Galaxy Zoo

Reinventing Discovery: The New Era of Networked Science
by Michael Nielsen
Published 2 Oct 2011

But over the long run these social changes may greatly alter the context in which science is done, and it’s worth exploring them in some depth. First, let’s return to examine Galaxy Zoo in more detail. Galaxy Zoo Revisited I can honestly say that Galaxy Zoo is the best thing I’ve ever done. . . . I don’t know quite what it is, but Galaxy Zoo does something to people. The contributions, both creative and academic, that people have made to the forum are as stunning as the sight of any spiral, and never fail to move me. —Alice Sheppard, volunteer Galaxy Zoo moderator Galaxy Zoo began in 2007, with two scientists at Oxford University, Kevin Schawinski and Chris Lintott.

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Sometimes serendipity is followed up with extensive systematic analysis, as in the study of the green peas. Follow-up projects Galaxy Zoo 2 and Galaxy Zoo: Hubble have launched, and are providing even more detailed information about some of the galaxies observed by the SDSS, and also by the Hubble Space Telescope. Other new projects from the team that started Galaxy Zoo include Moon Zoo, which aims to better understand the craters on the moon, and Project Solar Storm Watch, which aims to spot explosions on the sun. One of the astronomers involved in Galaxy Zoo 2, Bob Nichol of the University of Portsmouth, contrasted Galaxy Zoo with everyday astronomy in this way: Figure 7.3.

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Democratizing Science p 129: My account of Galaxy Zoo is based on the Galaxy Zoo blog, http://blogs.zooniverse.org/galaxyzoo/, the Galaxy Zoo forum, http://www.galaxyzooforum.org, and an article by Chris Lintott and Kate Land [127]. The material on Hanny’s Voorwerp draws also on Hanny van Arkel’s blog http://www.hannysvoorwerp.com/, and the original discussion thread started by Hanny van Arkel [67]. The first Galaxy Zoo paper on the voorwerp is [128]. p 131: The alternative explanation of the voorwerp is given in [105, 177]. Some comments on the alternative explanation by Galaxy Zoo cofounder and Zookeeper Chris Lintott may be found at [126].

A Grand and Bold Thing: An Extraordinary New Map of the Universe Ushering
by Ann K. Finkbeiner
Published 16 Aug 2010

Meanwhile, the BBC put the story on their website and the Associated Press had picked it up, as had several blogs including Slashdot, a website that calls itself “News for Nerds.” Around noon, Lintott opened his laptop to see how the Galaxy Zoo website was doing, but he couldn’t get through to it. So he opened the Galaxy Zoo e-mail and found more than ten thousand e-mails, mostly from people complaining that they couldn’t get to the website. Back at Hopkins, in the predawn, the Sloanie in charge of the computers was woken by an alarm that went off when computers died. He went to campus to investigate and found that the computer Galaxy Zoo was using had overheated, its wires melted and fuses blown. He assigned another computer to the website, and by the end of the day, 22,000 people had done 500,000 classifications.

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He assigned another computer to the website, and by the end of the day, 22,000 people had done 500,000 classifications. By the next day, they were classifying in one hour the 50,000 galaxies that Kevin Schawinski had taken a week to do—the unit of classification became the Kevin-week. By the end of the week, Galaxy Zoo had done what its founders thought would take three years. By the end of the first year, Galaxy Zoo had 150,000 people, “zooites,” who had done 50 million classifications, each galaxy classified for certainty more than thirty times. The zooites are: a family physician, a truck driver, an owner of a Dutch computer business, a single mother, a Belgian secretary, a British sixth former, an art teacher, a Canadian college student, a supervisor on an oil rig, an actress, an architect, an astronomer’s wife, a librarian, a medical student, a high school student, a mobile home park manager.

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The circumstances of Gray’s early death are in an article in Wired, July 23, 2007, available online at http://www.wired.com/techbiz/people/magazine/15-08/ff_jimgray?currentPage=all. SkyServer is at http://cas.sdss.org. The Sloan’s website is http://www.sdss.org/. Galaxy Zoo is at http://zooniverse.org/home and http://www.galaxyzoo.org/. A nice article about Galaxy Zoo is: Devin Powell, “Amateur Hour,” Arts and Sciences Magazine 5, no. 2 (spring 2008); http://krieger.jhu.edu/magazine/sp08/fl.html. The demographics of the zooites come from Jordan Raddick, 2010, personal communication. WikiSky is at http://wikisky.org/.

