DARPA: Urban Challenge

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Cities Under Siege: The New Military Urbanism by Stephen Graham

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airport security, anti-communist, autonomous vehicles, Berlin Wall, call centre, carbon footprint, clean water, congestion charging, credit crunch, DARPA: Urban Challenge, defense in depth, deindustrialization, edge city, energy security, European colonialism, failed state, Food sovereignty, Gini coefficient, global supply chain, Google Earth, illegal immigration, income inequality, knowledge economy, late capitalism, loose coupling, market fundamentalism, McMansion, megacity, mutually assured destruction, Naomi Klein, New Urbanism, offshore financial centre, pattern recognition, peak oil, planetary scale, private military company, RAND corporation, RFID, Richard Florida, Scramble for Africa, Silicon Valley, smart transportation, surplus humans, The Bell Curve by Richard Herrnstein and Charles Murray, urban decay, urban planning, urban renewal, urban sprawl, Washington Consensus, white flight

After a close contest, with six finishers, the Tartan team, an alliance of General Motors and Pittsburgh’s Carnegie Mellon University, was declared the victor – gaining the $2 million first prize in part because their vehicle had not only finished the course but also complied with California traffic rules. 9.9 DARPA’sUrban Challenge’ competition in November 2007. Eleven fully robotized SUVs and other cars had to navigate a simulated urban course completely autonomously. 9.10 Estimates for the future introduction of fully autonomous military and civilian vehicles from the Urban Challenge presentations of Stanford University’s entry. Whilst driverless cars are unlikely to become available to consumers until 2030 at the earliest, the Urban Challenge robocars are already being displayed at car shows, billed as a way to ‘fortify road safety and eliminate driver error as the most common cause of crashes’.131 The already strong links between militarized robotic combat vehicles (Figure 9.10) and an increasingly militarized society where cars become increasingly automated and surveilled, will likely intensify.

Law Professor Jeffrey Rosen stresses that, in both London and New York, ‘there’s really a form of mission creep, and cameras that are accepted for one purpose are used for another’.126 Incremental experiments like those in London, New York, and on the US-Canadian border prefigure a much more substantial and systematic move towards intelligent automobility based on militarized robotic navigation technologies. For example, in an attempt to stimulate further development of robotic ground vehicles for use in both the US military and on the streets of US cities, the Pentagon’s high-tech R&D arm, the Defense Advanced Research Projects Agency (DARPA), has initiated a series of high-profile rob otic-vehicle competitions. The agency stressed that the aim of the 2007 competition, called ‘Urban Challenge’, was to develop ‘technology that will keep warfighters off the battlefield and out of harm’s way’.127 It was ‘the first time in history that truly autonomous vehicles met and (mostly) avoided each other on the open road’.128 The event required that competing teams build vehicles capable of driving autonomously in traffic, relying entirely on on-board sensors, cameras, radars, computers and GPS systems.

Widespread campaigns, drawing on a long history of such activism, have targeted the militarized R&D that is carried on in US universities and so firmly underpins securocratic war, ubiquitous bordering, and the Long War.57 Two of the main centres for work on the robotization of weapons–the Robotics Institute and its commercial arm, the National Robotics Engineering Center (NREC) – are at Carnegie Mellon University in Pittsburgh, and both have been the target of a jamming campaign (Figure 10.13). (In Chapter 9 we already encountered NREC: its ‘robocar’ was the winner of DARPA’s 2007 Urban Challenge competition.) The Carnegie Mellon campaign, labelled ‘Barricade the War Machine’, is challenging the take-over of engineering sciences in the university and the local economy by military-robotics research in the service of the military-industrial-academic complex. It is also raising the key ethical question forced by the shift to fully autonomous weapons systems (see Chapter 5): ‘Who bears moral responsibility for outcomes that are caused by autonomous robotic systems?’


pages: 413 words: 119,587

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

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

They would have no chance of winning, it was too hard, it would cost too much money. Thrun looked at Montemerlo and it was obvious that although on paper he was the quintessential pessimist, everything in his demeanor was saying yes. Sebastian Thrun (left) and Mike Montemerlo (right) in front of the Stanford University autonomous vehicle while it was being tested to take part in DARPA’s Urban Challenge in 2007. (Photo courtesy of the author) Soon afterward Thrun threw himself into the DARPA competition with passion. For the first time in his life he felt like he was focusing on something that was genuinely likely to have broad impact. Living in the Arizona desert for weeks on end, surviving on pizza, the team worked on the car until it was able to drive the backcountry roads flawlessly. Montemerlo and Thrun made a perfect team of opposites.

