precision agriculture

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pages: 385 words: 103,561

Pinpoint: How GPS Is Changing Our World by Greg Milner

Ayatollah Khomeini, British Empire, creative destruction, data acquisition, Dava Sobel, different worldview, digital map, Edmond Halley, Eratosthenes, experimental subject, Flash crash, friendly fire, Hedy Lamarr / George Antheil, Internet of things, Isaac Newton, John Harrison: Longitude, Kevin Kelly, land tenure, lone genius, low earth orbit, Mars Rover, Mercator projection, place-making, polynesian navigation, precision agriculture, race to the bottom, Silicon Valley, Silicon Valley startup, skunkworks, smart grid, the map is not the territory

Just 22 percent of farms in the U.K. are using navigation satellites to increase accuracy, though that figure is slowly increasing. A survey of precision agriculture practices across the continent commissioned by the European Parliament noted a widespread skepticism of these methods among farmers in England, concluding that “there is a long way to go before the majority is convinced.” By 2020, the precision agriculture market (including tools that do not use GPS) will be worth $4.5 billion, and nearly 50 percent of the world’s tractors will use GPS. The fastest-growing market for GPS-based precision agriculture is Asia and the Pacific, where the adoption rate has been almost viral, from nearly nobody in 2006 to 17 percent of the world’s installed GPS precision agriculture systems in 2015, and growing at nearly twice the global rate. Evidence suggests that precision agriculture may be just as helpful for tiny farms (one or two acres) in developing nations as it is for larger farms.

Pham, “The Economic Benefits of Commercial GPS Use in the US and the Costs of Potential Disruption,” NDP Consulting, June 2011, http://saveourgps.org/pdf/GPS-Report-June-22-2011.pdf. The study analyzed U.S. crop production from 2007 to 2010 and estimated that GPS reduced input costs by $9.8 billion and accounted for $10.1 billion in output. 104 “there is a long way to go”: “Precision Agriculture: An Opportunity for EU Farmers,” European Parliament, Directorate-General For Internal Policies, Policy Department B, Structural And Cohesion Policies, Agriculture and Rural Development, 2014, 35–6. 104 By 2020: “Precision Farming Market by Technology (GPS/GNSS, GIS, Remote Sensing & VRT), Components (Automation & Control, Sensors, FMS), Application (Yield Monitoring, VRA, Mapping, Soil Monitoring & Scouting) and Geography—Global Forecasts to 2020,” MarketsandMarkets, 2014. 104 nearly 50 percent of the world’s tractors: European Global Navigation Satellite Systems Agency, “GNSS Market Report.” 104 The fastest-growing market: European Global Navigation Satellite Systems Agency, “GNSS Market Report.” 105 Evidence suggests: Caspar Van Vark, “From Agribusiness to Subsistence: High-Tech Tools Now Available to All,” Guardian, June 4, 2014. 105 In Uttar Pradesh: Ibid.

Seaworth Farms has been in the family since Troy’s grandfather purchased the 2,000 acres in 1945, using most of it to grow beets, which are still the farm’s main crop, along with corn, hay, and beans. In the mid-1990s, when Troy was studying agronomy at Kansas State University, he learned about the burgeoning field of precision agriculture. Practitioners of precision agriculture squeeze every last bit of efficiency out of the process, maximizing yield while minimizing cost—in money and time—and the use of resources such as water, fertilizer, and pesticides. Troy became a convert, and convinced his dad that investing in precision agriculture would quickly pay for itself. Troy wanted to convert most of the farm to a farming practice called strip till. The process of harvesting a field leaves behind leaves and other organic residue, which a farmer would traditionally remove in preparation for the next planting.


The New Harvest: Agricultural Innovation in Africa by Calestous Juma

agricultural Revolution, Albert Einstein, barriers to entry, bioinformatics, business climate, carbon footprint, clean water, colonial rule, conceptual framework, creative destruction, double helix, energy security, energy transition, global value chain, income per capita, industrial cluster, informal economy, Intergovernmental Panel on Climate Change (IPCC), Joseph Schumpeter, knowledge economy, land tenure, M-Pesa, microcredit, mobile money, non-tariff barriers, off grid, out of africa, precision agriculture, Second Machine Age, self-driving car, Silicon Valley, sovereign wealth fund, structural adjustment programs, supply-chain management, total factor productivity, undersea cable

One benefit is that it improves labor productivity and quality of life for farmers. It improves crop productivity by allowing farmers to plan exactly when to till, plant, weed, and apply fertilizer, based on changing conditions, without relying on labor or other resources. It can help in more appropriate applications (e.g., split application) of organic and nonorganic fertilizer, resulting in healthier soils. It is also a key component of precision agriculture such as direct seeding, which helps to limit tillage and carbon dioxide emissions. Finally, countries such as Uganda, Tanzania, and Zambia are realizing the benefits of technical education and are encouraging greater enrollment in standard and nonstandard programs. As more technical support becomes available in rural areas, tractors and other equipment become easier to maintain, and new entrepreneurial activities unfold.

UAVs, on the other hand, can provide high-quality data at an affordable price compared to aerial imagery or very high-resolution satellite data, and they can provide the real-time and frequent data collection that is essential to crop monitoring. One important use of this data is for land monitoring, which includes land management practices that can help reduce degradation and soil erosion. Second, it can be used to enhance precision agriculture, which can help farmers vary the rate of input use in order to reduce costs and improve efficiency. Third, one of the most important applications is using decision support systems for agro-technology transfer to produce yield maps, which are created by integrating data from 54 THE NEW HARVEST UAVs as well as on-the-ground data and can be made available to all farmers through smartphone applications.

Existing educational opportunities do not tap into this mindset, nor does the educational system in Africa specifically address the challenges faced by the sector. Sub-Saharan Africa still ranks the lowest in the world in terms of yield-enhancing practices and techniques, even compared to other developing regions. These practices include mechanization, use of agro-chemicals, improved seed, precision farming techniques, and increased use of irrigation.43 Mechanization is very low, with approximately 13 tractors per 100 square kilometers of arable land, versus 200 tractors per 100 square kilometers globally.44 Similarly, there are only two tractors per 1,000 farmers in sub-Saharan Africa versus 883 per 1,000 in the United Kingdom.45,46 As mentioned above, only 4% of sub-Saharan Africa’s cropland is irrigated, compared with the world average of 18.4%, and the use of chemical inputs is minimal, at nine kilograms per hectare compared with the world average of 100 kilograms per hectare.


pages: 364 words: 99,897

The Industries of the Future by Alec Ross

23andMe, 3D printing, Airbnb, algorithmic trading, AltaVista, Anne Wojcicki, autonomous vehicles, banking crisis, barriers to entry, Bernie Madoff, bioinformatics, bitcoin, blockchain, Brian Krebs, British Empire, business intelligence, call centre, carbon footprint, cloud computing, collaborative consumption, connected car, corporate governance, Credit Default Swap, cryptocurrency, David Brooks, disintermediation, Dissolution of the Soviet Union, distributed ledger, Edward Glaeser, Edward Snowden, en.wikipedia.org, Erik Brynjolfsson, fiat currency, future of work, global supply chain, Google X / Alphabet X, industrial robot, Internet of things, invention of the printing press, Jaron Lanier, Jeff Bezos, job automation, John Markoff, Joi Ito, Kickstarter, knowledge economy, knowledge worker, lifelogging, litecoin, M-Pesa, Marc Andreessen, Mark Zuckerberg, Mikhail Gorbachev, mobile money, money: store of value / unit of account / medium of exchange, Nelson Mandela, new economy, 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, The Future of Employment, Travis Kalanick, underbanked, Vernor Vinge, Watson beat the top human players on Jeopardy!, women in the workforce, Y Combinator, young professional

Monsanto, DuPont, and John Deere will have to continue to acquire the most promising start-ups, the precision-agriculture natives, if they are going to stay ahead in what will be a fast-changing field. I also think that small farmers are likely to derive as much benefit from precision agriculture as larger farmers with thousands of acres. Precision agriculture is not based on huge enterprise software systems that take up half the barn. That expensive software is in the cloud and accessible on cheap devices like smartphones and the tablets I saw in the tractor’s “cockpit.” The costs on the hardware side, including the sensors, will continue to decline, and the real costs will come from subscriptions to the software as a service—the precision agriculture content. This is the business model the big agribusinesses are already pushing, and it will spread from the highest-tech farmers working huge fields to the small family farm.