MacroWikinomics: Rebooting Business and the World
by Don Tapscott and Anthony D. Williams
Published 28 Sep 2010

Two and a half years later, merely claiming success may be an understatement. Galaxy Zoo is thriving, with more than 275,000 users who have made nearly 75 million classifications of one million different images—far beyond Schawinski’s original 50,000. If Schawinski were still laboring on his own, it would take him 124 years to classify that many images! But Galaxy Zoo is about more than just looking at pretty pictures of galaxies. The project has resulted in real scientific discoveries, with several papers already published using the data and a dozen or so more on the way. The Galaxy Zoo team—which includes astronomers from Yale and Johns Hopkins universities in the United States, and the University of Oxford and the University of Portsmouth in the United Kingdom—has often been surprised by the results.

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Bill Keel, an astronomy professor at the University of Alabama who studies overlapping galaxies, decided to ask Galaxy Zoo users to contact him if they came across an example of this rare phenomenon. Throughout his career, Keel had studied the dozen or so overlapping galaxies then known to astronomers. Within a day of posting his question on the Galaxy Zoo forum, he had more than one hundred responses from users who had indeed found such galaxies. Today, thousands have been identified. To be sure, Galaxy Zoo is only possible because Schawinski and his colleagues have eschewed the usual inclination to keep their discoveries private until they are ready to publish.

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So, with the aid of Lintott and several others, Schawinski cooked up a scheme whereby an army of armchair astronomers would help them sort through the millions of galactic images they had stored up in their databases. The result was Galaxy Zoo, a clever online citizen science project where anyone interested can peer at the wonders of outer space, while simultaneously helping advance an exciting new frontier in science. The premise of Galaxy Zoo was simple. Users would be shown an image of a galaxy and asked two basic questions: Is the galaxy an elliptical galaxy (a type of galaxy with no dust or gas, but many stars) or a spiral galaxy (with rotating arms, like our own Milky Way galaxy); and, if it’s a spiral, in which direction are the arms rotating?

Space at the Speed of Light: The History of 14 Billion Years for People Short on Time
by Becky Smethurst
Published 1 Jun 2020

Prior to this project, these images had just been sitting on a computer hard drive—primarily because there simply aren’t enough experts in the world to go through that much data themselves, so anyone logging on to the site stood a chance of being the first-ever human to see the image of that galaxy (this is the danger of Big Data—it’s a buzzword across most areas of science these days, but the result can be that needles go undiscovered in haystacks). One of the volunteers on Galaxy Zoo was a Dutch schoolteacher called Hanny van Arkel. While classifying the shapes of galaxies, Hanny came across one image that had a fuzzy blue smudge underneath the galaxy. She was curious enough about it that she flagged it on the website’s forum and asked what it was. The Galaxy Zoo team’s experts were stumped. They’d never seen anything like it before. They didn’t know if it was a real object, or whether it was something that had gone wrong while snapping the image.

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There is always room for us to learn and learning definitely doesn’t stop outside the classroom. Another classic story about unknown knowns—and another example of a scientific discovery originating from citizen scientists rather than “experts”—is that of Hanny’s Voorwerp. Back in 2007, astronomers launched a website called Galaxy Zoo, which called on the public to help classify the shapes of over a million images of galaxies. It was a complete success and more than three hundred thousand people2 worldwide got involved to help with this cutting-edge science. Prior to this project, these images had just been sitting on a computer hard drive—primarily because there simply aren’t enough experts in the world to go through that much data themselves, so anyone logging on to the site stood a chance of being the first-ever human to see the image of that galaxy (this is the danger of Big Data—it’s a buzzword across most areas of science these days, but the result can be that needles go undiscovered in haystacks).

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By this point, though, the supermassive black hole at the center of the galaxy was no longer actively growing, so we couldn’t see that it was there. We call this a quasar light ionization echo—an echo because it shows us that the supermassive black hole was once active, but no more. The wonderful thing is that, as soon as volunteers on Galaxy Zoo knew they were looking for fuzzy blue smudges in images, they found about forty more in the original set of a million images. That meant the experts had a full sample they could go away and study. None of this would have been discovered if it wasn’t for the curiosity of one person: Hanny. After she posted the object on the forum asking what it was, other users started referring to it as “Hanny’s Voorwerp.”

