler, barriers to entry, Berlin Wall, blue-collar work, business climate, business cycle, capital controls, classic study, collective bargaining, corporate governance, corporate raider, creative destruction, deindustrialization, Deng Xiaoping, deskilling, double entry bookkeeping, equal pay for equal work, European colonialism, Francis Fukuyama: the end of history, Frederick Winslow Taylor, full employment, George Gilder, glass ceiling, Glass-Steagall Act, global village, Gunnar Myrdal, hiring and firing, industrial robot, Jane Jacobs, job satisfaction, joint-stock company, joint-stock limited liability company, Joseph Schumpeter, Kanban, Kenneth Arrow, land reform, liberal capitalism, liberation theology, low skilled workers, manufacturing employment, mittelstand, price mechanism, profit maximization, RAND corporation, rent-seeking, Ronald Coase, scientific management, Silicon Valley, Steve Jobs, Steve Wozniak, The Death and Life of Great American Cities, The Nature of the Firm, the scientific method, The Wealth of Nations by Adam Smith, transaction costs, transfer pricing, traveling salesman, union organizing, vertical integration, W. E. B. Du Bois

Despite the large aggregate output, the production runs of the Emilian machine tool industry tend to be very low, often amounting to a single, custom- designed machine.17 Other highly competitive products from the Terza Italia include textiles and apparel, furniture, farm machinery, other sorts of advanced capital goods such as shoemaking equipment and industrial robots, high-quality ceramics, and ceramic tile. This confirms that there is no necessary connection between small-scale industry and technological backwardness. Italy is the world’s third-largest producer of industrial robots, and yet a third of that industry’s output is produced by enterprises with fewer than fifty employees.18 Italy has in many ways become the center of the European fashion industry, with many labels shifting there from France in the 1960s and 1970s.

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CHAPTER 10 Italian Confucianism Over the past decade and a half, one of the most interesting new economic phenomena to be studied by business schools and management experts has been small-scale industry in central Italy. Italy, which industrialized late and has usually been regarded as one of Western Europe’s economic backwaters, saw certain regions explode in the 1970s and 1980s with the emergence of networks of small businesses making everything from textiles and designer clothes to machine tools and industrial robots. Some enthusiasts of small-scale industrialization have argued that the Italian model represents an entirely new paradigm of industrial production, one that can be exported to other countries. Social capital and culture give us considerable insight into the reasons for this miniature economic renaissance.

Future Files: A Brief History of the Next 50 Years by Richard Watson

Abraham Maslow, Albert Einstein, bank run, banking crisis, battle of ideas, Black Swan, call centre, carbon credits, carbon footprint, carbon tax, cashless society, citizen journalism, commoditize, computer age, computer vision, congestion charging, corporate governance, corporate social responsibility, deglobalization, digital Maoism, digital nomad, disintermediation, driverless car, epigenetics, failed state, financial innovation, Firefox, food miles, Ford Model T, future of work, Future Shock, global pandemic, global supply chain, global village, hive mind, hobby farmer, industrial robot, invention of the telegraph, Jaron Lanier, Jeff Bezos, knowledge economy, lateral thinking, linked data, low cost airline, low skilled workers, M-Pesa, mass immigration, Northern Rock, Paradox of Choice, peak oil, pensions crisis, precautionary principle, precision agriculture, prediction markets, Ralph Nader, Ray Kurzweil, rent control, RFID, Richard Florida, self-driving car, speech recognition, synthetic biology, telepresence, the scientific method, The Wisdom of Crowds, Thomas Kuhn: the structure of scientific revolutions, Turing test, Victor Gruen, Virgin Galactic, white flight, women in the workforce, work culture , Zipcar

First, the cost of computing power (processing and storage) is dropping fast. Second, distributed computing, voice and visual-recognition technologies and wireless broadband connectivity are similarly becoming cheaper and more available. Personal robots will be cleaning floors, dispensing medicine and keeping an eye open for intruders, while industrial robots will operate dangerous machinery and handle hazardous materials. On a smaller scale, robots could carry our bags from the supermarket, work as guide dogs for the visually impaired, or replace care workers in hospitals or nursing homes. Whether a machine will ever fully replace human or animal contact is a big question, to which most people currently answer no.