As the population continues to grow rapidly, the task of producing enough rice, wheat, and other staples grows more difficult. Precision agriculture will not end hunger in India or turn its subsistence-level farmers into serious agribusinesses, but in an environment of scarcity, it can take those scarce resources, be they seed, fertilizer, or water, and get the most out of them. India does not have a national network of agronomists to provide expertise and resources to its country’s farmers as China, the Americas, and Europe do. The budgetary resources in India are spread too thin. When precision agriculture mainstreams, it could play the role of these national networks of agronomists. The best hope for India is that precision agriculture provides a leapfrog opportunity, helping its subsistence-level farmers achieve a level of performance that is impossible for them today.

The best hope for India is that precision agriculture provides a leapfrog opportunity, helping its subsistence-level farmers achieve a level of performance that is impossible for them today. It represents the best hope for feeding the hundreds of millions of people in India who don’t have enough to eat today. Precision agriculture will take farming from being an industrial age industry to a digital age industry. Precision agriculture also offers the promise of a major reduction in pollution. My adopted home state of Maryland provides an excellent example. I live on the Chesapeake Bay, home to beautiful waterways and delicious blue crabs. But the population of the bay’s crabs and other animal life has plummeted in recent decades because nitrogen from excess fertilizer has fouled the water. Nitrogen from fertilizer creates dead zones; there is one in the Gulf of Mexico that’s the size of New Jersey. And as the fertilizer kills off my home’s aquaculture, it also contributes to climate change.


pages: 239 words: 70,206

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

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

The Central Valley research, a side-by-side comparison of two methods of crop management, is the equivalent of an Internet A/B test of an ad or online offering, except done on a patch of the earth rather than on a Web site. The precision agriculture pilot was a joint effort of two companies, IBM and E. & J. Gallo Winery. And it was in good part a collaboration between two men: Hendrik Hamann, a German physicist and researcher at IBM, and Dokoozlian, a native Californian who grew up on a small family vineyard and is Gallo’s chief plant scientist. Dokoozlian sees precision agriculture as the latest step in a decades-long march, transforming a craft ruled by tradition and established practice into a science relying on objective measurement. “Nothing exemplifies that more than winemaking,” he says. Dokoozlian is a big man with a sturdy frame, thinning salt-and-pepper hair, and the tan of someone who spends plenty of time outside.

., 5–6 Snyder, Steven, 165–67, 170 social networks, research using human behavior and, 86–94 retail use, 153–62 spread of information and, 73–74 Twitter posts and, 197–202 see also privacy concerns Social Security numbers, data used to predict person’s, 187–88 software, origin of term, 96 Solow, Robert, 72 Speakeasy programming language, 160 Spee (Harvard club), 28–30 Spohrer, Jim, 25 Stanford University, 211–12 Starbucks, 157 Stockholm, rush-hour pricing in, 47 storytelling, computer algorithms and, 120–21, 149, 165–66, 205, 214 structural racism, in big data racial profiling, 194–95 Structure of Scientific Revolutions, The (Kuhn), 175 Sweeney, Latanya, 193–95 System S, at IBM, 40 Tarbell, Ida, 208 Taylor, Frederick Winslow, 207–8 Tecco, Halle, 16, 25, 28, 168–69 Tetlock, Philip, 67–68 thermostats, learning by, 143–45, 147–53 Thinking, Fast and Slow (Kahneman), 66–67 toggling, 84 Truth in Lending Act (1968), 185 T-shaped people, 25 Tukey, John, 96–97 Turing, Alan, 178–79 Tversky, Amos, 66 Twitter, 85 posts studied for personal information, 197–202 “Two Cultures, The” (Snow), 5–6 “universal machine” (Turing’s theoretical computer), 179 universities, data science and, 15–16, 97–98, 211–12 Unlocking the Value of Personal Data: From Collection to Usage (World Economic Forum), 203 “Unreasonable Effectiveness of Data, The” (Norvig), 116 use-only restrictions, on data, 203 Uttamchandani, Menka, 77–78, 80, 212 VALS (Values, Attitudes, and Lifestyles), 155 Van Alstyne, Marshall, 74 Vance, Ashlee, 85 Vargas, Veronica, 159–60 Varma, Anil, 136–37 Veritas, 91 vineyards, data used for precision agriculture in, 123–33, 212 Vivero, David, 29 Vladeck, David, 203, 204 von Neumann, John, 54 Von Neumann architecture, 54 Walker, Donald, 2, 63, 212 Walmart, 104, 154 Watson, Thomas Jr., 49 Watson technology, of IBM, 45, 66–67, 120, 205 as cloud service, 9, 54 Jeopardy and, 7, 40, 111, 114 medical diagnoses and, 69–70, 109 Watts, Duncan J., 86 weather analysis, with big data, 129–32 Weitzner, Daniel, 184 “Why ask Why?” (Gelman and Imbens), 115–16 winemaking, precision agriculture and, 123–33, 212 Wing, Michael, 49–50 workforce rebalancing, at IBM, 57 World Economic Forum, 203 Yarkoni, Tal, 199 Yoshimi, Bill, 198 ZestFinance, data correlation and, 104–7 Zeyliger, Philip, 100–101 Zhou, Michelle, 197–202 Zuckerberg, Mark, 28, 86, 89 ABOUT THE AUTHOR Photo by Fred Conrad STEVE LOHR reports on technology, business, and economics for the New York Times.

A few golden-brown leaves still hang on the trellised vines, but most of the leaves are underfoot and the grapes are gone, all harvested. The vines stand in neat rows that extend to the horizon, each in its assigned place, patiently waiting. The crisp fall air smells of dry, fallen leaves and rich alluvial soil. “This is autumn in the vineyard,” says Nick Dokoozlian. “Yes, it’s a beautiful thing.” This vineyard in the north of the Central Valley, outside the town of Lodi, is also the site of an encouraging experiment in precision agriculture, which is essentially big-data farming. Using data from on-the-ground sensors and satellite imaging, a research team was able to tailor the ideal water and fertilizer amounts to be drip-fed to vines almost on a vine-by-vine basis. In the 2013 growing season, two sections of the vineyard, side by side, served as an agricultural petri dish. One ten-acre section was managed with the precision techniques, while the vines in the other ten-acre tract received the usual standard doses of water and fertilizer.


pages: 523 words: 61,179

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

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

Both fresh water and arable soil are resources that have historically been difficult to acquire or maintain for agriculture. Precision agriculture—which leverages AI and fine-grain data about the state of crops—promises to significantly improve yield, reduce the waste of resources like water and fertilizer, and increase overall efficiency. To be effective, precision agriculture requires a vast network of diverse IoT sensors to collect granular data. This information might include aerial images captured by satellites or drones (to detect crop distress before it’s visible at ground level), environmental sensors in the field (to monitor the chemical composition of the soil, for instance), sensors mounted on farm equipment, weather forecast data, and soil databases. To help make sense of these various data streams, Accenture has developed a new service—the Precision Agriculture Service—that deploys AI to enable better decision making with respect to pest control, fertilizer usage, and so on.

AeroFarms is predicting that 2 million pounds of produce can be grown annually at the Newark vertical farm, only about fifteen miles from Manhattan.11 Precision agriculture is not yet widespread, but some of its technologies—the analysis of satellite data, for instance—have been used for years. The difference now is the pervasiveness of the IoT, which allows sensor data to talk to apps, and apps to talk to machine-learning-enabled systems. The ultimate goal with precision agriculture is that disparate systems can come together to produce recommendations that farmers can then act on in real time. The result is agricultural processes that produce less waste and higher yields. It’s no wonder that precision-agriculture services are expected to grow to $4.55 billion by 2020.12 As the technology becomes more widely used, the land will benefit, the farmer will benefit, and the hundreds of millions of people who need access to healthy affordable food will benefit.