Bold: How to Go Big, Create Wealth and Impact the World
by Peter H. Diamandis and Steven Kotler
Published 3 Feb 2015

In fact, we teamed up with some social scientists and found that the number one reason why people do Galaxy Zoo is the desire to contribute to actual science. They want to do something that’s useful.” A lot of people had this want. Schawinski and his colleagues had hit on a massively transformative purpose. The first iteration of Galaxy Zoo (they’re now up to version five) drew 150,000 participants classifying—wait for it—50 million galaxies. Subsequent versions pulled in over 250,000 participants and pushed the total over 60 million. And then Galaxy Zoo became a smorgasbord of citizen-science projects, now hosted at Zooniverse.

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Look, if you can leverage an existing community to fulfill your dreams, go that route. But if you’re passionate about something and no one else is sating that desire, then you have first-mover advantage. Don’t underestimate this power. When Galaxy Zoo first started, they were pretty sure only a handful of people would sign up to catalogue galaxies—yet within a very short time, tens of thousands of people were involved. Why? There was a deep, unmet need in people to participate in astronomy, and Galaxy Zoo was the only game in town. We saw something similar with Asteroid Zoo—the Zooniverse-hosted collaboration between my company, Planetary Resources, and NASA to use humans to identify new, never-before-detected asteroids, which, in turn, will create a rigorous dataset from which we can train up AIs to do the same at scale.

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I think this is the reason DIY communities are such a powerful tool for tackling bold challenges. You can go big because you don’t need to know how to pull something off ahead of time. The community shapes the path and accelerates the process. It’s a shocking amount of leverage.”8 Case Study 1: Galaxy Zoo—A DIY Community In early 2007, while working toward his PhD in astrophysics at Oxford, Kevin Schawinski was hunting blue ellipticals in the Sloan Digital Sky Survey data. A blue elliptical is a transitional galaxy, possibly the missing link between a galaxy engaged in active star formation and one long dead.

Too Big to Know: Rethinking Knowledge Now That the Facts Aren't the Facts, Experts Are Everywhere, and the Smartest Person in the Room Is the Room
by David Weinberger
Published 14 Jul 2011

For example: • Volunteers at Galaxy Zoo, a science crowdsourcing Web site, have created what it claims is “the world’s largest database of galaxy shapes.”24 Beginning in July 2007 it posted images of a million galaxies from the Sloan Digital Sky Survey and asked people to do a simple categorization of each one: spiral-shaped or elliptical? And if spiral-shaped, clockwise or counter-clockwise? In a year, it received 50 million classifications, including multiple classifications of the same galaxies, enabling Galaxy Zoo to error-check the reports. Having proved that the process works, Galaxy Zoo started a second project that asked more detailed questions.

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But the contribution of amateurs becomes more substantial if we look not only at what individuals are doing but at what networks of amateurs are contributing. For example, Arfon Smith, the technical lead of Galaxy Zoo, told me about the discovery of “green peas.” It began as a joke in the discussion area of Galaxy Zoo about the green objects that showed up in some photos. After over a hundred posts on the topic, the amateurs at Galaxy Zoo realized that there was a type of astronomical object that the professionals had not noticed. “In mid-2008,” said Smith, “they put together a portfolio and delivered it to us, and insisted that we pay attention.”