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A 311 Index ‘O’ Garage 170 3D printers 56 accelerated education 57 accidents 159, 161–6, 173, 246 ACNielsen 126 adaptive cruise control 165 Adeg Aktiv 50+ 208 advertising 115–16, 117, 119 Africa 70, 89, 129, 174, 221, 245, 270, 275, 290, 301 ageing 1, 10, 54, 69, 93, 139, 147–8, 164, 188, 202, 208, 221, 228–9, 237, 239, 251, 261, 292, 295, 297–8 airborne networks 56 airlines 272 allergies 196–7, 234, 236 Alliance Against Urban 4x4s 171 alternative energy 173 alternative futures viii alternative medicine 244–5 alternative technology 151 amateur production 111–12 Amazon 32, 113–14, 121 American Apparel 207 American Express 127–8 androids 55 Angola 77 anti-ageing drugs 231, 237 anti-ageing foods 188 anti-ageing surgery 2, 237 antibiotics 251 anxiety 10, 16, 30, 32, 36, 37, 128, 149, 179, 184, 197, 199, 225, 228, 243, 251, 252, 256, 263, 283–4, 295–6, 300, 301, 305 Apple 61, 115, 121, 130, 137–8, 157 Appleyard, Bryan 79 Argentina 210 Armamark Corporation 193 artificial intelliegence 22, 40, 44, 82 131, 275, 285–6, 297, 300 Asda 136, 137 Asia 11, 70, 78, 89, 129, 150, 174, 221, 280, 290, 292 Asimov, Isaac 44 Asos.com 216 asthma 235 auditory display software 29 Australia 20–21, 72–3, 76, 92, 121, 145, 196, 242, 246, 250, 270, 282 Austria 208 authenticity 32, 37, 179, 194, 203–11 authoritarianism 94 automated publishing machine (APM) 114 automation 292 automotive industry 154–77 B&Q 279 baby boomers 41, 208 bacterial factories 56 Bahney, Anna 145 Bahrain 2 baking 27, 179, 195, 199 Bangladesh 2 bank accounts, body double 132 banknotes 29, 128 banks 22, 123, 135–8, 150, 151 virtual 134 Barnes and Noble 114 bartering 151 BBC 25, 119 Become 207 Belgium 238 313 314 benriya 28 Berlusconi, Silvio 92 Best Buy 223 biofuel 64 biomechatronics 56 biometric identification 28, 35, 52, 68, 88, 132 bionic body parts 55 Biosphere Expeditions 259 biotechnology 40, 300 blended families 20 blogs 103, 107, 109, 120 Blurb 113 BMW 289 board games 225 body double bank accounts 132 body parts bionic 55 replacement 2, 188, 228 Bolivia 73 Bollywood 111 books 29, 105, 111–25 boomerang kids 145 brain transplants 231 brain-enhancing foods 188 Brazil 2, 84, 89, 173, 247, 254, 270, 290 Burger King 184 business 13, 275–92 Bust-Up 189 busyness 27, 195, 277 Calvin, Bill 45 Canada 63, 78, 240 cancer 251 car sharing 160, 169, 176 carbon credits 173 carbon footprints 255 carbon taxes 76, 172 cars classic 168–9 driverless 154–5 flying 156, 165 hydrogen-powered 12, 31, 157, 173 pay-as-you-go 167–8 self-driving 165 cascading failure 28 cash 126–7, 205 cellphone payments 129, 213 cellphones 3, 25, 35, 51, 53, 120, 121, FUTURE FILES 129, 156, 161, 251 chicken, Christian 192 childcare robots 57 childhood 27, 33–4, 82–3 children’s database 86 CHIME nations (China, India, Middle East) 2, 10, 81 China 2, 10, 11, 69–72, 75–81, 88, 92–3, 125, 137, 139–40, 142, 151, 163, 174–5, 176, 200, 222, 228, 247, 260, 270–71, 275, 279, 295, 302 choice 186–7 Christian chicken 192 Christianity, muscular 16, 73 Chrysler 176 cinema 110–11, 120 Citibank 29, 128 citizen journalism 103–4, 108 City Car Club 168 Clarke, Arthur C. 58–9 Clarke’s 187 classic cars 168–9 climate change 4, 11, 37, 43, 59, 64, 68, 74, 77–9, 93, 150, 155, 254, 257, 264, 298–9 climate-controlled buildings 254, 264 cloning 38 human 23, 249 CNN 119 coal 176 Coca-Cola 78, 222–3 co-creation 111–12, 119 coins 29, 128, 129 collective intelligence 45–6 Collins, Jim 288 comfort eating 200 Comme des Garçons 216 community 36 compassion 120 competition in financial services 124–5 low-cost 292 computers disposable 56 intelligent 23, 43 organic 56 wearable 56, 302 computing 3, 33, 43, 48, 82 connectivity 3, 10, 11, 15, 91, 120, Index 233, 261, 275–6, 281, 292, 297, 299 conscientious objection taxation 86 contactless payments 123, 150 continuous partial attention 53 control 36, 151, 225 convenience 123, 178–9, 184, 189, 212, 223, 224 Coren, Stanley 246 corporate social responsibility 276, 282, 298 cosmetic neurology 250 Costa Rica 247 Craig’s List 102 creativity 11, 286; see also innovation credit cards 141–3, 150 crime 86–9 forecasting 86–7 gene 57, 86 Croatia 200 Crowdstorm 207 Cuba 75 cultural holidays 259, 273 culture 11, 17–37 currency, global 127, 151 customization 56, 169, 221–2, 260 cyberterrorism 65, 88–9 Cyc 45 cynicism 37 DayJet 262 death 237–9 debt 123–4, 140–44, 150 defense 63, 86 deflation 139 democracy 94 democratization of media 104, 108, 113 demographics 1, 10, 21, 69, 82, 93, 202, 276, 279–81, 292, 297–8 Denmark 245 department stores 214 deregulation 11, 3 Destiny Health 149 detox 200 Detroit Project 171 diagnosis 232 remote 228 digital downloads 121 evaporation 25 315 immortality 24–5 instant gratification syndrome 202 Maoism 47 money 12, 29, 123, 126–7, 129, 132, 138, 150, 191 nomads 20, 283 plasters 241 privacy 25, 97, 108 readers 121 digitalization 37, 292 Dinner by Design 185 dirt holidays 236 discount retailers 224 Discovery Health 149 diseases 2, 228 disintegrators 57 Disney 118–19 disposable computers 56 divorce 33, 85 DNA 56–7, 182 database 86 testing, compulsory 86 do-it-yourself dinner shops 185–6 dolls 24 doorbells 32 downshifters 20 Dream Dinners 185 dream fulfillment 148 dressmaking 225 drink 178–200 driverless cars 154–5 drugs anti-ageing 231, 237 performance-improving 284–5 Dubai 264, 267, 273 dynamic pricing 260 E Ink 115 e-action 65 Earthwatch 259 Eastern Europe 290 eBay 207 e-books 29, 37, 60, 114, 115, 302 eco-luxe resorts 272 economic collapse 2, 4, 36, 72, 221, 295 economic protectionism 10, 15, 72, 298 economy travel 272 316 Ecuador 73 education 15, 18, 82–5, 297 accelerated 57 lifelong learning 290 Egypt 2 electricity shortages 301 electronic camouflage 56 electronic surveillance 35 Elephant 244 email 18–19, 25, 53–4, 108 embedded intelligence 53, 154 EMF radiation 251 emotional capacity of robots 40, 60 enclosed resorts 273 energy 72, 75, 93 alternative 173 nuclear 74 solar 74 wind 74 enhancement surgery 249 entertainment 34, 121 environment 4, 10, 11, 14, 64, 75–6, 83, 93, 155, 171, 173, 183, 199, 219–20, 252, 256–7, 271, 292, 301 epigenetics 57 escapism 16, 32–3, 121 Estonia 85, 89 e-tagging 129–30 e-therapy 242 ethical bankruptcy 35 ethical investing 281 ethical tourism 259 ethics 22, 24, 41, 53, 78, 86, 132, 152, 194, 203, 213, 232, 238, 249–50, 258, 276, 281–2, 298–9 eugenics 252 Europe 11, 70, 72, 81, 91, 141, 150, 174–5, 182, 190, 192, 209 European Union 15, 139 euthanasia 238, 251 Everquest 33 e-voting 65 experience 224 extended financial families 144 extinction timeline 9 Facebook 37, 97, 107 face-recognition doors 57 fakes 32 family 36, 37 FUTURE FILES family loans 145 fantasy-related industries 32 farmaceuticals 179, 182 fast food 178, 183–4 fat taxes 190 fear 10, 34, 36, 38, 68, 150, 151, 305 female-only spaces 210–11, 257 feminization 84 financial crisis 38, 150–51, 223, 226, 301 financial services 123–53, 252 trends 123–5 fish farming 181 fixed-price eating 200 flashpacking 273 flat-tax system 85–6 Florida, Richard 36, 286, 292 flying cars 165 food 69–70, 72, 78–9, 162, 178–201 food anti-ageing 188 brain-enhancing 188 fast 178, 183–4 functional 179 growing your own 179, 192, 195 history 190–92 passports 200 slow 178, 193 tourism 273 trends 178–80 FoodExpert ID 182 food-miles 178, 193, 220 Ford 169, 176, 213, 279–80 forecasting 49 crime 86–7 war 49 Forrester Research 132 fractional ownership 168, 175, 176, 225 France 103, 147, 170, 189, 198, 267 Friedman, Thomas 278–9, 292 FriendFinder 32 Friends Reunited 22 frugality 224 functional food 179 Furedi, Frank 68 gaming 32–3, 70, 97, 111–12, 117, 130, 166, 262 Gap 217 Index gardening 27, 148 gas 176 GE Money 138, 145 gendered medicine 244–5 gene silencing 231 gene, crime 86 General Motors 157, 165 Generation X 41, 281 Generation Y 37, 41, 97, 106, 138, 141–2, 144, 202, 208, 276, 281, 292 generational power shifts 292 Genes Reunited 35 