Viewing the event, in which the cars glided seemingly endlessly through a makeshift town previously used for training military troops in urban combat, it didn’t seem to be a race at all. It felt more like an afternoon of stop-and-go Sunday traffic in a science-fiction movie like Blade Runner. Indeed, by almost any standard it was an odd event. The DARPA Urban Challenge pitted teams of roboticists, artificial intelligence researchers, students, automotive engineers, and software hackers against each other in an effort to design and build robot vehicles capable of driving autonomously in an urban traffic setting. The event was the third in the series of contests that Tether organized. At the time military technology largely amplified a soldier’s killing power rather than replacing the soldier. Robotic military planes were flown by humans and, in some cases, by extraordinarily large groups of soldiers.

To bedevil the teams and create a real-world sense of crisis, DARPA throttled the data connection at regular intervals. This gave even the best robots a stuttering quality, and the assembled press hunted for metaphors less trite than “watching grass grow” or “watching paint dry” to describe the scene. Nevertheless, the DARPA Robotics Challenge did what it was designed to do: expose the limits of today’s robotic systems. Truly autonomous robots are not yet a reality. Even the prancing and trotting Boston Dynamics machines that performed on the racetrack tarmac were wirelessly tethered to human controllers. It is equally clear, however, that truly autonomous robots will arrive soon. Just as the autonomous vehicle challenges of 2004 through 2007 significantly accelerated the development of self-driving cars, the Robotics Challenge will bring us close to Gill Pratt’s dream of a robot that can work in hazardous environments and Andy Rubin’s vision of the automated Google delivery robot.


pages: 352 words: 104,411

Rush Hour by Iain Gately

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Albert Einstein, autonomous vehicles, Beeching cuts, blue-collar work, British Empire, business intelligence, business process, business process outsourcing, call centre, car-free, Clapham omnibus, cognitive dissonance, congestion charging, connected car, DARPA: Urban Challenge, Dean Kamen, decarbonisation, Deng Xiaoping, Detroit bankruptcy, don't be evil, Elon Musk, extreme commuting, Google bus, Henri Poincaré, Hyperloop, Jeff Bezos, low skilled workers, postnationalism / post nation state, Ralph Waldo Emerson, remote working, self-driving car, Silicon Valley, stakhanovite, Steve Jobs, telepresence, Tesla Model S, urban planning, éminence grise

Why send a soldier as well as a vehicle through a minefield? The Defense Advanced Research Projects Agency (DARPA), part of the US Department of Defense – hoping to inspire the creation of autonomous vehicles that might have martial applications – staged the DARPA Grand Challenges of 2004 and 2005, and the Urban Challenge of 2007, which offered million-dollar prizes and grants to teams who could create effective driverless cars. Various universities built entries, and while none met the challenge in 2004, four succeeded in 2005 and there were as many winners in the urban event. The grand challenges advanced autonomous technology by leaps and bounds, and also created a pool of engineering expertise, eager to take the concept further. The potential that the DARPA challengers had demonstrated revived commercial interest in driverless cars.

In the same speech in which CFO Patrick Pichette dismissed telecommuting, he also stated that, in an ideal world, ‘nobody should be driving cars… Look at factorial math and probabilities of everything that could go wrong, times the number of cars out there… That’s why you have gridlock… It makes no sense to make people drive cars.’ Google’s ambitions for autonomous vehicles reach beyond safety: Its lead developer Sebastian Thrun, a veteran of the DARPA ’05 Grand Challenge, sums them up as: (1) We can reduce traffic accidents by 90%. (2) We can reduce wasted commute time and energy by 90%. (3) We can reduce the number of cars by 90%. Although if you began with objective (3) you’d probably also succeed with (2) and (1) by default, progress the other way isn’t so simple. Testing has started nonetheless: Google’s initial fleet of ten driverless cars have clocked up over 300,000 miles between them.