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Embodied thought Emerson, Ralph Waldo Enders, John Engadget Environmental niche modeling Environmental Protection Agency (EPA) Eureqa computer program Evolutionary science Experiments, scientific method and Expert Labs Expertise Challenger investigation crowdsourcing diversity in networking knowledge networks outperforming individuals professionalization of scaling knowledge and networking sub-networks Extremism: group polarization Exxon Valdez oil disaster Facebook Fact-based knowledge as foundation of knowledge British backlash against British chimney sweep reform Darwin’s work on barnacles Hunch.com international dispute settlement See also Data Fact-finding missions Facts Linked Data standard Malthusian theory of population growth networked Failed science Fear, information overload and Federal Advisory Committees (FACs) Federal Highway Administration Feminism Filters information overload as filter failure knowledge management FoldIt Food, extending shelf life of Foodies Ford Motors Forking Forscher, Bernard K. Fortune magazine Foucault, Michel Frauenfelder, Mark FuelEconomy.gov Future Shock (Toffler) The Futurist journal Galapagos Islands Galaxy Zoo Galen of Pergamum Garfield, Eugene Gartner Group GBIF.org (Global Biodiversity Information Facility) Geek news General Electric Gentzkow, Matthew Gillmor, Dan Gladwell, Malcolm Glazer, Nathan Global social problems Goals, shared Google abundance of knowledge amateur scientists’ use of books and filtering information physical books and e-books zettabyte Gore, Al Gray, Jim Greece, ancient Green peas Group polarization Groupthink The Guardian newspaper Gulf of Mexico oil spill The Gutenberg Elegies (Birkerts) Habermas, Jürgen Hacker ethic Hague conference Haiti Halberstam, David Hannay, Timo Hard Times (Dickens) Hargittai, Eszter Harrison, John Harvard Library Innovation Lab Haumea (planet) Hawaii Heidegger, Martin Heidegger Circle Henning, Victor Heywood, Stephen Hidary, Jack Hillis, Danny Hilscher, Emily H1N1 virus Holtzblatt, Les Home economics Homophily Howe, Jeff Human Genome Project Humors Hunch.com Hyperlinks linked knowledge providing data links IBM computers Impact factor of scientific journals In vitro fertilization An Inconvenient Truth (film) Information crowd-sourcing data and networking information for fund managers Open Government Initiative reliability of Information Anxiety (Wurman) Information cascades Information overload as filter failure consequences of metadata value of information Infrastructure of knowledge InnoCentive Institutions, Net response to Insularity of Net users Intelligence Internet increasing stupidity providing hooks for Intelligence agencies Intelligent Design International Nucleotide Sequence Database Collaboration Internet abundance of knowledge amateur scientists challenging beliefs crowds and mobs cumulative nature of data sharing diversity of expertise echo chambers forking Hunch.com improving the knowledge environment increasing institutional use indefinite scaling information information filtering interpretations knowledge residing in the network LA Times wikitorial experiment linked knowledge loss of body of knowledge permission-free knowledge public nature of knowledge reliability of information scientific inquiry shaping knowledge shared experiences sub-networks The WELL conversation unresolved knowledge See also Networked knowledge Interpretations, knowledge as iPhone Iraq Jamming Jarvis, Jeff Jellies de Joinville, Jean Journals, scientific Kahn, Herman Kantor, Jodi Kelly, Kevin Kennedy, Ted Kennedy administration Kepler, Johannes Kindle Kitano, Hiroaki Knowledge abundance of as interpretation changing shape of crisis of echo chambers hiding enduring characteristics of environmental niche modeling fact-based and analogy-based human pursuit of hyperlinked context improving the Internet environment Internet challenging beliefs linked permission-free public reason as the path to social elements of stopping points unresolved Knowledge clubs Kuhn, Thomas Kundra, Vivek Kutcher, Ashton Lakhani, Karim Language games Latour, Bruno Leadership Debian network decision-making and Dickover’s social solutions network distribution Lebkowsky, Jon Leibniz, Gottfried Lessig, Lawrence Levy-Shoemaker comet Librarians Library of Congress Library use Lili’uokalani (Hawaiian queen) Linked Data standard Linked knowledge Links filters as See also Hyperlinks Linnean Society Linux Lipson, Hod Literacies Loganathan, G.V.

Age of Discovery: Navigating the Risks and Rewards of Our New Renaissance
by Ian Goldin and Chris Kutarna
Published 23 May 2016

Now, by redesigning research methods to focus computers on what they do best and inviting volunteer masses to donate human brainpower where it’s needed most, “citizen science” is starting to break through the analytic bottlenecks that plague a wide range of disciplines. In 2007, Chris Lintott and Kevin Schawinski co-founded Galaxy Zoo, inviting amateur stargazers to help them catalog and classify some 900,000 galaxies that had been photographed from the year 2000 onward. The task would have taken one devout graduate student three to five years of 24 × 7 × 365 labor to complete; twice as long if she double-checked her work. Instead, it took over 100,000 volunteers less than six months, and each galaxy was re-checked an average of 38 times. By mid-2014, several hundred thousand Galaxy Zoo volunteers had crunched through seven giant-scale data sets, compiled a catalog of galaxies ten times larger than any previous version, and produced 44 scientific papers’ worth of results.27 Along the way they spotted rare astronomical phenomena that had been conjectured for years but never detected, and found others, like Hanny’s Voorwerp, that were entirely unexpected.28 Hanny van Arkel, a Dutch schoolteacher, got an object in the sky named after her—an honor that even professional astronomers rarely receive.