See ethical, moral, legal issues Mori, Masahiro, 131 Murphy, Mike, 23 Nadella, Satya, 203 Nao, 146 NASA, 200–201 natural-language agents, 55–56, 59, 65, 145–146 natural-language processing (NLP), 64 Nettsträter, Andreas, 26 network analysis, 45–46 neural networks, 34 deep, recurrent, and feedforward, 63 definition of, 62 history of, 40–41 neural opportunism, 205–206 Nike, 74–75 Nina, 145–146 Nissan, 113–114 normalizing, responsible, 12, 189–191 Nuance Communications, 145–146 Numerate, 81 Oak Labs, 87–88 observation, 69–72, 157–158 on-demand work environment, 111 operations, reimagining, 29–30 optimization, 63, 77 Orcutt, Mike, 78, 79 outsourcing, 120–121 PAIR (People + AI Research) initiative, 179 Paley, Sean, 199 Papert, Seymour, 40–41 PCSK9 drugs, 74 Penn Medicine, 188 Percolata, 88–89 performance, 3–4, 7, 11–12 personality trainers, 118–119 personalization brands and, 96–97 of cars, 147–149 definition of, 66 marketing and sales, 86, 89–90, 91 product/service design and, 76 theory and practice of, 77–80 ultra-customization, 68 Pew Center, 167 pharmaceutical industry, 81 Philips, 87, 141–143 Pogo, 196 Popper, Nathaniel, 49 Pratt, Gill, 166 Precision Agriculture Service, 35 predictive systems, 63 Predix, 27, 29–30, 75, 183–184 Preferred Networks, 21–22 pricing decisions, 193–194 privacy issues, 90, 164–165 processes, 4 adaptive, 5–6, 16, 108–109 automated, 5, 19 determining which to change, 52–54 discovering and describing, 155–158 experimentation with, 14, 160–165 guardrails in, 168–169 mindset for reimagining, 155–160 reimagining, 50, 105–112, 151–152, 203–205 reimagining, leadership in, 153–181 reimagining around people, 58–59 rewriting, 9 robotic automation of, 50–52 standardized, 5 Procter & Gamble, 34 procurement, 53–54 product design, 74–76 generative design in, 135–137, 139, 141 product development, 29 production, 19–39 in agriculture, 34–37 third wave, 38–39 productivity, 3–4, 135–152 job satisfaction and, 46–47 rehumanizing time and, 188–189 products, intelligent, 66 product support, 87 “quantamental” funds, 122 Quid, 70–72 Quixote, 130 Raccuglia, Paul, 71 radio-frequency identification (RFID), 31, 87–88 Ralph Lauren, 87–88, 100 rating systems, 172 R&D.


pages: 219 words: 63,495

50 Future Ideas You Really Need to Know by Richard Watson

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

the condensed idea Don’t panic, we’re inventive timeline 1973 First oil crisis 2020 Launch of North African solar grid 2025 Oil, coal and gas still responsible for 70 percent of energy supply 2030 Global energy demand up by 50 percent over 2008 levels 2045 Clean energy islands built off the coast of China 2050 First commercial thorium reactor 08 Precision agriculture Global population growth (more precisely, global income growth) will challenge the ability of agriculture to deliver maximum productivity in the future, especially if climate change negatively affects agricultural yields. Until quite recently farmers used experience mixed with trial and error to produce crops, but things are changing down on the farm. “Precision agriculture” is a term used to describe the use of hyperspecific GPS (global positioning systems) and digital mapping to control precisely the application of seeds, pesticides and water to crops and, on occasion, to manage livestock.

ISBN 978-1-62365-195-4 Distributed in the United States and Canada by Random House Publisher Services c/o Random House, 1745 Broadway New York, NY 10019 www.quercus.com Contents Introduction POLITICS & POWER 01 Ubiquitous surveillance 02 Digital democracy 03 Cyber & drone warfare 04 Water wars 05 Wane of the West ENERGY & ENVIRONMENT 06 Resource depletion 07 Beyond fossil fuels 08 Precision agriculture 09 Population change 10 Geo-engineering THE URBAN LANDSCAPE 11 Megacities 12 Local energy networks 13 Smart cities 14 Next-generation transport 15 Extra-legal & feral slums TECHNOLOGICAL CHANGE 16 An internet of things 17 Quantum & DNA computing 18 Nanotechnology 19 Gamification 20 Artificial Intelligence HEALTH & WELL-BEING 21 Personalized genomics 22 Regenerative medicine 23 Remote monitoring 24 User-generated medicine 25 Medical data mining SOCIAL & ECONOMIC DIMENSIONS 26 Living alone 27 Dematerialization 28 Income polarization 29 What (& where) is work?


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

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

Hope appeared in the form of a bright green John Deere tractor. We were introduced to Carl Wellington, another NREC researcher, whose work focuses on helping agricultural companies automate farming equipment. Modern agricultural practices are technologically sophisticated, using an approach called precision agriculture. Carl explained that farmers have used partially autonomous vehicles for more than a decade. In the early stages of automation, farmers equipped their tractors with highly accurate GPS systems and used farm management software to map out their fields. In the early days of precision agriculture, a human driver was still required. The first generation of autonomous agricultural vehicles, while capable of handling the straightaways, still needed a human driver to steer the tractor around the curves at the end of each field. A few years later, however, commercial software capable of guiding an autonomous tractor around curves became available.

See National Highway Transportation and Safety Administration 1964 World’s Fair, 121 1939 World’s Fair, 107–110 NREC, 68–72 NVIDIA, 225 Object recognition, 87–90. See also Artificial perception Occupancy grid, 11, 93–95. See also Mid-level controls Operating systems. See Artificial Intelligence; Automotive operating system; Controls engineering; Robotic operating system Parking lots, 32–37 Perceptron, 202–206, 208, 209 Platooning, 30 Precision agriculture, 74 Pratt, Gill, 183 Privacy, 247, 248, 249 Public transportation, 40, 41, 42 Qualia, 231–233 Radar, 181–184 RCA, 116–120 Reactive controls. See Low-level controls Rebound effect, 25 Recombinant innovation, 166 Reliability, 67, 98–104, 195. See also Humansafe ratings Residual learning 228 Retail, 269–272 Road capacity, 30 Robotic density, 48 Robotic operating system Challenges of creating, 71–74 Overview of, 66, 67 See also CHIMP; Controls engineering Robot morality.


pages: 372 words: 94,153

More From Less: The Surprising Story of How We Learned to Prosper Using Fewer Resources – and What Happens Next by Andrew McAfee

back-to-the-land, Bartolomé de las Casas, Berlin Wall, bitcoin, Branko Milanovic, British Empire, Buckminster Fuller, call centre, carbon footprint, clean water, cleantech, cloud computing, Corn Laws, creative destruction, crony capitalism, David Ricardo: comparative advantage, decarbonisation, dematerialisation, Deng Xiaoping, Donald Trump, Edward Glaeser, en.wikipedia.org, energy transition, Erik Brynjolfsson, failed state, Fall of the Berlin Wall, Haber-Bosch Process, Hans Rosling, humanitarian revolution, hydraulic fracturing, income inequality, indoor plumbing, intangible asset, James Watt: steam engine, Jeff Bezos, job automation, John Snow's cholera map, joint-stock company, Joseph Schumpeter, Khan Academy, Landlord’s Game, Louis Pasteur, Lyft, Marc Andreessen, market fundamentalism, means of production, Mikhail Gorbachev, oil shale / tar sands, Paul Samuelson, peak oil, precision agriculture, profit maximization, profit motive, risk tolerance, road to serfdom, Ronald Coase, Ronald Reagan, Scramble for Africa, Second Machine Age, Silicon Valley, Steve Jobs, Steven Pinker, Stewart Brand, telepresence, The Wealth of Nations by Adam Smith, Thomas Davenport, Thomas Malthus, Thorstein Veblen, total factor productivity, Uber and Lyft, uber lyft, Veblen good, War on Poverty, Whole Earth Catalog, World Values Survey

Technology: The Human Interface with the Material World One of my favorite definitions of technology comes from the philosopher Emmanuel Mesthene, who called it “the organization of knowledge for the achievement of practical purposes.” Sometimes that knowledge is crystallized into products such as hammers and iPhones, and sometimes it exists as techniques such as those for fracking or precision agriculture. Like knowledge itself, technologies accumulate. We haven’t forgotten about the lever, the plow, or the steam engine in the Second Machine Age, and we haven’t had to give them up to use cloud computing or drones. Like innovation itself, technologies are combinatorial; most of them are combinations or recombinations of existing things. This implies that the number of potentially powerful new technologies increases over time because the number of available building blocks does.