genetic enhancement 40, 48 history 35 modification 31, 182 testing 221 genetics 3, 10, 45, 251–2 genomic medicine 231 Germany 73, 147, 160, 170, 204–5, 216–17, 261, 267, 279, 291 Gimzewski, James 232 glamping 273 global currency 127 global warming 4, 47, 77, 93, 193, 234 globalization 3, 10, 15–16, 36–7, 63–7, 72–3, 75, 81–2, 88, 100, 125, 139, 143, 146, 170, 183, 189, 193–5, 221, 224, 226, 233–4, 247–8, 263, 275, 278–80, 292, 296, 299 GM 176 Google 22, 61, 121, 137, 293 gout 235 government 14, 18, 36, 63–95, 151 GPS 3, 15, 26, 50, 88, 138, 148, 209, 237, 262, 283 Grameen Bank 135 gravity tubes 57 green taxes 76 Greenpeace 172 GRIN technologies (genetics, robotics, internet, nanotechnology) 3, 10, 11 growing your own food 178, 192, 195 Gucci 221 Gulf States 125, 260, 268 H&M 217 habitual shopping 212 Handy, Charles 278 317 Happily 210 happiness 63–4, 71–2, 146, 260 health 15, 82, 178–9, 199 health monitoring 232, 236, 241 healthcare 2, 136, 144, 147–8, 154, 178–9, 183–4, 189–91, 228–53, 298; see also medicine trends 214–1534–7 Heinberg, Richard 74 Helm, Dieter 77 Heritage Foods 195 hikikomori 18 hive mind 45 holidays 31, 119; see also tourism holidays at home 255 cultural 259 dirt 236 Hollywood 33, 111–12 holographic displays 56 Home Equity Share 145 home baking 225 home-based microgeneration 64 home brewing 225 honesty 152 Hong Kong 267 hospitals 228, 241–3, 266 at home 228, 238, 240–42 hotels 19, 267 sleep 266 human cloning 23, 249 Hungary 247 hybrid humans 22 hydrogen power 64 hydrogen-powered cars 12, 31, 157, 173 Hyperactive Technologies 184 Hyundai 170 IBM 293 identities, multiple 35, 52 identity 64, 71 identity theft 88, 132 identity verification, two-way 132 immigration 151–2, 302 India 2, 10, 11, 70–72, 76, 78–9, 81, 92, 111, 125, 135, 139, 163, 174–5, 176, 247, 249–50, 254, 260, 270, 275, 279, 302 indirect taxation 86 318 individualism 36 Indonesia 2, 174 industrial robots 42 infinite content 96–7 inflation 151 information overlead 97, 120, 159, 285; see also too much information innovation 64, 81–2, 100, 175, 222, 238, 269, 277, 286–8, 291, 297, 299 innovation timeline 8 instant gratification 213 insurance 123, 138, 147–50, 154, 167, 191, 236, 250 pay-as-you-go 167 weather 264 intelligence 11 embedded 53, 154 implants 229 intelligent computers 23, 43 intelligent night vision 162–3 interaction, physical 22, 25, 97, 110, 118, 133–4, 215, 228, 243, 276, 304 interactive media 97, 105 intergenerational mortgages 140, 144–5 intermediaries 123, 135 internet 3, 10, 11, 17–18, 25, 68, 103, 108, 115–17, 124, 156, 240–41, 261, 270, 283, 289, 305 failure 301 impact on politics 93–4 sensory 56 interruption science 53 iPills 240 Iran 2, 69 Ishiguro, Hiroshi 55 Islamic fanaticism 16 Italy 92, 170, 198–9 iTunes 115, 130; see also Apple Japan 1, 18, 26, 28–9, 54–5, 63, 80–81, 114, 121, 128–9, 132, 140, 144–5, 147, 174, 186, 189, 192, 196, 198, 200, 209–10, 223, 240, 260, 264, 271, 279, 291 jetpacks 60 job security 292 journalism 96, 118 journalism, citizen 103–4, 107 joy-makers 57 FUTURE FILES Kaboodle 207 Kapor, Mitchell 45 Kenya 128 keys 28–9 Kindle 60, 121 Kramer, Peter 284 Kuhn, Thomas 281 Kurzweil, Ray 45 Kuwait 2 labor migration 290–91 labor shortages 3, 80–81, 289–90 Lanier, Jaron 47 laser shopping 212 leisure sickness 238 Let’s Dish 185 Lexus 157 libraries 121 Libya 73 life-caching 24, 107–8 lighting 158, 160 Like.com 216 limb farms 249 limited editions 216–17 live events 98, 110, 304 localization 10, 15–16, 116, 128, 170, 178, 189, 193, 195, 215, 220, 222–3, 224, 226, 255, 270, 297 location tagging 88 location-based marketing 116 longevity 188–9, 202 Longman, Philip 71 low cost 202, 219–22 luxury 202, 221, 225, 256, 260, 262, 265–6, 272 machinamas 112 machine-to-machine communication 56 marketing 115–16 location-based 116 now 116 prediction 116 Marks & Spencer 210 Maslow, Abraham 305–6 masstigue 223 materialism 37 Mayo Clinic 243 McDonald’s 130, 168, 180, 184 McKinsey 287 Index meaning, search for 16, 259, 282, 290, 305–6 MECU 132 media 96–122 democratization of 104, 108, 115 trends 96–8 medical outsourcing 247–8 medical tourism 2, 229, 247 medicine 188, 228–53; see also healthcare alternative 243–4 gendered 244–5 genomic 231 memory 229, 232, 239–40 memory loss 47 memory pills 231, 240 memory recovery 2, 228–9, 239 memory removal 29–30, 29, 240 Menicon 240 mental health 199 Meow Mix 216 Merriman, Jon 126 metabolomics 56 meta-materials 56 Metro 204–5 Mexico 2 micromedia 101 micro-payments 130, 150 Microsoft 137, 147, 293 Middle East 10, 11, 70, 81, 89, 119, 125, 129, 139, 174–5, 268, 301 migration 3, 11, 69–70, 78, 82, 234, 275, 290–91 boomerang 20 labor 290–91 Migros 215 military recruitment 69 military vehicles 158–9 mind-control toys 38 mindwipes 57 Mitsubishi 198, 279 mobile payments 123, 150 Modafinil 232 molecular biology 231 monetization 118 money 123–52 digital 12, 29, 123, 126–7, 129, 132, 138, 150, 191 monitoring, remote 154, 168, 228, 242 monolines 135, 137 319 mood sensitivity 41, 49, 154, 158, 164, 187–8 Morgan Stanley 127 mortality bonds 148 Mozilla Corp. 289 M-PESA 129 MTV 103 multigenerational families 20 multiple identities 35, 52 Murdoch, Rupert 109 muscular Christianity 16, 73 music industry 121 My-Food-Phone 242 MySpace 22, 25, 37, 46, 97, 107, 113 N11 nations (Bangladesh, Egypt, Indonesia, Iran, South Korea, Mexico, Nigeria, Pakistan, Philippines, Turkey, Vietnam) 2 nanoelectronics 56 nanomedicine 32 nanotechnology 3, 10, 23, 40, 44–5, 50, 157, 183, 232, 243, 286, 298 napcaps 56 narrowcasting 109 NASA 25, 53 nationalism 16, 70, 72–3, 139, 183, 298, 302 natural disasters 301 natural resources 2, 4, 11, 64, 298–9 Nearbynow 223 Nestlé 195 Netherlands 238 NetIntelligence 283 networkcar.com 154 networks 28, 166, 288 airborne 56 neural nets 49 neuronic whips 57 neuroscience 33, 48 Neville, Richard 58–9 New Economics Foundation 171 New Zealand 265, 269 newspapers 29, 102–9, 117, 119, 120 Nigeria 2, 73 Nike 23 nimbyism 63 no-frills 224 Nokia 61, 105 Norelift 189 320 Northern Rock 139–40 Norwich Union 167 nostalgia 16, 31–2, 51, 169–70, 179, 183, 199, 203, 225, 303 now marketing 116 nuclear annihilation 10, 91 nuclear energy 74 nutraceuticals 179, 182 Obama, Barack 92–3 obesity 75, 190–92, 199, 250–51 oceanic thermal converters 57 oil 69, 72–3, 93, 151, 174, 176, 272, 273, 301 Oman 2, 270 online relationships 38 organic computers 56 organic food 200, 226 osteoporosis 235 outsourcing 224, 292 Pakistan 2 pandemics 4, 10, 16, 59, 72, 128, 232, 234, 272, 295–7, 301 paper 37 parasite singles 145 passwords 52 pictorial 52 pathogens 233 patient simulators 247 patina 31 patriotism 63, 67, 299 pay-as-you-go cars 167–8 pay-as-you-go insurance 167 payments cellphone 129, 213 contactless 123, 150 micro- 130, 150 mobile 123, 150 pre- 123, 150 PayPal 124, 137 Pearson, Ian 44 performance-improving drugs 284–5 personal restraint 36 personal robots 42 personalization 19, 26, 56, 96–8, 100, 102–3, 106, 108–9, 120, 138, 149, 183, 205–6, 223, 244–5, 262, 267, 269 Peru 73 FUTURE FILES Peters, Tom 280 Pharmaca 244 pharmaceuticals 2, 33, 228, 237 Philippines 2, 212, 290 Philips 114 Philips, Michael 232–3 photographs 108 physical interaction 22, 25, 97, 110, 118, 133–4, 215, 228, 243, 276, 304 physicalization 96–7, 101–2, 106, 110, 120 pictorial passwords 52 piggy banks 151 Pink, Daniel 285 plagiarism 83 polarization 15–16, 285 politics 37, 63–95, 151–2 regional 63 trends 63–5 pop-up retail 216, 224 pornography 31 portability 178, 183–4 power shift eastwards 2, 10–11, 81, 252 Prada 205–6, 216 precision agriculture 181–2 precision healthcare 234–7 prediction marketing 116 predictions 37, 301–2 premiumization 223 pre-payments 123, 150 privacy 3, 15, 41, 50, 88, 154, 165–7, 205, 236, 249, 285, 295 digital 25, 97, 108 Procter & Gamble 105, 280 product sourcing 224 Prosper 124, 135 protectionism 67, 139, 156, 220, 226, 301 economic 10, 15, 72, 299 provenance 178, 193, 226 proximity