Index a Achen Motor Company 315 Acton 43, 46 Acts of Parliament 17 Acworth, Sir William Mitchell 73 aeroplanes 307 America cars 90–101 commuting 224–5 railways 66–80 American Automobile Association (AAA) 198, 209–10 American Bicycle Co. 91 American Motors 120 American School Bus Council (ASBC) 236 Andrade, Claudio 279, 280 Apple 295–6 Australia 232 autobahn 103, 109, 151, 166 b Bagehot, Walter 59 Balfour, A.J. 65 Barter, David Obsessive Compulsive Cycling Disorder 168 Bazalgette, Joseph 60 Beeching, Dr Richard cuts 137, 146, 158, 313, 328 Beerbohm, Max 58 Beijing 160, 161 Metro 160, 162 Benz, Karl 90 Bern, Switzerland 86, 87 Besant, Sir Walter 57 Best Friend of Charleston crash 69 Betjeman, John 109, 135, 272–3 bicycle Boris bikes 167 Brompton 167 commuting in Britain 101, 138–9, 166–8, 216–17 commuting in Europe 166, 222 Flying Pigeon 161–2 penny farthing 101 Raleigh 139 Rover 101–2 Birmingham HS2 329 number 8 bus 141 Birt, William 61 Bishop’s Waltham 313, 327 Blake, William Marriage of Heaven and Hell 104 Booth, Henry 27 Boris bikes 167 Boston 69, 97 Boston and Worcester Line 72 Botley station, Hampshire 1, 2, 3–5, 7, 313, 334 Bowser, Sylvanus Freelove 95 Brazil 279 British Telecom 291–3 Bromley 23, 46 Brompton bike 167 Brunel, Isambard Kingdom 331 Buchanan, Professor Sir Colin Traffic in Towns 145–6 buses 48, 140–41, 235–6, 275–6 c California High Speed Rail (CHSR) 330, 331 Callan Automobile Law 95 carriages (railway) 29–30, 54, 55 in America 71–3 in France 83–4 WCs 33, 72, 226–7 women-only 188–9 ‘workmen’s trains’ 33–4, 60, 61, 83 cars 89–92, 195 commuting in America 101, 113, 116–17 in Britain 107, 142–4, 249–52 in communist countries 151–2 in Italy 149–50 congestion 192–5 congestion charge 312 driverless 316–17, 320–27 ownership 97–8, 100, 103, 125 radio 119, 255–8 SUVs 204–8 Central Railroad of Long Island 76 C5 (electric tricycle) 309–11 Chaplin, William James 15 Cheap Trains Act 61 Chesterton, G.K. 57, 105, 109 Chicago Automobile Club 96–7, 256 Great Fire of 1871 79 Oak Park suburb 79–80 Park Forest suburb 113–15 China 160–62, 314–15 Chrysler 119, 160 Churchill, Winston 308–9 City and South London Railway 54–5, 62 Clean Air Act 286–7 Cobbett, William 334 Collins, Wilkie Basil 52 commuting (car) see cars commuting (cycling) see cycling commuting (rail) comic representation of 137 commuter etiquette 72–3, 82, 249 extreme commuting 233–4 in America 66–80 in France 81–7 in Germany 80, 86–7 in Japan 177–84 in the 1950s 136 in Victorian times 33–9, 42 food in England 36–7, 247 in France 84–5 origin of the term 67 overcrowding 171–83 coronations 140 County Durham 14 Coventry 102 Crawshay, William 35 Croton Falls 66 Croydon 56 Cultural Revolution (China) 161 Cunarders 140 cycling commuting in Britain 101, 138–9, 166–8, 216–17 commuting in Europe 166, 222 Cyclists’ Touring Club 102–3 d Dagenham 107 Dahl, Roald 129, 135–6 Daimler, Gottlieb 90 Dalai Lama 210 Darwin, Charles 13, 32 Daudet, Alphonse 83–4 Daumier, Honoré The Third-Class Carriage 83 The New Paris 86 Landscapists at Work 86 Defense Advance Research Projects Agency (DARPA) 317, 318 Delhi 211–13 Deng Xiaoping 161, 162 Denmark 222, 288 Detroit 110, 121, 123–4 ‘Detroit by the Volga’ 153 Dickens, Charles 12, 25, 50 food 36–7, 84–5, 247 Mugby Junction 84–5 Great Expectations 12 Our Mutual Friend 50 train travel in America 70, 71, 74 Diggins, John 3 Docklands Light Railway (DLR) 279 Downing, Andrew Jackson 66 driverless cars 316–17, 320–27 driving schools 215–16 driving tests New York State 94–5 UK 216 Duluth, Minnesota 79–80 e Ealing, London 38, 40, 42, 46, 56 Eden, Emily 58 Edinburgh 13, 14, 16, 329 Edmondson, Brad 314 Einstein, Albert 87 Eliot, William G.