Such contraptions sound like science fiction today, but they might be carrying us around by midcentury. Agriculture. As we saw in chapter 5, leading farms have demonstrated an ability to increase their tonnage of output year after year while decreasing their use of inputs such as land, water, and fertilizer. This trend toward optimization will continue thanks to a set of innovations under the label precision agriculture. The precision comes from many sources, including better sensors of plant and animal health, soil quality and moisture, and so on; the ability to deliver fertilizer, pesticides, and water just where they’re needed; and machinery that adapts itself to each plant or animal. All these varieties of precision will combine to allow traditional farms to generate more from less. So will changes to the genomes of plants and animals.

., 114–15 lead, 95 leather, 45 Leopold II, King of Belgium, 39 Li Keqiang, 146 Life, 61 life expectancy, 13, 32, 196–97 limits, imposing of, 65–67, 93–97 Limits to Growth, The, 57–58, 65, 66, 71, 93, 119–20 Lincoln, Abraham, 37, 38, 121 Linux operating system, 235–36 Litton, Martin, 61 living standards, 9–10, 32, 69 Lomborg, Bjorn, 179, 181 London, 22–23, 26 Lovins, Amory, 58–59 MacLeish, Archibald, 54 Macron, Emmanuel, 155, 250 Maddison, Angus, 9, 13 Maduro, Nicolas, 134–35, 137–38 Magee, Christopher, 73 Magie, Elizabeth, 203 Malthus, Thomas Robert, 7–8, 9, 10, 13, 15, 20, 131, 237 mammals, biomass of, 33 Mann, Charles, 31 manufacturing, 202, 239–40 Mao Zedong, 170 Marine Mammal Protection Act (1972), 96 market fundamentalism, 131–32, 133 Marshall, Alfred, 47–48, 50–51, 63, 99, 108–09, 141, 6977 Martha’s Vineyard Fishermen’s Preservation Trust, 263 Marx, Karl, 21, 130, 131 material intensity, 75 maternal mortality, 196–97 Mattis, James, 211–12 Maybach, Wilhelm, 27 Meadows, Donella, 57 Mesthene, Emmanuel, 114 metals, 56, 79 Mexico, 137, 139 Microsoft, 102, 257 Milanovic, Branko, 221 Mill, John Stuart, 180 Miller, Grant, 28 Mines Act (1842), 38 Mises, Ludwig von, 40 Mokyr, Joel, 122 Molina, Mario, 149 monopolies, 202–03, 204 Monsanto, 155 Montreal Protocol, 150, 249 Morris, Ian, 24–25, 60n Most Powerful Idea in the World, The (Rosen), 16 motors, 27 Mussolini, Benito, 40 Naam, Ramez, 31 National Security Council, 56 Native Americans, 44–45 natural gas, 103, 104, 109, 110, 188 Nature Wars (Sterba), 43–44 negative bias, 179–81 negative externalities, 142, 186, 247–48, 253 Nelson, Gaylord, 61 Neolithic revolution, 12 New Pioneers (Jacob), 91 New Testament, 127 New York Times, 53, 61–62, 147 Newcomen, Thomas, 16 Nicholas, Kim, 185 nitrogen, 30–31 nitrogen pollution, 190 Nixon, Richard, 66 Nokia, 102, 111 nonprofits, 259–63 Nordhaus, William, 248–49 Norquist, Grover, 132 North, Douglass, 159 North Korea, 133 nuclear energy, 58–59, 110, 251–52, 266 nuclear fusion, 240–41 Nunn, Nathan, 268 nutrition, 23–24, 32, 177, 193 ocean acidification, 190 O’Hanlon, Michael, 174 oil, 135–36 one-child policy, 93–94 Ostrom, Elinor, 182 Our World in Data (website), 179, 180 overdoses, 215, 216 ozone layer, 149–50, 228 Pacific Steam Navigation Company, 17 Paddock, William and Paul, 55–56 Paris Agreement, 158 partial excludability, 232–33 passenger pigeon, 42–43, 96, 152, 181 Pasteur, Louis, 23 Patagonia National Park, 260 patents, 19, 116, 232, 235 peak oil, 102–05 peak paper, 90, 113 “Peak Stuff” (Goodall), 76–77 pertussis, 227 Peru, 138 Petroleum Reitwagen, 27 phones, 168–69 Pinker, Steven, 37, 122, 176, 177, 179 Plain Cookery Book for the Working Classes, A (Francatelli), 23–24 plastics, 83, 252 plumbing, indoor, 26, 28–30, 168 Poland, 92 polarization, political, 224–25, 254 Politics of Resentment, The (Cramer), 221 pollution, 5, 23, 35, 36, 40–42, 54–55, 63, 66–67, 95, 141, 142, 157, 160–61, 167, 266 globalization of, 148–50 markets for, 143–44 Poole, Robert, 54 population, 13, 32–33, 62–63, 88, 192 of England, 10–11 global, 55–56, 65–69, 71 limiting, 93–94 oscillation in, 8–12, 15, 17, 31 Population Bomb, The (Ehrlich), 55, 65 poverty, 10–11, 179–80, 181, 189, 191–92, 215 Poverty and Famines (Sen), 69 precision agriculture, 242–43 price elasticity of demand, 49, 108–09 Principles of Economics (Marshall), 50–51 private ownership, 117, 170 “Problem of Social Cost, The” (Coase), 143 profit-seeking companies, 115–16 property rights, 116, 133 proteins, 239–40 public awareness, 3–4, 145–48, 153, 154, 158–59, 161, 167–68, 176–78, 226 Public Health Service, US, 55 Putnam, Robert, 212, 213 Radio Shack, 102 railroads, 18, 19, 26, 105–06, 109–10 Rand, Ayn, 132 rare earth elements (REE), 106–08, 109, 110 Reagan, Ronald, 132 rebound effect, 72–73 reciprocity, 212, 213, 217 recycling, 64–65, 90–91 reforestation, 184, 185 regulation, 5 regulatory capture, 129 religion, 115 renewable energy, 111 resource availability, 119–20 resource consumption, 56–58, 63–64, 78–79, 99, 119–20 responsive government, 3–4, 145–48, 153, 154, 158–59, 161, 167–68, 175–76 Return of Nature, The (Ausubel), 4–5 Ricardo, David, 19n Ridley, Matt, 161 Riley, James, 13 Ripley, S.


pages: 472 words: 117,093

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

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

Financial Times, October 19, 2015, https://www.ft.com/content/43f7436a-7632-11e5-a95a-27d368e1ddf7. 100 The driverless vehicles run twenty-four hours a day: Rio Tinto, “Driving Productivity in the Pilbara,” June 1, 2016, http://www.riotinto.com/ourcommitment/spotlight-18130_18328.aspx. 101 Automated milking systems: Janet Beekman and Robert Bodde, “Milking Automation Is Gaining Popularity,” Dairy Global, January 15, 2015, http://www.dairyglobal.net/Articles/General/2015/1/Milking-automation-is-gaining-popularity-1568767W. 101 Ninety percent of all crop spraying: Alltech, “Drones and the Potential for Precision Agriculture,” accessed January 30, 2017, http://ag.alltech.com/en/blog/drones-and-potential-precision-agriculture. 101 “radically simplify[ing] the environment”: David H. Autor, “Why Are There Still So Many Jobs? The History and Future of Workplace Automation,” Journal of Economic Perspectives 29, no. 3 (2015): 3–30, http://pubs.aeaweb.org/doi/pdfplus/10.1257/jep.29.3.3. 101 “Do you think when my grandfather”: Brian Scott, “55 Years of Agricultural Evolution,” Farmer’s Life (blog), November 9, 2015, http://thefarmerslife.com/55-years-of-agricultural-evolution-in-john-deere-combines. 102 Kiva was bought by Amazon in 2012: John Letzing, “Amazon Adds That Robotic Touch,” Wall Street Journal, March 20, 2012, http://www.wsj.com/articles/SB10001424052702304724404577291903244796214. 103 When Gill Pratt was a program manager at DARPA: John Dzieza, “Behind the Scenes at the Final DARPA Robotics Challenge,” Verge, June 12, 2015, http://www.theverge.com/2015/6/12/8768871/darpa-robotics-challenge-2015-winners. 104 250 million tons: PlasticsEurope, “Plastics—the Facts 2014/2015: An Analysis of European Plastics Production, Demand and Waste Data,” 2015, http://www.plasticseurope.org/documents/document/20150227150049-final_plastics_the_facts_2014_2015_260215.pdf. 105 About thirty years ago: PlasticsEurope, “Automotive: The World Moves with Plastics,” 2013, http://www.plasticseurope.org/cust/documentrequest.aspx?