indicators 32 PruHealth 149 psychological neoteny 52 public ownership 92 public transport 171 purposeful shopping 212 Qatar 2 quality 96–7, 98, 101, 109 Index quantum mechanics 56 quantum wires 56 quiet materials 56 radiation, EMF 251 radio 117 randominoes 57 ranking 34, 83, 109, 116, 134, 207 Ranking Ranqueen 186 reality mining 51 Really Cool Foods 185 rebalancing 37 recession 139–40, 202, 222 recognition 36, 304 refrigerators 197–8 refuge 121 regeneration 233 regional food 200 regional politics 63 regionality 178, 192–3 regulation 124, 137, 143 REI 207 Reid, Morris 90 relationships, online 38 religion 16, 58 remote diagnosis 228 remote monitoring 154, 168, 228, 242 renting 225 reputation 34–5 resistance to technology 51 resorts, enclosed 273 resource shortages 11, 15, 146, 155, 178, 194, 254, 300 resources, natural 2, 4, 11, 64, 73–4, 143, 298–9 respect 36, 304 restaurants 186–8 retail 20–21, 202–27, 298 pop-up 216, 224 stealth 215 theater 214 trends 202–3 Revkin, Andy 77 RFID 3, 24, 50, 121, 126, 149, 182, 185, 192, 196, 205 rickets 232 risk 15, 124, 134, 138, 141, 149–50, 162, 167, 172, 191, 265, 299–300, 303 Ritalin 232 321 road pricing 166 Robertson, Peter 49 robogoats 55 robot department store 209 Robot Rules 44 robotic assistants 54, 206 concierges 268 financial advisers 131–2 lobsters 55 pest control 57 soldiers 41, 55, 60 surgery 35, 41, 249 robotics 3, 10, 41, 44–5, 60, 238, 275, 285–6, 292, 297 robots 41, 54–5, 131, 237, 249 childcare 57 emotional capacity of 40, 60 industrial 42 personal 42 security 209 therapeutic 41, 54 Russia 2, 69, 72, 75, 80, 89, 92–3, 125, 174, 232, 254, 270, 295, 302 safety 32, 36, 151, 158–9, 172–3, 182, 192, 196 Sainsbury’s 215 Salt 187 sanctuary tourism 273 satellite tracking 166–7 Saudi Arabia 2, 69 Schwartz, Barry 186 science 13, 16, 40–62, 300 interruption 53 trends 40–42 scramble suits 57 scrapbooking 25, 108, 225 Sears Roebuck 137 seasonality 178, 193–4 second-hand goods 224 Second Life 133, 207–8 securitization 124, 140 security 16, 31, 151 security robots 209 self-driving cars 165 self-medication 242 self-publishing 103, 113–14 self-reliance 35, 75 self-repairing roads 57 322 self-replicating machines 23, 44 Selfridges 214 sensor motes 15, 50, 196 sensory internet 56 Sharia-based investment 125 Shop24 209 shopping 202–27 habitual 212 laser 212 malls 211–5 purposeful 212 slow 213 social 207 Shopping 2.0 224 short-wave scalpels 57 silicon photonics 56 simplicity 169–70, 179, 186, 202, 218, 224, 226, 272 Singapore 241 single-person households 19–20, 202–3, 208–9, 221, 244, 298, 304 skills shortage 293, 302 sky shields 57 sleep 159–60, 188, 228, 231, 246–7, 265 sleep debt 96, 266 sleep hotels 266 sleep surrogates 57 slow food 178, 193 slow shopping 213 slow travel 273 smart devices 26–7, 28, 32, 35, 44, 50, 56, 57, 164, 206, 207 smart dust 3, 15, 50, 196 smartisans 20 Smartmart 209 snakebots 55 social networks 97, 107, 110, 120, 133, 217, 261 social shopping 207 society 13, 15–16, 17–37 trends 15–16 Sodexho 193 solar energy 74 Sony 114, 121 South Africa 84, 149, 242 South America 82, 270 South Korea 2, 103, 128–9 space ladders 56 space mirrors 47 space tourism 271, 273 FUTURE FILES space tugs 57 speed 164, 202, 209, 245, 296–7 spirituality 16, 22, 282, 298, 306 spot knowledge 47 spray-on surgical gloves 57 St James’s Ethics Centre 282 stagflation 139 starch-based plastics 64 stealth retail 215 stealth taxation 86 Sterling, Bruce 55 storytelling 203 Strayer, David 161 street signs 162–3 stress 32, 96, 235, 243, 245–6, 258–9, 265, 257–9, 275, 277, 283–5 stress-control clothing 57 stupidity 151, 302 Stylehive 207 Sudan 73 suicide tourism 236 Super Suppers 185 supermarkets 135–6, 184–6, 188, 191–2, 194, 202–3, 212, 215, 218–19, 224, 229 surgery 2, 31 anti-ageing 2, 237 enhancement 249 Surowiecki, James 45 surveillance 35, 41 sustainability 4, 37, 74, 181, 193–5, 203, 281, 288, 298–9 Sweden 84 swine flu 38, 251, 272 Switzerland 168, 210, 215 synthetic biology 56 Taco Bell 184 Tactical Numerical Deterministic Model 49 tagging, location 86, 88 Taiwan 81 talent, war for 275, 279, 293; see also labor shortages Target 216 Tasmania 267 Tata Motors 174, 176 taxation 85–6, 92, 93 carbon 76, 172 conscientious objection 86 Index fat 190 flat 85–6 green 76 indirect 86 stealth 86 Tchibo 217 technology 3, 14–16, 18, 22, 26, 28, 32, 37, 40–62, 74–5, 82–3, 96, 119, 132, 147–8, 154, 157, 160, 162, 165–7, 178, 182, 195–8, 208, 221, 229, 237, 242–3, 249, 256, 261, 265–6, 268, 275–6, 280, 283–4, 292, 296–7, 300 refuseniks 30, 51, 97 trends 40–42 telemedicine 228, 238, 242 telepathy 29 teleportation 56 television 21, 96, 108, 117, 119 terrorism 67, 91, 108, 150, 262–3, 267, 272, 295–6, 301 Tesco 105, 135–6, 185, 206, 215, 219, 223 Thailand 247, 290 therapeutic robots 41, 54 thermal imaging 232 things that won’t change 10, 303–6 third spaces 224 ThisNext 207 thrift 224 Tik Tok Easy Shop 209 time scarcity 30, 96, 102, 178, 184–6, 218, 255 time shifting 96, 110, 116 time stamps 50 timeline, extinction 9 timeline, innovation 8 timelines 7 tired all the time 246 tobacco industry 251 tolerance 120 too much choice (TMC) 29, 202, 218–19 too much information (TMI) 29, 51, 53, 202, 229; see also information overload tourism 254–74 cultural 273 ethical 259 food 273 323 local 273 medical 2, 229, 247 sanctuary 273 space 271, 273 suicide 238 tribal 262 Tourism Concern 259 tourist quotas 254, 271 Toyota 48–9, 157 toys, mind-control 38 traceability 195 trading down 224 transparency 3, 15, 143, 152, 276, 282, 299 transport 15, 154–77, 298 public 155, 161 trends 154–6 transumerism 223 travel 2, 3, 11, 148, 254–74 economy 272 luxury 272 slow 273 trends 254–6 trend maps 6–7 trends 1, 5–7, 10, 13 financial services 123–5 food 178–80 healthcare 228–9 media 96–8 politics 63–5 retail 202–3 science and technology 40–42 society 15–16 transport 154–6 travel 254–6 work 275–7 tribal tourism 262 tribalism 15–16, 63, 127–8, 183, 192, 220, 260 trust 82, 133, 137, 139, 143, 192, 203, 276, 282–3 tunnels 171 Turing test 45 Turing, Alan 44 Turkey 2, 200, 247 Twitter 60, 120 two-way identity verification 132 UAE 2 UFOs 58 324 UK 19–20, 72, 76, 84, 86, 90–91, 100, 102–3, 105, 128–9, 132, 137, 139–42, 147–9, 150, 163, 167–8, 170–71, 175, 185, 195–6, 199, 200, 206, 210, 214–16, 238, 259, 267–8, 278–9, 284, 288 uncertainty 16, 30, 34, 52, 172, 199, 246, 263, 300, 303 unemployment 151 Unilever 195 University of Chicago 245–6 urban rental companies 176 urbanization 11, 18–19, 78, 84, 155, 233 Uruguay 200 US 1, 11, 19–21, 23, 55–6, 63, 67, 69, 72, 75, 77, 80–83, 86, 88–90, 92, 104–5, 106, 121, 129–33, 135, 139–42, 144, 147, 149, 150, 151, 162, 167, 169–71, 174, 185, 190–3, 195, 205–6, 209, 211, 213, 216, 218, 220, 222–3, 237–8, 240–8, 250, 260, 262, 267–8, 275, 279–80, 282–4, 287, 291 user-generated content (UGC) 46, 97, 104, 289 utility 224 values 36, 152 vending machines 209 Venezuela 69, 73 verbal signatures 132 VeriChip 126 video on demand 96 Vietnam 2, 290 Vino 100 113 Virgin Atlantic 261 virtual adultery 33 banks 134 economy 130–31 protests 65 reality 70 sex 32 stores 206–8 vacations 32, 261 worlds 157, 213, 255, 261, 270, 305 Vocation Vacations 259–60 Vodafone 137 voice recognition 41 voice-based internet search 56 voicelifts 2, 237 FUTURE FILES Volkswagen 175 voluntourism 259 Volvo 164 voting 3, 68, 90–91 Walgreens 244 Wal-Mart 105, 136–7, 215, 219–20, 223, 244, 282 war 68–9, 72 war for talent 275, 279; see also labor shortages war forecasting 49 water 69–70, 74, 77–9, 199 wearable computers 55 weather 64 weather insurance 264 Web 2.0 93, 224 Weinberg, Peter 125 wellbeing 2, 183, 188, 199 white flight 20 Wikipedia 46, 60, 104 wild swimming 273 Wilson, Edward O. 74 wind energy 74 wine producers 200 wisdom of idiots 47 Wizard 145 work 275–94 trends 275–94 work/life balance 64, 71, 260, 277, 289, 293 worldphone 19 xenophobia 16, 63 YouTube 46, 103, 107, 112 Zara 216–17 Zipcar 167 Zopa 124, 134