pages: 523 words: 148,929

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

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agricultural Revolution, AI winter, Albert Einstein, augmented reality, Bill Joy: nanobots, bioinformatics, blue-collar work, British Empire, Brownian motion, cloud computing, Colonization of Mars, DARPA: Urban Challenge, delayed gratification, double helix, Douglas Hofstadter, en.wikipedia.org, friendly AI, Gödel, Escher, Bach, hydrogen economy, I think there is a world market for maybe five computers, industrial robot, invention of movable type, invention of the telescope, Isaac Newton, John von Neumann, life extension, Louis Pasteur, Mahatma Gandhi, Mars Rover, megacity, Murray Gell-Mann, new economy, oil shale / tar sands, optical character recognition, pattern recognition, planetary scale, postindustrial economy, Ray Kurzweil, refrigerator car, Richard Feynman, Richard Feynman, Rodney Brooks, Ronald Reagan, Search for Extraterrestrial Intelligence, Silicon Valley, Simon Singh, speech recognition, stem cell, Stephen Hawking, Steve Jobs, telepresence, The Wealth of Nations by Adam Smith, Thomas L Friedman, Thomas Malthus, trade route, Turing machine, uranium enrichment, Vernor Vinge, Wall-E, Walter Mischel, Whole Earth Review, X Prize

They had to drive on roads that included 100 sharp turns, three narrow tunnels, and paths with sheer drop-offs on either side. Some critics said that robotic cars might be able to travel in the desert but never in midtown traffic. So in 2007, DARPA sponsored an even more ambitious project, the Urban Challenge, in which robotic cars had to complete a grueling 60-mile course through mock-urban territory in less than six hours. The cars had to obey all traffic laws, avoid other robot cars along the course, and negotiate four-way intersections. Six teams successfully completed the Urban Challenge, with the top three claiming the $2 million, $1 million, and $500,000 prizes. The Pentagon’s goal is to make fully one-third of the U.S. ground forces autonomous by 2015. This could prove to be a lifesaving technology, since recently most U.S. casualties have been from roadside bombs.

Scientists hope to incorporate some of these lessons from nature by designing swarm-bots that might one day journey to other planets and stars. This is similar to the hypothetical concept of smart dust being pursued by the Pentagon: billions of particles sent into the air, each one with tiny sensors to do reconnaissance. Each sensor is not very intelligent, but collectively they can relay back mountains of information. The Pentagon’s DARPA has funded this research for possible military applications, such as monitoring enemy positions on the battlefield. In 2007 and 2009, the Air Force released position papers detailing plans for the coming decades, outlining everything from advanced versions of the Predator (which today cost $4.5 million apiece) to swarms of tiny sensors smaller than a moth costing pennies. Scientists are also interested in this concept. They might want to spray smart dust to instantly monitor thousands of locations during hurricanes, thunderstorms, volcanic eruptions, earthquakes, floods, forest fires, and other natural phenomena.

DRIVERLESS CAR In the near future, you will also be able to safely surf the Web via your contact lens while driving a car. Commuting to work won’t be such an agonizing chore because cars will drive themselves. Already, driverless cars, using GPS to locate their position within a few feet, can drive over hundreds of miles. The Pentagon’s Defense Advanced Research Projects Agency (DARPA) sponsored a contest, called the DARPA Grand Challenge, in which laboratories were invited to submit driverless cars for a race across the Mojave Desert to claim a $1 million prize. DARPA was continuing its long-standing tradition of financing risky but visionary technologies. (Some examples of Pentagon projects include the Internet, which was originally designed to connect scientists and officials during and after a nuclear war, and the GPS system, which was originally designed to guide ICBM missiles.