Information gained from these daily flyovers enables a much deeper understanding of change over time with a given crop, and also enables much more precise targeting of water, fertilizer, and pesticides. Modern agricultural equipment often has the capability to deliver varying amounts of these critical ingredients foot by foot, rather than laying down a uniform amount. Drone data helps make the most of this capability, enabling farmers to move deeper into the era of precision agriculture. It’s likely that drones will soon also be used by insurance companies to assess how badly a roof was damaged after a tornado, to help guard herds of endangered animals against poaching and remote forests against illegal logging, and for many other tasks. They’re already being used to inspect equipment that would be dull, dirty, dangerous, or dear to get to. Sky Futures, a UK company, specializes in flying its drones around oil rigs in the North Sea, where metal and cement are no match over time for salt water and harsh weather.


The Ages of Globalization by Jeffrey D. Sachs

Admiral Zheng, British Empire, Cape to Cairo, colonial rule, Columbian Exchange, Commentariolus, coronavirus, COVID-19, Covid-19, cuban missile crisis, decarbonisation, demographic transition, Deng Xiaoping, domestication of the camel, Donald Trump, en.wikipedia.org, endogenous growth, European colonialism, global supply chain, greed is good, income per capita, invention of agriculture, invention of gunpowder, invention of movable type, invention of the steam engine, invisible hand, Isaac Newton, James Watt: steam engine, job automation, John von Neumann, joint-stock company, Louis Pasteur, low skilled workers, mass immigration, Nikolai Kondratiev, out of africa, packet switching, Pax Mongolica, precision agriculture, profit maximization, profit motive, purchasing power parity, South China Sea, spinning jenny, The inhabitant of London could order by telephone, sipping his morning tea in bed, the various products of the whole earth, The Wealth of Nations by Adam Smith, trade route, transatlantic slave trade, Turing machine, Turing test, urban planning, Watson beat the top human players on Jeopardy!, wikimedia commons

Another opportunity is the shift in diet from heavy meat eating, especially beef eating, toward the use of more plant proteins, which would improve human health while also reducing the pressures on land for feed grains and pastures. A third opportunity is improved building designs, which can greatly reduce the need for heating and cooling and thereby the demand for energy. A fourth opportunity is precision agriculture, meaning more precise applications of water and fertilizers—for example, through drip irrigation and fertigation (direct injection of the fertilizers via the irrigation system). The key to sustainability, in short, is the transformation of technologies and behaviors (such as plant-based diets, or choosing walking over driving) that can deliver the same GDP or higher GDP with a lower environmental impact.

Environmental degradation is rampant, a reflection of a global economy that has reached nearly $100 trillion in annual output without taking care to ensure that the impacts on the planet are kept to a safe and sustainable level. And the risk of conflict is rising, especially given the rapid shifts in geopolitics, and the anxieties that are being created in the US, China, and elsewhere. All is not lost—not by a longshot. Humanity has the low-impact technologies (such as renewable energy and precision agriculture) and the policy knowhow needed to head off the environmental crises. We also have the benefit of global experience, if we choose to use it, to redistribute income from the rich to the poor, while finding diplomatic solutions to rising geopolitical tensions. We even have a new globally agreed approach to governance—sustainable development—that can provide a roadmap for action. The next and final chapter looks forward to see how we can achieve the goals of prosperity, social justice, environmental sustainability, and peace, that all the world has adopted. 9 Guiding Globalization in the Twenty-First Century Each age of globalization has given rise to new tensions and wars.


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

Albert Einstein, bank run, banking crisis, battle of ideas, Black Swan, call centre, carbon footprint, cashless society, citizen journalism, commoditize, computer age, computer vision, congestion charging, corporate governance, corporate social responsibility, deglobalization, digital Maoism, disintermediation, epigenetics, failed state, financial innovation, Firefox, food miles, future of work, global pandemic, global supply chain, global village, hive mind, 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, peak oil, pensions crisis, precision agriculture, prediction markets, Ralph Nader, Ray Kurzweil, rent control, RFID, Richard Florida, self-driving car, speech recognition, telepresence, the scientific method, The Wisdom of Crowds, Thomas Kuhn: the structure of scientific revolutions, Turing test, Victor Gruen, white flight, women in the workforce, Zipcar

Is “fish ranching” a good thing? When compared with people not having enough to eat, probably yes; and while there are some very real concerns about semi-farmed fish mingling with the wild variety, people are ultimately more important than fish — or at least, human lives are more important than the genetic purity of plants or animals. It’s progress; get over it. Back on dry land we’ll see some dramatic changes too. “Precision agriculture” is an idea whereby farmland is monitored 182 FUTURE FILES and controlled meter by meter, with seeds sown at exactly the correct time and fertilizers and pesticides applied almost on a plantby-plant basis. Similar techniques exist for cattle, allowing individual herds to be monitored and controlled by satellite and the history of an individual animal to be tracked from paddock to plate.

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


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The Fourth Industrial Revolution by Klaus Schwab

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

Researchers are already working on 4D, a process that would create a new generation of self-altering products capable of responding to environmental changes such as heat and humidity. This technology could be used in clothing or footwear, as well as in health-related products such as implants designed to adapt to the human body. Advanced robotics Until recently, the use of robots was confined to tightly controlled tasks in specific industries such as automotive. Today, however, robots are increasingly used across all sectors and for a wide range of tasks from precision agriculture to nursing. Rapid progress in robotics will soon make collaboration between humans and machines an everyday reality. Moreover, because of other technological advances, robots are becoming more adaptive and flexible, with their structural and functional design inspired by complex biological structures (an extension of a process called biomimicry, whereby nature’s patterns and strategies are imitated).


pages: 181 words: 52,147

The Driver in the Driverless Car: How Our Technology Choices Will Create the Future by Vivek Wadhwa, Alex Salkever

23andMe, 3D printing, Airbnb, artificial general intelligence, augmented reality, autonomous vehicles, barriers to entry, Bernie Sanders, bitcoin, blockchain, clean water, correlation does not imply causation, distributed ledger, Donald Trump, double helix, Elon Musk, en.wikipedia.org, epigenetics, Erik Brynjolfsson, Google bus, Hyperloop, income inequality, Internet of things, job automation, Kevin Kelly, Khan Academy, Kickstarter, Law of Accelerating Returns, license plate recognition, life extension, longitudinal study, Lyft, M-Pesa, Menlo Park, microbiome, mobile money, new economy, personalized medicine, phenotype, precision agriculture, RAND corporation, Ray Kurzweil, recommendation engine, Ronald Reagan, Second Machine Age, self-driving car, Silicon Valley, Skype, smart grid, stem cell, Stephen Hawking, Steve Wozniak, Stuxnet, supercomputer in your pocket, Tesla Model S, The Future of Employment, Thomas Davenport, Travis Kalanick, Turing test, Uber and Lyft, Uber for X, uber lyft, uranium enrichment, Watson beat the top human players on Jeopardy!, zero day

If a small factory needed spare parts from the nearest distributor, then a direct flight by a drone would trump a FedEx delivery both in cost and in speed. There are also tremendous applications of drones to agriculture, such as monitoring the growth of weeds and crops, spraying insecticides when needed, and tracking soil hydration to adjust watering. Drones can enable a process known as precision agriculture, which optimizes the use of resources and reduces the amount of runoff that could flow into nearby rivers and streams. The Darker Side to Drones In June 2015, a hobby drone flew into the path of an air tanker fighting a 17,000-acre forest fire in California, causing the state fire agency Cal Fire to ground all nearby air operations for the evening.6 The incidence of such dangerous drone near-misses is on the rise.