Only Humans Need Apply: Winners and Losers in the Age of Smart Machines by Thomas H. Davenport, Julia Kirby

"World Economic Forum" Davos, AI winter, Amazon Robotics, Andy Kessler, Apollo Guidance Computer, artificial general intelligence, asset allocation, Automated Insights, autonomous vehicles, basic income, Baxter: Rethink Robotics, behavioural economics, business intelligence, business process, call centre, carbon-based life, Clayton Christensen, clockwork universe, commoditize, conceptual framework, content marketing, dark matter, data science, David Brooks, deep learning, deliberate practice, deskilling, digital map, disruptive innovation, Douglas Engelbart, driverless car, Edward Lloyd's coffeehouse, Elon Musk, Erik Brynjolfsson, estate planning, financial engineering, fixed income, flying shuttle, follow your passion, Frank Levy and Richard Murnane: The New Division of Labor, Freestyle chess, game design, general-purpose programming language, global pandemic, Google Glasses, Hans Lippershey, haute cuisine, income inequality, independent contractor, index fund, industrial robot, information retrieval, intermodal, Internet of things, inventory management, Isaac Newton, job automation, John Markoff, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, Joi Ito, Khan Academy, Kiva Systems, knowledge worker, labor-force participation, lifelogging, longitudinal study, loss aversion, machine translation, Mark Zuckerberg, Narrative Science, natural language processing, Nick Bostrom, Norbert Wiener, nuclear winter, off-the-grid, pattern recognition, performance metric, Peter Thiel, precariat, quantitative trading / quantitative finance, Ray Kurzweil, Richard Feynman, risk tolerance, Robert Shiller, robo advisor, robotic process automation, Rodney Brooks, Second Machine Age, self-driving car, Silicon Valley, six sigma, Skype, social intelligence, speech recognition, spinning jenny, statistical model, Stephen Hawking, Steve Jobs, Steve Wozniak, strong AI, superintelligent machines, supply-chain management, tacit knowledge, tech worker, TED Talk, the long tail, transaction costs, Tyler Cowen, Tyler Cowen: Great Stagnation, Watson beat the top human players on Jeopardy!, Works Progress Administration, Zipcar