pages: 574 words: 164,509

Superintelligence: Paths, Dangers, Strategies by Nick Bostrom

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agricultural Revolution, AI winter, Albert Einstein, algorithmic trading, anthropic principle, anti-communist, artificial general intelligence, autonomous vehicles, barriers to entry, bioinformatics, brain emulation, cloud computing, combinatorial explosion, computer vision, cosmological constant, dark matter, DARPA: Urban Challenge, data acquisition, delayed gratification, demographic transition, Douglas Hofstadter, Drosophila, Elon Musk, en.wikipedia.org, epigenetics, fear of failure, Flash crash, Flynn Effect, friendly AI, Gödel, Escher, Bach, income inequality, industrial robot, informal economy, information retrieval, interchangeable parts, iterative process, job automation, John von Neumann, knowledge worker, Menlo Park, meta analysis, meta-analysis, mutually assured destruction, Nash equilibrium, Netflix Prize, new economy, Norbert Wiener, NP-complete, nuclear winter, optical character recognition, pattern recognition, performance metric, phenotype, prediction markets, price stability, principal–agent problem, race to the bottom, random walk, Ray Kurzweil, recommendation engine, reversible computing, social graph, speech recognition, Stanislav Petrov, statistical model, stem cell, Stephen Hawking, strong AI, superintelligent machines, supervolcano, technological singularity, technoutopianism, The Coming Technological Singularity, The Nature of the Firm, Thomas Kuhn: the structure of scientific revolutions, transaction costs, Turing machine, Vernor Vinge, Watson beat the top human players on Jeopardy!, World Values Survey

Available at http://web.archive.org/web/20090615040912/http://www.aeiveos.com/~bradbury/MatrioshkaBrains/MatrioshkaBrainsPaper.html. Brinton, Crane. 1965. The Anatomy of Revolution. Revised ed. New York: Vintage Books. Bryson, Arthur E., Jr., and Ho, Yu-Chi. 1969. Applied Optimal Control: Optimization, Estimation, and Control. Waltham, MA: Blaisdell. Buehler, Martin, Iagnemma, Karl, and Singh, Sanjiv, eds. 2009. The DARPA Urban Challenge: Autonomous Vehicles in City Traffic. Springer Tracts in Advanced Robotics 56. Berlin: Springer. Burch-Brown, J. 2014. “Clues for Consequentialists.” Utilitas 26 (1): 105–19. Burke, Colin. 2001. “Agnes Meyer Driscoll vs. the Enigma and the Bombe.” Unpublished manuscript. Retrieved February 22, 2013. Available at http://userpages.umbc.edu/~burke/driscoll1-2011.pdf. Canbäck, S., Samouel, P., and Price, D. 2006.