pages: 1,034 words: 241,773

Enlightenment Now: The Case for Reason, Science, Humanism, and Progress by Steven Pinker

3D printing, access to a mobile phone, affirmative action, Affordable Care Act / Obamacare, agricultural Revolution, Albert Einstein, Alfred Russel Wallace, anti-communist, Anton Chekhov, Arthur Eddington, artificial general intelligence, availability heuristic, Ayatollah Khomeini, basic income, Berlin Wall, Bernie Sanders, Black Swan, Bonfire of the Vanities, business cycle, capital controls, Capital in the Twenty-First Century by Thomas Piketty, carbon footprint, clean water, clockwork universe, cognitive bias, cognitive dissonance, Columbine, conceptual framework, correlation does not imply causation, creative destruction, crowdsourcing, cuban missile crisis, Daniel Kahneman / Amos Tversky, dark matter, decarbonisation, deindustrialization, dematerialisation, demographic transition, Deng Xiaoping, distributed generation, diversified portfolio, Donald Trump, Doomsday Clock, double helix, effective altruism, Elon Musk, en.wikipedia.org, end world poverty, endogenous growth, energy transition, European colonialism, experimental subject, Exxon Valdez, facts on the ground, Fall of the Berlin Wall, first-past-the-post, Flynn Effect, food miles, Francis Fukuyama: the end of history, frictionless, frictionless market, germ theory of disease, Gini coefficient, Hans Rosling, hedonic treadmill, helicopter parent, Hobbesian trap, humanitarian revolution, Ignaz Semmelweis: hand washing, income inequality, income per capita, Indoor air pollution, Intergovernmental Panel on Climate Change (IPCC), invention of writing, Jaron Lanier, Joan Didion, job automation, Johannes Kepler, John Snow's cholera map, Kevin Kelly, Khan Academy, knowledge economy, l'esprit de l'escalier, Laplace demon, life extension, long peace, longitudinal study, Louis Pasteur, Martin Wolf, mass incarceration, meta analysis, meta-analysis, Mikhail Gorbachev, minimum wage unemployment, moral hazard, mutually assured destruction, Naomi Klein, Nate Silver, Nathan Meyer Rothschild: antibiotics, Nelson Mandela, New Journalism, Norman Mailer, nuclear winter, obamacare, open economy, Paul Graham, peak oil, Peter Singer: altruism, Peter Thiel, precision agriculture, prediction markets, purchasing power parity, Ralph Nader, randomized controlled trial, Ray Kurzweil, rent control, Republic of Letters, Richard Feynman, road to serfdom, Robert Gordon, Rodney Brooks, rolodex, Ronald Reagan, Rory Sutherland, Saturday Night Live, science of happiness, Scientific racism, Second Machine Age, secular stagnation, self-driving car, sharing economy, Silicon Valley, Silicon Valley ideology, Simon Kuznets, Skype, smart grid, sovereign wealth fund, stem cell, Stephen Hawking, Steven Pinker, Stewart Brand, Stuxnet, supervolcano, technological singularity, Ted Kaczynski, The Rise and Fall of American Growth, the scientific method, The Signal and the Noise by Nate Silver, The Spirit Level, The Wealth of Nations by Adam Smith, The Wisdom of Crowds, Thomas Kuhn: the structure of scientific revolutions, Thomas Malthus, total factor productivity, union organizing, universal basic income, University of East Anglia, Unsafe at Any Speed, Upton Sinclair, uranium enrichment, urban renewal, War on Poverty, We wanted flying cars, instead we got 140 characters, women in the workforce, working poor, World Values Survey, Y2K

Alexander, A. C., & Welzel, C. 2011. Islam and patriarchy: How robust is Muslim support for patriarchal values? International Review of Sociology, 21, 249–75. Alexander, S. 2016. You are still crying wolf. Slate Star Codex, Nov. 18. http://slatestarcodex.com/2016/11/16/youarestillcryingwolf/. Alferov, Z. I., Altman, S., & 108 other Nobel Laureates. 2016. Laureates’ letter supporting precision agriculture (GMOs). http://supportprecisionagriculture.org/nobel-laureate-gmo-letter_rjr.html. Allen, P. G. 2011. The singularity isn’t near. Technology Review, Oct. 12. Allen, W. 1987. Hannah and her sisters. New York: Random House. Alrich, M. 2001. History of workplace safety in the United States, 1880–1970. In R. Whaples, ed., EH.net Encyclopedia. http://eh.net/encyclopedia/history-of-workplace-safety-in-the-united-states-1880-1970/.

At various times, farmers have pivoted to slash-and-burn horticulture, night soil (a euphemism for human feces), crop rotation, guano, saltpeter, ground-up bison bones, chemical fertilizer, hybrid crops, pesticides, and the Green Revolution.20 Future pivots may include genetically modified organisms, hydroponics, aeroponics, urban vertical farms, robotic harvesting, meat cultured in vitro, artificial intelligence algorithms fed by GPS and biosensors, the recovery of energy and fertilizer from sewage, aquaculture with fish that eat tofu instead of other fish, and who knows what else—as long as people are allowed to indulge their ingenuity.21 Though water is one resource that people will never pivot away from, farmers could save massive amounts if they switched to Israeli-style precision farming. And if the world develops abundant carbon-free energy sources (a topic we will explore later), it could get what it needs by desalinating seawater.22 * * * Not only have the disasters prophesied by 1970s greenism failed to take place, but improvements that it deemed impossible have taken place. As the world has gotten richer and crested the environmental curve, nature has begun to rebound.23 Pope Francis’s “immense pile of filth” is the vision of someone who has woken up thinking it’s 1965, the era of belching smokestacks, waterfalls of sewage, rivers catching fire, and jokes about New Yorkers not liking to breathe air they can’t see.


Enriching the Earth: Fritz Haber, Carl Bosch, and the Transformation of World Food Production by Vaclav Smil

agricultural Revolution, Albert Einstein, demographic transition, Deng Xiaoping, Haber-Bosch Process, invention of gunpowder, Louis Pasteur, Pearl River Delta, precision agriculture, recommendation engine, The Design of Experiments

A counterintuitive result regarding fertilizer placement emerged from a study in Missouri that demonstrated that with adequate water supply applications of nitrogen, and water, in alternate furrows produced a harvest at least equivalent or even higher than those resulting from fertilizing every furrow.17 Cheaper microcomputers and the commercial availability of global positioning systems (GPS) opened up the possibility of site-specific applications of fertilizers. Rather than choosing the fertilizer amount according to average conditions within a field, precision farming adjusts the applied amount according not only to field-tofield variations in soil quality but also to often substantial differences of nutrient content within a single field.18 Maximized yields and profits and minimized nitrogen applications, and hence reduced nutrient losses to the environment, should be the ideal outcome. Evaluations of recent experiments with precision farming have ranged from highly encouraging results to no significant difference when compared with standard practices to unprofitable experiences, but there is little doubt that the technique will be pursued and perfected in the future.19 A totally different approach to increasing the efficiency of fertilizing is to slow down the rate of nitrification, and hence to reduce the water-borne losses of the nutrient.

Field soil sampling density for variable rate fertilization. Journal of Production Agriculture 8:568–674; Lu, Y., et al. 1997. The current state of precision farming. Food Reviews International 13(2):141–162; Wollring, J., et al. 1998. Variable Nitrogen Application Based on Crop Sensing. York: International Fertiliser Society. Notes to Chapter 10 319 19. Wibawa, W. D., et al. 1993. Variable fertilizer application based on yield goal, soil fertility, and soil map unit. Journal of Production Agriculture 6:255–261; Lowenberg-DeBoer, J., and S. M. Swinton. 1995. Economics of Site-Specific Management in Agronomic Crops. East Lansing: Department of Agricultural Economics, Michigan State University; Fenton, J. P. 1998. On-Farm Experience of Precision Farming. York: International Fertiliser Society. 20. Prasad, R., and J. F. Power. 1995. Nitrification inhibitors for agriculture, health, and the environment.