At Xchanging, a process outsourcing company in the United Kingdom, the Blue Prism “robots” were given cute names like Poppy (after the poppies people wear in that country on Remembrance Day, when the machine went live) and Henry.10 The anthropomorphizing of these smart machines suggests that workers didn’t find this form of technology particularly threatening. We’ll finish our exposition of our matrix’s second column by looking at how repetitive task automation applies to the performance of physical tasks. This, of course, is what robots are all about. That’s exactly what they do—both traditional industrial robots, and the more recent collaborative robots. The only real difference is how easy it is to teach the robots new repetitive tasks, and whether they can work in close cooperation with humans or not. Because traditional robots take a lot of work to train—each movement has to be carefully specified in a vendor-specific robotics programming language such as RAPID or Karel, for example—they are well suited to highly repetitive and heavy-lifting industrial tasks that don’t change at all.

…

The lion’s share of robots today are doing dirty, dull, dangerous tasks involving things like welding and heavy material handling tasks—work that has been dangerous or difficult for humans to do, or both. A good bit of that work will continue, and it won’t be done by collaborative robots. The choice between robot types all depends on the type of application.” We expect robots to continue gaining ground in repetitive tasks. What would make them advance more quickly would be combining the industrial robots’ ability to deal with heavier work with the collaborative robots’ ease of programming. A cross-industry standard for robotics programming languages—and perhaps a popular open-source alternative—would also help to facilitate code reuse and improve productivity. Like every other kind of smart machine, robots are becoming more autonomous.

The Deep Learning Revolution (The MIT Press) by Terrence J. Sejnowski

AI winter, Albert Einstein, algorithmic bias, algorithmic trading, AlphaGo, Amazon Web Services, Any sufficiently advanced technology is indistinguishable from magic, augmented reality, autonomous vehicles, backpropagation, Baxter: Rethink Robotics, behavioural economics, bioinformatics, cellular automata, Claude Shannon: information theory, cloud computing, complexity theory, computer vision, conceptual framework, constrained optimization, Conway's Game of Life, correlation does not imply causation, crowdsourcing, Danny Hillis, data science, deep learning, DeepMind, delayed gratification, Demis Hassabis, Dennis Ritchie, discovery of DNA, Donald Trump, Douglas Engelbart, driverless car, Drosophila, Elon Musk, en.wikipedia.org, epigenetics, Flynn Effect, Frank Gehry, future of work, Geoffrey Hinton, Google Glasses, Google X / Alphabet X, Guggenheim Bilbao, Gödel, Escher, Bach, haute couture, Henri Poincaré, I think there is a world market for maybe five computers, industrial robot, informal economy, Internet of things, Isaac Newton, Jim Simons, John Conway, John Markoff, John von Neumann, language acquisition, Large Hadron Collider, machine readable, Mark Zuckerberg, Minecraft, natural language processing, Neil Armstrong, Netflix Prize, Norbert Wiener, OpenAI, orbital mechanics / astrodynamics, PageRank, pattern recognition, pneumatic tube, prediction markets, randomized controlled trial, Recombinant DNA, recommendation engine, Renaissance Technologies, Rodney Brooks, self-driving car, Silicon Valley, Silicon Valley startup, Socratic dialogue, speech recognition, statistical model, Stephen Hawking, Stuart Kauffman, theory of mind, Thomas Bayes, Thomas Kuhn: the structure of scientific revolutions, traveling salesman, Turing machine, Von Neumann architecture, Watson beat the top human players on Jeopardy!, world market for maybe five computers, X Prize, Yogi Berra

He argued that, for robots to accomplish everyday tasks, their higher cognitive abilities should be based on sensorimotor interaction with the environment, not on abstract reasoning. Elephants are highly social, have great memories, and are mechanical geniuses,13 but they don’t play chess.14 In 1990, Brooks went on to found iRobot, which has sold more than 10 million Roombas to clean even more floors. Industrial robots have stiff joints and powerful servomotors, which makes them look and feel mechanical. In 2008, Brooks started Rethink Robotics, a company that built a robot called “Baxter” with pliant joints, so its arms could be moved around (figure 12.3). Instead of having to write a program to move Baxter’s arms, each arm could be moved through the desired motions, and it would program itself to repeat the sequence of motions.