INDEX A Afghan Taliban 215 Agricultural Revolution 2, 80, 261 AI-complete problem 14, 47, 71, 93, 145, 186 AI-OUM, see optimality notions AI-RL, see optimality notions AI-VL, see optimality notions algorithmic soup 172 algorithmic trading 16–17 anthropics 27–28, 126, 134–135, 174, 222–225 definition 225 Arendt, Hannah 105 Armstrong, Stuart 280, 291, 294, 302 artificial agent 10, 88, 105–109, 172–176, 185–206; see also Bayesian agent artificial intelligence arms race 64, 88, 247 future of 19, 292 greater-than-human, see superintelligence history of 5–18 overprediction of 4 pioneers 4–5, 18 Asimov, Isaac 139 augmentation 142–143, 201–203 autism 57 automata theory 5 automatic circuit breaker 17 automation 17, 98, 117, 160–176 B backgammon 12 backpropagation algorithm 8 bargaining costs 182 Bayesian agent 9–11, 123, 130; see also artificial agent and optimality notions Bayesian networks 9 Berliner, Hans 12 biological cognition 22, 36–48, 50–51, 232 biological enhancement 36–48, 50–51, 142–143, 232; see also cognitive enhancement boxing 129–131, 143, 156–157 informational 130 physical 129–130 brain implant, see cyborg brain plasticity 48 brain–computer interfaces 44–48, 51, 83, 142–143; see also cyborg Brown, Louise 43 C C. elegans34–35, 266, 267 capability control 129–144, 156–157 capital 39, 48, 68, 84–88, 99, 113–114, 159–184, 251, 287, 288, 289 causal validity semantics 197 CEV, see coherent extrapolated volition Chalmers, David 24, 265, 283, 295, 302 character recognition 15 checkers 12 chess 11–22, 52, 93, 134, 263, 264 child machine 23, 29; see also seed AI CHINOOK 12 Christiano, Paul 198, 207 civilization baseline 63 cloning 42 cognitive enhancement 42–51, 67, 94, 111–112, 193, 204, 232–238, 244, 259 coherent extrapolated volition (CEV) 198, 211–227, 296, 298, 303 definition 211 collaboration (benefits of) 249 collective intelligence 48–51, 52–57, 67, 72, 142, 163, 203, 259, 271, 273, 279 collective superintelligence 39, 48–49, 52–59, 83, 93, 99, 285 definition 54 combinatorial explosion 6, 9, 10, 47, 155 Common Good Principle 254–259 common sense 14 computer vision 9 computing power 7–9, 24, 25–35, 47, 53–60, 68–77, 101, 134, 155, 198, 240–244, 251, 286, 288; see also computronium and hardware overhang computronium 101, 123–124, 140, 193, 219; see also computing power connectionism 8 consciousness 22, 106, 126, 139, 173–176, 216, 226, 271, 282, 288, 292, 303; see also mind crime control methods 127–144, 145–158, 202, 236–238, 286; see also capability control and motivation selection Copernicus, Nicolaus 14 cosmic endowment 101–104, 115, 134, 209, 214–217, 227, 250, 260, 283, 296 crosswords (solving) 12 cryptographic reward tokens 134, 276 cryptography 80 cyborg 44–48, 67, 270 D DARPA, see Defense Advanced Research Projects Agency DART (tool) 15 Dartmouth Summer Project 5 data mining 15–16, 232, 301 decision support systems 15, 98; see also tool-AI decision theory 10–11, 88, 185–186, 221–227, 280, 298; see also optimality notions decisive strategic advantage 78–89, 95, 104–112, 115–126, 129–138, 148–149, 156–159, 177, 190, 209–214, 225, 252 Deep Blue 12 Deep Fritz 22 Defense Advanced Research Projects Agency (DARPA) 15 design effort, see optimization power Dewey, Daniel 291 Differential Technological Development (Principle of) 230–237 Diffie–Hellman key exchange protocol 80 diminishing returns 37–38, 66, 88, 114, 273, 303 direct reach 58 direct specification 139–143 DNA synthesis 39, 98 Do What I Mean (DWIM) 220–221 domesticity 140–143, 146–156, 187, 191, 207, 222 Drexler, Eric 239, 270, 276, 278, 300 drones 15, 98 Dutch book 111 Dyson, Freeman 101, 278 E economic growth 3, 160–166, 179, 261, 274, 299 Einstein, Albert 56, 70, 85 ELIZA (program) 6 embryo selection 36–44, 67, 268 emulation modulation 207 Enigma code 87 environment of evolutionary adaptedness 164, 171 epistemology 222–224 equation solvers 15 eugenics 36–44, 268, 279 Eurisko 12 evolution 8–9, 23–27, 44, 154, 173–176, 187, 198, 207, 265, 266, 267, 273 evolutionary selection 187, 207, 290 evolvable hardware 154 exhaustive search 6 existential risk 4, 21, 55, 100–104, 115–126, 175, 183, 230–236, 239–254, 256–259, 286, 301–302 state risks 233–234 step risks 233 expert system 7 explicit representation 207 exponential growth, see growth external reference semantics 197 F face recognition 15 failure modes 117–120 Faraday cage 130 Fields Medal 255–256, 272 Fifth-Generation Computer Systems Project 7 fitness function 25; see also evolution Flash Crash (2010) 16–17 formal language 7, 145 FreeCell (game) 13 G game theory 87, 159 game-playing AI 12–14 General Problem Solver 6 genetic algorithms 7–13, 24–27, 237–240; see also evolution genetic selection 37–50, 61, 232–238; see also evolution genie AI 148–158, 285 definition 148 genotyping 37 germline interventions 37–44, 67, 273; see also embryo selection Ginsberg, Matt 12 Go (game) 13 goal-content 109–110, 146, 207, 222–227 Good Old-Fashioned Artificial Intelligence (GOFAI) 7–15, 23 Good, I.