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By mid-2014, several hundred thousand Galaxy Zoo volunteers had crunched through seven giant-scale data sets, compiled a catalog of galaxies ten times larger than any previous version, and produced 44 scientific papers’ worth of results.27 Along the way they spotted rare astronomical phenomena that had been conjectured for years but never detected, and found others, like Hanny’s Voorwerp, that were entirely unexpected.28 Hanny van Arkel, a Dutch schoolteacher, got an object in the sky named after her—an honor that even professional astronomers rarely receive. Galaxy Zoo expanded into Zooniverse (zooniverse.org)—in 2015, the world’s largest citizen science portal with 1.1 million registered volunteers. Together they tackle oversized data sets in dozens of projects, spanning astronomy, biology, ecology, climate science and the humanities.29 A project called Planet Four enlists Mars enthusiasts to help map the surface of the Red Planet.

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IEEE Spectrum. Retrieved from spectrum.ieee.org/biomedical/devices/the-dna-data-deluge. 26. Jet Propulsion Laboratory (2013, October 27). “Managing the Deluge of ‘Big Data’ from Space.” NASA. Retrieved from www.jpl.nasa.gov/news. 27. SciTech Daily (2013, September 24). “Researchers Publish Galaxy Zoo 2 Catalog, Data on More Than 300,000 Nearby Galaxies.” SciTech Daily. Retrieved from scitechdaily.com. 28. van Arkel, Hanny (2015). “Voorwerp Discovery.” Retrieved from www.hannysvoorwerp.com. 29. Smith, A., S. Lynn, et al. (2013, December). “Zooniverse-Web Scale Citizen Science with People and Machines.”

Smarter Than You Think: How Technology Is Changing Our Minds for the Better
by Clive Thompson
Published 11 Sep 2013

Baker published the results: Firas Khatib et al., “Crystal Structure of a Monomeric Retroviral Protease Solved by Protein Folding Game Players,” Nature Structural & Molecular Biology 19, no. 3 (March 2012): 1175–77. the Galaxy Zoo: Tim Adams, “Galaxy Zoo and the New Dawn of Citizen Science,” The Observer (UK), March 17, 2012, accessed March 24, 2013, www.guardian.co.uk/science/2012/mar/18/galaxy-zoo-crowdsourcing-citizen-scientists. a one-million-dollar prize: Eliot Van Buskirk, “BellKor’s Pragmatic Chaos Wins $1 Million Netflix Prize by Mere Minutes,” Wired, September 21, 2009, accessed March 24, 2013, www.wired.com/business/2009/09/bellkors-pragmatic-chaos-wins-1-million-netflix-prize/; I also previously reported on the Netflix Prize in “If You Liked This, You’re Sure to Love That,” The New York Times Magazine, November 21, 2008, accessed March 24, 2013, www.nytimes.com/2008/11/23/magazine/23Netflix-t.html.

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People eagerly pitch in on projects they’re interested in, which is exactly why so many ad hoc collaborations erupt around amateur passions, like hobbies or pop culture. But as the Fold.it guys found, science projects work well, too, because people enjoy feeling they’re contributing to global knowledge. Many other scientists have joined Baker in crafting successful group thinking projects, such as the Galaxy Zoo, founded by the Radcliffe Observatory in Oxford, England, which puts a deluge of space imagery online and lets everyday astrophiles classify the shapes of galaxies; like Fold.it, it quickly evolved a community of contributors. Politics, too, is an area where many people are motivated to help, which is what drives the success of the Ushahidi maps or government 2.0 projects, where citizens compile information to improve their communities.

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See also memory and ability to refind information, 127–28 artificial forgetting, 241–42 benefits of, 40–41 details versus meaning, 129, 133–34 Ebbinghaus curve, 25, 144–45 process of, 23–24 4chan, 241 Foursquare, 37–38 FoursquareAnd7YearsAgo, 38 Freedom app, 136 Friedel, Frederic, 17 Frye, Northrop, 132 Fuchsian functions, 132 Fujifilm Velvia film, 110 “Funes, the Memorius” (Borges), 39–40 Galaga (video game), 148 Galaxy Zoo, 169 Galileo, 59 Galton, Francis, 155–56 Gardner, Sue, 161 Gee, James Paul, 198 generation effect, 57, 75, 184 geography, learning through video games, 199–202 geolocation. See also mapping ambient awareness of, 242–43 geography, impact on message, 62–63 location-based sharing, 81 gerrymandering, 84–86 Ghonim, Wael, 255–57, 272 Gibson, William, 9 Gilman, Charlotte Perkins, 225 Giovanni, Daniel, 38 Gladwell, Malcolm, 229 Glaeser, Edward, 15 Gleeson, Colleen, 186 Gleick, James, 259 Global Network Initiative, 277 Gmail mail as lifelog, 43–44 mail storage and ads, 28 as transactive memory tool, 131 Goffman, Erving, 238 Gold, Heather, 79–80, 226 Goodreads, 82, 243 Google collaborative projects, 171 collective knowledge as basis, 170–71 mail.