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Instead of having to write a program to move Baxter’s arms, each arm could be moved through the desired motions, and it would program itself to repeat the sequence of motions. Movellan went one step further than Brooks and developed a robot baby called “Diego San” (manufactured in Japan),15 whose motors were pneumatic (driven by air pressure) and all of whose forty-four joints were compliant compared to the stiff torque motors used in most industrial robots (figure 12.4). The motivation for making them so is that when we pick something up, every muscle in our bodies is involved to some extent (when we move only one joint at a time, we look like robots). This makes us better able to adapt to changing conditions of load and interaction with the world.

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

Abraham Maslow, agricultural Revolution, Airbnb, Albert Einstein, Alvin Toffler, Amazon Mechanical Turk, Apple's 1984 Super Bowl advert, Asperger Syndrome, Baxter: Rethink Robotics, bitcoin, blockchain, Boeing 747, business process, call centre, carbon tax, clean water, Computing Machinery and Intelligence, creative destruction, crowdsourcing, data science, deep learning, Donald Trump, Douglas Engelbart, Douglas Engelbart, driverless car, drone strike, Elon Musk, en.wikipedia.org, Erik Brynjolfsson, experimental economics, Exxon Valdez, Ford Model T, future of work, Future Shock, Galaxy Zoo, Garrett Hardin, gig economy, happiness index / gross national happiness, independent contractor, industrial robot, Internet of things, invention of the telegraph, inventory management, invisible hand, Jeff Rulifson, jimmy wales, job automation, John Markoff, Joi Ito, Joseph Schumpeter, Kenneth Arrow, knowledge worker, longitudinal study, Lyft, machine translation, Marshall McLuhan, Nick Bostrom, Occupy movement, Pareto efficiency, pattern recognition, prediction markets, price mechanism, radical decentralization, Ray Kurzweil, Rodney Brooks, Ronald Coase, search costs, Second Machine Age, self-driving car, Silicon Valley, slashdot, social intelligence, Stephen Hawking, Steve Jobs, Steven Pinker, Stewart Brand, technological singularity, The Nature of the Firm, The Wealth of Nations by Adam Smith, The Wisdom of Crowds, theory of mind, Tim Cook: Apple, Tragedy of the Commons, transaction costs, Travis Kalanick, Uber for X, uber lyft, Vernor Vinge, Vilfredo Pareto, Watson beat the top human players on Jeopardy!

For instance, if you want a robot to serve you meals, make your bed, and carry other things around in your house, you need it to be able to fit through your doorways and climb your stairs. That robot may look quite a bit like a person. Second, we may create robots that look like people just to satisfy our human desire to interact with humanlike creatures. For instance, Baxter is an industrial robot from Rethink Robotics designed to do the kind of physical tasks in factories that human workers do today. And it’s probably no accident that Baxter has a humanlike face mounted on its body between its humanlike arms, right where a human head would be. There’s no technical reason why a face or head is needed there, but presumably the designers of Baxter thought the humans in a factory would be more comfortable around a robot that sort of looked like a person.

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The photograph is from the above paper and is available online at https://tangible.media.mit.edu/project/soundform, where you can also see a fascinating video of the system in operation. Photograph © Tangible Media Group, MIT Media Lab. Reprinted with permission. 13. Erico Guizzo and Evan Ackerman, “How Rethink Robotics Built Its New Baxter Robot Worker,” IEEE Spectrum, September 18, 2012, http://spectrum.ieee.org/robotics/industrial-robots/rethink-robotics-baxter-robot-factory-worker. 14. Robert Lee Hotz, “Neural Implants Let Paralyzed Man Take a Drink,” Wall Street Journal, May 21, 2015, http://www.wsj.com/articles/neural-implants-let-paralyzed-man-take-a-drink-1432231201; Tyson Aflalo, Spencer Kellis, Christian Klaes, Brian Lee, Ying Shi, Kelsie Shanfield, Stephanie Hayes-Jackson, et al., “Decoding Motor Imagery from the Posterior Parietal Cortex of a Tetraplegic Human,” Science 348, no. 6,237 (May 22, 2015): 906–910, http://science.sciencemag.org/content/348/6237/906.full, doi:10.1126/science.aaa5417.

Radical Abundance: How a Revolution in Nanotechnology Will Change Civilization by K. Eric Drexler

3D printing, additive manufacturing, agricultural Revolution, Bill Joy: nanobots, Brownian motion, carbon footprint, Cass Sunstein, conceptual framework, continuation of politics by other means, crowdsourcing, dark matter, data science, double helix, failed state, Ford Model T, general purpose technology, global supply chain, Higgs boson, industrial robot, iterative process, Large Hadron Collider, Mars Rover, means of production, Menlo Park, mutually assured destruction, Neil Armstrong, New Journalism, Nick Bostrom, performance metric, radical decentralization, reversible computing, Richard Feynman, Silicon Valley, South China Sea, Thomas Malthus, V2 rocket, Vannevar Bush, Vision Fund, zero-sum game

To build machines that perform these motions, engineers have accumulated a kit full of design solutions, including devices like conveyor belts, rotary feeders, pick-and-place mechanisms, continuous-motion assembly machines, and (more famous and photogenic) the jointed, arm-like devices called “industrial robots.” Many factories today use both machines and human labor to perform assembly, and economics largely determines the extent of machine automation. Machine-based assembly has been in practice for decades (in the automobile industry, for example) and industrial robots are gaining ground as their costs fall and capabilities increase. APM can deliver macroscopic products (built from smaller parts, in turn built from yet smaller parts, and so on), and the macroscopic end of the process can be almost perfectly conventional.

Four Futures: Life After Capitalism by Peter Frase

Aaron Swartz, Airbnb, Anthropocene, basic income, bitcoin, business cycle, call centre, Capital in the Twenty-First Century by Thomas Piketty, carbon footprint, carbon tax, congestion pricing, cryptocurrency, deindustrialization, do what you love, Dogecoin, Donald Shoup, Edward Snowden, emotional labour, Erik Brynjolfsson, Ferguson, Missouri, fixed income, full employment, future of work, green new deal, Herbert Marcuse, high net worth, high-speed rail, income inequality, industrial robot, informal economy, Intergovernmental Panel on Climate Change (IPCC), iterative process, Jevons paradox, job automation, John Maynard Keynes: Economic Possibilities for our Grandchildren, Kim Stanley Robinson, litecoin, mass incarceration, means of production, military-industrial complex, Occupy movement, pattern recognition, peak oil, plutocrats, post-work, postindustrial economy, price mechanism, private military company, Ray Kurzweil, Robert Gordon, Second Machine Age, self-driving car, sharing economy, Silicon Valley, smart meter, TaskRabbit, technoutopianism, The future is already here, The Future of Employment, Thomas Malthus, Tyler Cowen, Tyler Cowen: Great Stagnation, universal basic income, Wall-E, warehouse robotics, Watson beat the top human players on Jeopardy!, We are the 99%, Wolfgang Streeck

The review of legal documents, an extremely time-consuming process traditionally performed by legions of junior lawyers, is another promising application of the technology. Another area of rapid advance is robotics, the interaction of machinery with the physical world. Over the twentieth century, great advances were made in the development of large-scale industrial robots, of the sort that could operate a car assembly line. But only recently have they begun to challenge the areas in which humans excel: fine-grained motor skills and the navigation of a complex physical terrain. The US Department of Defense is now developing computer-controlled sewing machines so as to avoid sourcing its uniforms from China.9 Until just the past few years, self-driving cars were regarded as well beyond the scope of our technical ability.