.: Lewis Publishers, pp. 137–204. 10. FAO. 1980. Maximizing the Efficiency of Fertilizer Use by Grain Crops. Rome: FAO; FAO. 1983. Maximizing Fertilizer Use Efficiency. Rome: FAO; Hargrove, W. L., ed. 1988. Cropping Strategies for Efficient Use of Water and Nitrogen. Madison, Wis.: American Society of Agronomy; Munson, R. D., and C. F. Runge. 1990. Improving Fertilizer and Chemical Efficiency Through ‘‘High Precision Farming.’’ Center for International Food and Agricultural Policy, St. Paul, Minn.: University of Minnesota; Fragoso, M. A., ed. 1993. Optimization of Plant Nutrition. Amsterdam: Kluwer; Dudal, R. and R. N. Roy, eds. 1995. Integrated Plant Nutrition Systems. Rome: FAO; Prasad, R., and J. F. Power. 1997. Soil Fertility Management 318 Notes to Chapter 10 for Sustainable Agriculture. Boca Raton, Fla.: Lewis Publishing; Trenkel, M.


pages: 400 words: 88,647

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, Bretton Woods, business climate, business process, call centre, Capital in the Twenty-First Century by Thomas Piketty, carbon footprint, cloud computing, collaborative consumption, collaborative economy, Computer Numeric Control, connected car, corporate social responsibility, creative destruction, crowdsourcing, disruptive innovation, Elon Musk, financial exclusion, financial innovation, 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, low cost carrier, M-Pesa, Mahatma Gandhi, megacity, minimum viable product, more computing power than Apollo, new economy, payday loans, peer-to-peer lending, Peter H. Diamandis: Planetary Resources, precision agriculture, race to the bottom, reshoring, risk tolerance, Ronald Coase, self-driving car, shareholder value, sharing economy, Silicon Valley, Silicon Valley startup, six sigma, smart grid, smart meter, software as a service, standardized shipping container, Steve Jobs, supply-chain management, TaskRabbit, The Fortune at the Bottom of the Pyramid, The Nature of the Firm, transaction costs, Travis Kalanick, unbanked and underbanked, underbanked, women in the workforce, X Prize, yield management, Zipcar

Use financial measurements to change customers’ own business model Asking customers to dramatically change their behaviour is akin to asking a company to change its business model. This only happens if the new model might significantly improve the bottom line. Changing a business model also requires investment, which must come with an attractive return. This analogy can help frugal producers convince customers to change their personal business model by showing them the relevant return on investment. For example, gThrive, a Silicon Valley start-up, offers precision agriculture services to farmers in drought-prone California. It sells gStakes, maintenance-free wireless sensors designed like a lightweight plastic ruler, which, when inserted in various parts of a field, frequently measure and track soil and environmental conditions (moisture, air temperature, sunlight). This detailed data can be monitored remotely from a website, smartphone or tablet. This affordable, easy-to-use system has several benefits.


pages: 484 words: 104,873

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

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

* The company is not unaware of the potential impact its technology will have on jobs and, according to its website, plans to support a program that will offer discounted technical training to workers who are displaced. * Economists categorize fast food as part of the service sector; however, from a technical standpoint it is really closer to being a form of just-in-time manufacturing. * Google’s strong interest in robotics was further demonstrated in 2013, when the company purchased eight robotics start-up companies over a six-month period. Among the companies acquired was Industrial Perception. * Precision agriculture—or the ability to keep track of and manage individual plants or even fruits—is part of the “big data” phenomenon, a subject that we’ll examine in more depth in Chapter 4. Chapter 2 IS THIS TIME DIFFERENT? On the morning of Sunday, March 31, 1968, the Reverend Martin Luther King, Jr., stood in the elaborately carved limestone pulpit at Washington National Cathedral. The building—one of the largest churches in the world and over twice the size of London’s Westminster abbey—was filled to capacity with thousands of people packed into the nave and transept, looking down from the choir loft, and squeezed into doorways.


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Predator: The Secret Origins of the Drone Revolution by Richard Whittle

Berlin Wall, Charles Lindbergh, cuban missile crisis, drone strike, Francis Fukuyama: the end of history, Google Earth, indoor plumbing, Khyber Pass, Kickstarter, Mikhail Gorbachev, precision agriculture, Ronald Reagan, Silicon Valley, Yom Kippur War

Enabled by ever more accessible and affordable component technologies, a new generation of mini-drones quickly began gaining popularity. And just as it transformed the military and the CIA, the drone revolution also promises to reshape society, from the way our laws are enforced and how much privacy we enjoy, to the way our food is grown, our news is gathered, and our goods and services are bought, sold, and delivered. Law enforcement, wildfire management, precision agriculture, news and entertainment media, search and rescue, environmental research, disaster response—the list of potential uses for drones providing a bird’s-eye view of the world is nearly inexhaustible, the possibilities as boundless as the human imagination. For the moment, Federal Aviation Administration regulations limit the use of unmanned aircraft to hobbyists and government and academic entities granted a special certificate of authorization by the FAA.


pages: 918 words: 257,605

The Age of Surveillance Capitalism by Shoshana Zuboff

Amazon Web Services, Andrew Keen, augmented reality, autonomous vehicles, barriers to entry, Bartolomé de las Casas, Berlin Wall, bitcoin, blockchain, blue-collar work, book scanning, Broken windows theory, California gold rush, call centre, Capital in the Twenty-First Century by Thomas Piketty, Cass Sunstein, choice architecture, citizen journalism, cloud computing, collective bargaining, Computer Numeric Control, computer vision, connected car, corporate governance, corporate personhood, creative destruction, cryptocurrency, dogs of the Dow, don't be evil, Donald Trump, Edward Snowden, en.wikipedia.org, Erik Brynjolfsson, facts on the ground, Ford paid five dollars a day, future of work, game design, Google Earth, Google Glasses, Google X / Alphabet X, hive mind, impulse control, income inequality, Internet of things, invention of the printing press, invisible hand, Jean Tirole, job automation, Johann Wolfgang von Goethe, John Markoff, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, Joseph Schumpeter, Kevin Kelly, knowledge economy, linked data, longitudinal study, low skilled workers, Mark Zuckerberg, market bubble, means of production, multi-sided market, Naomi Klein, natural language processing, Network effects, new economy, Occupy movement, off grid, PageRank, Panopticon Jeremy Bentham, pattern recognition, Paul Buchheit, performance metric, Philip Mirowski, precision agriculture, price mechanism, profit maximization, profit motive, recommendation engine, refrigerator car, RFID, Richard Thaler, ride hailing / ride sharing, Robert Bork, Robert Mercer, Second Machine Age, self-driving car, sentiment analysis, shareholder value, Shoshana Zuboff, Silicon Valley, Silicon Valley ideology, Silicon Valley startup, slashdot, smart cities, Snapchat, social graph, social web, software as a service, speech recognition, statistical model, Steve Jobs, Steven Levy, structural adjustment programs, The Future of Employment, The Wealth of Nations by Adam Smith, Tim Cook: Apple, two-sided market, union organizing, Watson beat the top human players on Jeopardy!, winner-take-all economy, Wolfgang Streeck

Our hope is that this model provides examples of how collective decision-making may work in other aspects of the global community.”21 Later that year, Zuckerberg told an audience of developers that “we have a full roadmap of products to help build groups and community, help build a more informed society, help keep our communities safe, and we have a lot more to do here.”22 Back on that stage in the spring of 2017, Microsoft’s Nadella encouraged his developers: “Whether it’s precision medicine or precision agriculture, whether it’s digital media or the industrial internet, the opportunity for us as developers to have broad, deep impact on all parts of society and all parts of the economy has never been greater.”23 The vision that Nadella unveiled that day is emblematic of the wider surveillance capitalist template for our futures. Where do they think they are taking us? IV. Confluence as Machine Relations In order to decipher the true measure of an instrumentarian society, let’s set aside the razzle-dazzle of a “magic age” and focus instead on the practices of applied utopistics and the social vision they imply.


pages: 348 words: 102,438

Green and Prosperous Land: A Blueprint for Rescuing the British Countryside by Dieter Helm

3D printing, Airbnb, barriers to entry, British Empire, clean water, conceptual framework, corporate social responsibility, decarbonisation, deindustrialization, demographic transition, Diane Coyle, digital map, facts on the ground, food miles, Haber-Bosch Process, illegal immigration, Internet of things, Kickstarter, land reform, mass immigration, New Urbanism, North Sea oil, precision agriculture, quantitative easing, smart meter, sovereign wealth fund, the built environment, urban planning, urban sprawl