Machines of Loving Grace: The Quest for Common Ground Between Humans and Robots
by John Markoff
Published 24 Aug 2015

That was very inexpensive but did not yield perfect results. In the next version of the program, dubbed Galaxy Zoo 2, computers with machine-learning models would interpret the images of the galaxies in order to present accurate specimens to human classifiers, who could then catalog galaxies with much less effort than they had in the past. In yet another refinement, the system would add the ability to recognize the particular skills of different human participants and leverage them appropriately. Galaxy Zoo 2 was able to automatically categorize the problems it faced and knew which people could contribute to solving which problem most effectively.

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As early as 2005, for example, two chess amateurs used a chess-playing software program to win a match against chess experts and individual chess-playing programs. Horvitz is continuing to deepen the human-machine interaction by researching ways to couple machine learning and computerized decision-making with human intelligence. For example, his researchers have worked closely with the designers of the crowd-sourced citizen science tool called Galaxy Zoo, harnessing armies of human Web surfers to categorize images of galaxies. Crowd-sourced labor is becoming a significant resource in scientific research: professional scientists can enlist amateurs, who often need to do little more than play elaborate games that exploit human perception, in order to help scientists map tricky problems like protein folding.19 In a number of documented cases teams of human experts have exceeded the capability of some of the most powerful supercomputers.

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., 240–241 DARPA Advanced Research Projects Agency as precursor to, 30, 110, 111–112, 164, 171 ARPAnet, 164, 196 autonomous cars and Grand Challenge, 24, 26, 27–36, 40 CALO and, 31, 297, 302–304, 310, 311 Dugan and, 236 Engelbart and, 6 Licklider and, 11 LRASM, 26–27 Moravec and, 119 Pratt and, 235–236 Robotics Challenge, 227–230, 234, 236–238, 244–254, 249, 333–334 Rosen and, 102 Taylor and, 160 Darrach, Brad, 103–105 Dartmouth Summer Research Project on Artificial Intelligence, 105, 107–109, 114, 143 DataLand, 307 Davis, Ruth, 102–103 “Declaration of the Independence of Cyberspace, A” (Barlow), 173 DeepMind Technologies, 91, 337–338 Defense Science Board, 27 de Forest, Lee, 98 “demons,” 190 Dendral, 113–114, 127 Diebold, John, 98 Diffie, Whitfield, 8, 112 Digital Equipment Corporation, 112, 285 direct manipulation, 187 Djerassi, Carl, 113 Doerr, John, 7 Dompier, Steve, 211–212 Dreyfus, Hubert, 177–178, 179 drone delivery research, 247–248 Dubinsky, Donna, 154 Duda, Richard, 128, 129 Dugan, Regina, 236 Duvall, Bill, 1–7 Earnest, Les, 120, 199 Earth Institute, 59 Edgerton, Germeshausen, and Grier (EG&G), 127 e-discovery software, 78 E-Groups, 259 elastic actuation, 236–237 electronic commerce, advent of, 289, 301–302 electronic stability control (ESC), 46 Elementary Perceiver and Memorizer (EPAM), 283 “Elephants Don’t Play Chess” (Brooks), 201 Eliza, 14, 113, 172–174, 221 email, advent of, 290, 310 End of Work, The (Rifkin), 76–77 Engelbart, Doug. see also SRI International on exponential power of computers, 118–119 IA versus AI debate and, 165–167 on intelligence augmentation (IA), xii, 5–7, 31 Minsky and, 17 “Mother of All Demos” (1968) by, 62 NLS, 5–7, 172, 197 Rosen and, 102 Siri and, 301, 316–317 Engineers and the Price System, The (Veblen), 343 Enterprise Integration Technologies, 289, 291 ethical issues, 324–344. see also intelligence augmentation (IA) versus AI; labor force of autonomous cars, 26–27, 60–61 decision making and control, 341–342 Google on, 91 human-in-the-loop debates, 158–165, 167–169, 335 of labor force, 68–73, 325–332 scientists’ responsibility and, 332–341, 342–344 “techno-religious” issues, 116–117 expert systems, defined, 134–141, 285 Facebook, 83, 156–158, 266–267 Fast-SLAM, 37 Feigenbaum, Ed, 113, 133–136, 167–169, 283, 287–288 Felsenstein, Lee, 208–215 Fernstedt, Anders, 71 “field robotics,” 233–234 Fishman, Charles, 81 Flextronics, 68 Flores, Fernando, 179–180, 188 Foot, Philippa, 60 Ford, Martin, 79 Ford Motor Company, 70 Forstall, Scott, 322 Foxconn, 93, 208, 248 Friedland, Peter, 292 Galaxy Zoo, 219–220 Gates, Bill, 305, 329–330 General Electric (GE), 68–69 General Magic, 240, 315 General Motors (GM), 32–35, 48–50, 52, 53, 60 Genetic Finance, 304 Genghis (robot), 202 Geometrics, 127 George, Dileep, 154 Geraci, Robert, 85, 116–117 Gerald (digital light field), 271 Giant Brains, or Machines That Think (Berkeley), 231 Gibson, William, 23–24 Go Corp., 141 God & Golem, Inc.