Information: A Very Short Introduction by Luciano Floridi

agricultural Revolution, Albert Einstein, bioinformatics, Bletchley Park, carbon footprint, Claude Shannon: information theory, Computing Machinery and Intelligence, conceptual framework, digital divide, disinformation, double helix, Douglas Engelbart, Douglas Engelbart, George Akerlof, Gordon Gekko, Gregor Mendel, industrial robot, information asymmetry, intangible asset, Internet of things, invention of writing, John Nash: game theory, John von Neumann, Laplace demon, machine translation, moral hazard, Nash equilibrium, Nelson Mandela, Norbert Wiener, Pareto efficiency, phenotype, Pierre-Simon Laplace, prisoner's dilemma, RAND corporation, RFID, Thomas Bayes, Turing machine, Vilfredo Pareto

In economics, it is the sum of the utilities associated with all possible outcomes of a course of action, weighted by the probability that each outcome will occur, where `utilities' refers to a measure of the relative satisfaction from, or desirability of, an outcome, e.g. the consumption of a good or service. The benefits brought about by information need to be understood contextually because the agents exchanging information could be not only human individuals, but also biological agents, social groups, artificial agents (such as software programs or industrial robots), or synthetic agents (such as a corporation or a tank), which comprise agents of all kinds. In Chapter 1, we saw how human society has come to depend, for its proper functioning and growth, on the management and exploitation of information processes. Unsurprisingly, in recent years the scientific study of economic information has bloomed.

Applied Artificial Intelligence: A Handbook for Business Leaders by Mariya Yao, Adelyn Zhou, Marlene Jia

Airbnb, algorithmic bias, AlphaGo, Amazon Web Services, artificial general intelligence, autonomous vehicles, backpropagation, business intelligence, business process, call centre, chief data officer, cognitive load, computer vision, conceptual framework, data science, deep learning, DeepMind, en.wikipedia.org, fake news, future of work, Geoffrey Hinton, industrial robot, information security, Internet of things, iterative process, Jeff Bezos, job automation, machine translation, Marc Andreessen, natural language processing, new economy, OpenAI, pattern recognition, performance metric, price discrimination, randomized controlled trial, recommendation engine, robotic process automation, Salesforce, self-driving car, sentiment analysis, Silicon Valley, single source of truth, skunkworks, software is eating the world, source of truth, sparse data, speech recognition, statistical model, strong AI, subscription business, technological singularity, The future is already here

In sales, for example, machine learning approaches to lead scoring can perform better than rule-based or statistical methods. Once the machine has produced a prediction on the quality of a lead, the salesperson then applies human judgment to decide how to follow up. More complex systems, such as self-driving cars and industrial robotics, handle everything from gathering the initial data to executing the action resulting from its analysis. For example, an autonomous vehicle must turn video and sensor feeds into accurate predictions of the surrounding world and adjust its driving accordingly. Systems That Create We humans like to think we’re the only beings capable of creativity, but computers have been used for generative design and art for decades.

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

Ada Lovelace, additive manufacturing, Airbnb, Albert Einstein, AlphaGo, Amazon Mechanical Turk, Amazon Robotics, augmented reality, autonomous vehicles, barriers to entry, Big Tech, biodiversity loss, bitcoin, blockchain, blood diamond, Boston Dynamics, Burning Man, call centre, cashless society, Charles Babbage, Charles Lindbergh, Clayton Christensen, clean water, cloud computing, Colonization of Mars, computer vision, creative destruction, CRISPR, crowdsourcing, cryptocurrency, data science, Dean Kamen, deep learning, deepfake, DeepMind, delayed gratification, dematerialisation, digital twin, disruptive innovation, Donald Shoup, driverless car, Easter island, Edward Glaeser, Edward Lloyd's coffeehouse, Elon Musk, en.wikipedia.org, epigenetics, Erik Brynjolfsson, Ethereum, ethereum blockchain, experimental economics, fake news, food miles, Ford Model T, fulfillment center, game design, Geoffrey West, Santa Fe Institute, gig economy, gigafactory, Google X / Alphabet X, gravity well, hive mind, housing crisis, Hyperloop, impact investing, indoor plumbing, industrial robot, informal economy, initial coin offering, intentional community, Intergovernmental Panel on Climate Change (IPCC), Internet of things, invention of the telegraph, Isaac Newton, Jaron Lanier, Jeff Bezos, job automation, Joseph Schumpeter, Kevin Kelly, Kickstarter, Kiva Systems, late fees, Law of Accelerating Returns, life extension, lifelogging, loss aversion, Lyft, M-Pesa, Mary Lou Jepsen, Masayoshi Son, mass immigration, megacity, meta-analysis, microbiome, microdosing, mobile money, multiplanetary species, Narrative Science, natural language processing, Neal Stephenson, Neil Armstrong, Network effects, new economy, New Urbanism, Nick Bostrom, Oculus Rift, One Laptop per Child (OLPC), out of africa, packet switching, peer-to-peer lending, Peter H. Diamandis: Planetary Resources, Peter Thiel, planned obsolescence, QR code, RAND corporation, Ray Kurzweil, RFID, Richard Feynman, Richard Florida, ride hailing / ride sharing, risk tolerance, robo advisor, Satoshi Nakamoto, Second Machine Age, self-driving car, Sidewalk Labs, Silicon Valley, Skype, smart cities, smart contracts, smart grid, Snapchat, SoftBank, sovereign wealth fund, special economic zone, stealth mode startup, stem cell, Stephen Hawking, Steve Jobs, Steve Jurvetson, Steven Pinker, Stewart Brand, supercomputer in your pocket, supply-chain management, tech billionaire, technoutopianism, TED Talk, Tesla Model S, Tim Cook: Apple, transaction costs, Uber and Lyft, uber lyft, unbanked and underbanked, underbanked, urban planning, Vision Fund, VTOL, warehouse robotics, Watson beat the top human players on Jeopardy!, We wanted flying cars, instead we got 140 characters, X Prize