If and when glyphosate is banned, or when weed resistance to it begins to pose a significant threat, substitute chemicals can be relied upon to take its place. The result will be a more silent and browner environment. The countryside becomes more and more industrialised. To these incremental technological advances, two new and transformational ones are being added, together already further changing the face of agriculture. These are digitalisation and genetics. Digitalisation enables both precision farming based on big data, and a further switch away from labour to robotics, 3D printing and AI. Genetics means that centuries of careful plant and animal breeding can be leapfrogged in a test tube. The very building blocks of species can be manipulated and changed, and all at a fast pace. These two changes are probably each more profound than the switch from horse power to tractors. Together they herald a very big revolution.


pages: 406 words: 109,794

Range: Why Generalists Triumph in a Specialized World by David Epstein

Airbnb, Albert Einstein, Apple's 1984 Super Bowl advert, Atul Gawande, Checklist Manifesto, Claude Shannon: information theory, Clayton Christensen, clockwork universe, cognitive bias, correlation does not imply causation, Daniel Kahneman / Amos Tversky, deliberate practice, Exxon Valdez, Flynn Effect, Freestyle chess, functional fixedness, game design, Isaac Newton, Johannes Kepler, knowledge economy, lateral thinking, longitudinal study, Louis Pasteur, Mark Zuckerberg, medical residency, meta analysis, meta-analysis, Mikhail Gorbachev, Nelson Mandela, Netflix Prize, pattern recognition, Paul Graham, precision agriculture, prediction markets, premature optimization, pre–internet, random walk, randomized controlled trial, retrograde motion, Richard Feynman, Richard Feynman: Challenger O-ring, Silicon Valley, Stanford marshmallow experiment, Steve Jobs, Steve Wozniak, Steven Pinker, Walter Mischel, Watson beat the top human players on Jeopardy!, Y Combinator, young professional

The launch vehicle was slightly damaged, but fortunately the probe was intact. Four months later, in April 2004, GP-B finally took off. It was the first direct test to support Einstein’s idea that Earth drags the fabric of space-time around with it as it spins. The technology left a greater legacy. Components designed for Gravity Probe B improved digital cameras and satellites; the centimeter-accurate GPS was applied to automatic aircraft landing systems and precision farming. The following year, a new NASA administrator was appointed by the president. The new administrator demanded the kind of individualism and opinionated debate that could serve as a cross-pressure for NASA’s robust process accountability. He made Geveden the associate administrator, essentially the COO of NASA, and the highest position in the agency that is not politically appointed. * * * — In 2017, Geveden took his lessons to a new role as CEO of BWX Technologies, a company whose wide purview includes nuclear propulsion technology that could power a manned Mars mission.


pages: 407 words: 116,726

Infinite Powers: How Calculus Reveals the Secrets of the Universe by Steven Strogatz

Albert Einstein, Asperger Syndrome, Astronomia nova, Bernie Sanders, clockwork universe, complexity theory, cosmological principle, Dava Sobel, double helix, Edmond Halley, Eratosthenes, four colour theorem, fudge factor, Henri Poincaré, invention of the telescope, Isaac Newton, Islamic Golden Age, Johannes Kepler, John Harrison: Longitude, Khan Academy, Laplace demon, lone genius, music of the spheres, pattern recognition, Paul Erdős, Pierre-Simon Laplace, precision agriculture, retrograde motion, Richard Feynman, Socratic dialogue, Solar eclipse in 1919, Steve Jobs, the rule of 72, the scientific method

The global positioning system was developed by the US military during the Cold War. The original intent was to keep track of US submarines carrying nuclear missiles and give them precise estimates of their current locations so that if they needed to launch a nuclear strike, they could target their intercontinental ballistic missiles very accurately. Peacetime applications of GPS nowadays include precision farming, blind landings of airplanes in heavy fog, and enhanced 911 systems that automatically calculate the fastest routes for ambulances and fire trucks. But GPS is more than a location and guidance system. It allows time synchronization to within a hundred nanoseconds, which is useful for coordinating bank transfers and other financial transactions. It also keeps wireless phone and data networks in sync, allowing them to share the frequencies in the electromagnetic spectrum more efficiently.


Autonomous Driving: How the Driverless Revolution Will Change the World by Andreas Herrmann, Walter Brenner, Rupert Stadler

Airbnb, Airbus A320, augmented reality, autonomous vehicles, blockchain, call centre, carbon footprint, cleantech, computer vision, conceptual framework, connected car, crowdsourcing, cyber-physical system, DARPA: Urban Challenge, data acquisition, demand response, digital map, disruptive innovation, Elon Musk, fault tolerance, fear of failure, global supply chain, industrial cluster, intermodal, Internet of things, Jeff Bezos, Lyft, manufacturing employment, market fundamentalism, Mars Rover, Masdar, megacity, Pearl River Delta, peer-to-peer rental, precision agriculture, QWERTY keyboard, RAND corporation, ride hailing / ride sharing, self-driving car, sensor fusion, sharing economy, Silicon Valley, smart cities, smart grid, smart meter, Steve Jobs, Tesla Model S, Tim Cook: Apple, uber lyft, upwardly mobile, urban planning, Zipcar

The time and place of loading can be determined with consideration of the level of grain in the harvester’s Fields 155 Box 14.1. Statement by Markwart von Pentz Markwart von Pentz, President Agriculture and Turf, Europe, Asia, Africa, John Deere & Company Agricultural productivity can be significantly increased with autonomous vehicles (tractors, combine harvesters etc.). The development of self-driving tractors, combine harvesters and other vehicles is embedded in the precision farming system at John Deere. The objective is to improve agricultural productivity with the application of information technology. Autonomous vehicles can be controlled so exactly that lane overlaps are a maximum of 1 centimetre at a speed of up to 40 kilometres per hour (25 miles per hour). This leads to significant fuel savings’ reductions in the amount of seed and fertilizer used, which increases productivity by 10 per cent. 90 per cent of large machines are already equipped with this technology, and due to falling prices, it is worthwhile using self-driving vehicles in smaller and smaller fields.


pages: 482 words: 121,173

Tools and Weapons: The Promise and the Peril of the Digital Age by Brad Smith, Carol Ann Browne

Affordable Care Act / Obamacare, AI winter, airport security, Albert Einstein, augmented reality, autonomous vehicles, barriers to entry, Berlin Wall, Boeing 737 MAX, business process, call centre, Celtic Tiger, chief data officer, cloud computing, computer vision, corporate social responsibility, Donald Trump, Edward Snowden, en.wikipedia.org, immigration reform, income inequality, Internet of things, invention of movable type, invention of the telephone, Jeff Bezos, Mark Zuckerberg, minimum viable product, national security letter, natural language processing, Network effects, new economy, pattern recognition, precision agriculture, race to the bottom, ransomware, Ronald Reagan, Rubik’s Cube, school vouchers, self-driving car, Shoshana Zuboff, Silicon Valley, Skype, speech recognition, Steve Ballmer, Steve Jobs, The Rise and Fall of American Growth, Tim Cook: Apple, WikiLeaks, women in the workforce

Their research suggests that the Pew numbers are much closer to the mark than the estimate from the FCC.9 But even more than that, this leaves us with the inescapable conclusion that today there exists no fully accurate estimate of broadband availability in the United States, anywhere. Does this matter? You bet, and in a big way. Broadband has become the electricity of the twenty-first century. It’s fundamental to the way people work, live, and learn. The future of medicine is telemedicine. The future of education is online education. And the future of agriculture is precision farming. Even with a future where there is more computing intelligence “at the edge”—meaning with ubiquitous small and powerful devices that process more data themselves—there still needs to be some high-speed access to the cloud. And that requires broadband. Today, rural areas that lack broadband are still living in the twentieth century. And it shows in almost every economic indicator. Our data science team confirmed what universities and research institutions around the world have been finding: The highest unemployment rates in the country are frequently located in the counties with the lowest availability of broadband, highlighting the strong link between broadband availability and economic growth.10 When you talk to business leaders about where they might expand their operations and add jobs, this requirement surfaces almost immediately.