The US military and intelligence establishments have been leading the way to the large-scale deployment of bomb-disposing robots, surveillance and attack drones, and other unmanned vehicles. These still depend mainly on remote control by human operators, but work is underway to extend their autonomous capabilities. Intelligent scheduling is a major area of success. The DART tool for automated logistics planning and scheduling was used in Operation Desert Storm in 1991 to such effect that DARPA (the Defense Advanced Research Projects Agency in the United States) claims that this single application more than paid back their thirty-year investment in AI.68 Airline reservation systems use sophisticated scheduling and pricing systems. Businesses make wide use of AI techniques in inventory control systems. They also use automatic telephone reservation systems and helplines connected to speech recognition software to usher their hapless customers through labyrinths of interlocking menu options.


pages: 464 words: 127,283

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

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

Electrical Grid Gets Less Reliable,” IEEE Spectrum, January 2011, http://spectrum.ieee.org/energy/policy/us-electrical-grid-gets-less-reliable. 32Massoud Amin, “The Rising Tide of Power Outages and the Need for a Stronger and Smarter Grid,” Security Technology, blog, Technological Leadership Institute, University of Minnesota, last modified October 8, 2010, http://tli.umn.edu/blog/security-technology/the-rising-tide-of-power-outages-and-the-need-for-a-smart-grid/. 33Maurice Gagnaire et al., “Downtime statistics of current cloud solutions,” International Working Group on Cloud Computing Resiliency website, n.d., accessed February 14, 2013, http://iwgcr.org/wp-content/uploads/2012/06/IWGCR-Paris.Ranking-002-en.pdf. 34Kathleen Hickey, “DARPA: Dump Passwords for Always-on Biometrics,” Government Computer News, March 21, 2012, http://gcn.com/articles/2012/03/21/darpa-dump-passwords-continuous-biometrics.aspx. 35Global Positioning System: Significant Challenges in Sustaining and Upgrading Widely Used Capabilities (US Government Accountability Office: Washington, DC), GAO-09-670T, May 7, 2009, http://www.gao.gov/products/GAO-09-670T. 36Global Navigation Space Systems: Reliance and Vulnerabilities (London: Royal Academy of Engineering, 2011), 3. 37“Scientists Warn of ‘Dangerous Over-reliance on GPS,’” The Raw Story, March 8, 2011, http://www.rawstory.com/rs/2011/03/08/scientists-warn-of-dangerous-over-reliance-on-gps/. 38“BufferBloat: What’s Wrong with the Internet?”

To put it simply, we need science, but we also need culture to chart the way forward. In chapter 3 we saw how the roots of modern city planning grew from Patrick Geddes’s evolutionary understanding of cities and his belief that the practical application of sociology was crucial to solving the fast-multiplying problems of industrial-era cities. Geddes would no doubt approve of how today’s smart-city builders are applying technology to urban challenges and seeking to develop a new, rigorous empirical science of cities. But he also understood the limits of science, and the need to view cities with eyes that see not only facts, but wonder as well. As biographer Helen Meller wrote, Geddes believed that “the city had to be seen as a whole, not as an amalgam of disparate elements each requiring specific treatment. . . . Seeing the city as a whole however, was not straightforward; it required a special combination of science and art.

ID=3352&sku=IN1104731WH. 40“Historical Figures in Telecommunications,” International Telecommunications Union, last modified February 11, 2010, http://www.itu.int/en/history/overview/Pages/figures.aspx. 41Urs Fitze, “No Longer A One-Way Street,” Pictures of the Future, Spring 2011, 22, http://www.siemens.com/innovation/pool/en/publikationen/ publications_pof/pof_spring_2011/pof_0111_strom_smartgrid_en.pdf. 42Edwin D. Hill, “New Challenges Demand New Solutions: IBEW Leader Charts Energy Future,” EnergyBiz, September/October 2007, http://energycentral.fileburst.com/EnergyBizOnline/2007-5-sep-oct/Financial_Front_New_Challenges.pdf. 43Martin Rosenberg, “Continental Grid Vision Needed,” RenewableEnergyWorld.com blog, last modified December 11, 2007, http://www.renewableenergyworld.com/rea/news/article/2007/12/continental-grid-vision-needed-50777. 44“Company development 1847–1865,” Siemens, n.d., http://www.siemens.com/history/en/history/1847_1865_beginnings_and_initial _expansion.htm. 45Jeff St. John, “How Siemens is Tackling the Smart Grid,” GigaOM, last modified June 24, 2010, http://gigaom.com/cleantech/how-siemens-is-tackling-the-smart-grid/. 46“Siemens CEO Peter Löscher: We’re on the threshold of a new electric age,” Siemens press release, December 15, 2010, http://www.siemens.com/press/en/pressrelease/?