The Half-Life of Facts: Why Everything We Know Has an Expiration Date
by Samuel Arbesman
Published 31 Aug 2012

By pairing a distorted known word with one that computers are unable to decipher, everyday users who can read these words are helping bring newspapers and books into digital formats. Scientists are beginning to use this sort of human computation. These researchers are relying on citizen scientists to help them look through large amounts of data, most of which is too difficult for a computer (or even a single person) to comb through. One example is Galaxy Zoo, in which scientists gave participants pictures of galaxies to help classify them. The participants weren’t experts; they were interested individuals who participated in a minutes-long tutorial and were simply interested in space, or wanted to help scientific progress. Several intrepid scientists turned a fiendishly difficult problem—how to predict what shapes proteins will fold into based on their chemical makeup—into a game.

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.), 85 dinosaurs, 3, 79–82, 168–69, 194 discovery: long tail of, 38 multiple independent, 104–5 pace of, 9–25 discriminating power, 159–60 diseases, 52, 176–77 categorization of, 205 spread of, 62, 64 Dittmar, Jeremiah, 71, 73 Dixon, William Macneile, 8 DNA, 88, 90, 122, 163 drugs, 24, 111–12 repurposing of, 112 streptokinase, 108–9 Dunbar, Robin, 205 Dunbar’s Number, 205–6 Earth, curvature of, 35–36 education, 182–83, 195 Einstein, Albert, 36, 106, 186 Electronics, 42 Ellsworth, Henry, 54 e-mail, 41 Empedocles, 201 Encyclopaedia of Scientific Units, Weights, and Measures: Their SI Equivalences and Origins (Cardarelli), 146 EndNote, 117–18 energy, 55, 204 Eos, 148 Erdo˝s, Paul, 104 errors, 78–95 contrary to popular belief phrase and, 84–85 Essay on the Application of Mathematical Analysis to the Theories of Electricity and Magnetism, An (Green), 106 eurekometrics, 21, 22 Eureqa, 113–14 Everest, George, 140 evolution, 79, 187 evolutionary programming, 113 evolutionary psychology, 175 expertise, long tail of, 96, 102 experts, 96–97 exponential growth, 10–14, 44–45, 46–47, 54–55, 57, 59, 130, 204 extinct species, 26, 27–28 facts, see knowledge and facts factual inertia, 175, 179–83, 188, 190, 199 Fallows, James, 86 Fermat, Pierre de, 132 Feynman, Richard, 104 fish, 201 fishing, 173 fish oil, 99, 110 Florey, Lord, 163 Flory, Paul, 104 Foldit, 20 Franzen, Jonathan, 208–9 French Canadians, 193–94 frogs: boiling of, 86, 171 vision of, 171 Galaxy Zoo, 20 Galileo, 21, 143–44 Galton, Francis, 165–68 games, 51 generational knowledge, 183–85, 199 genetics, 87–90 genome sequencing, 48, 51 Gibrat’s Law, 103 Goddard, Robert H., 174 Godwin’s law, 105 Goldbach’s Conjecture, 112–13 Goodman, Steven, 107–8 Gould, Stephen Jay, 82 grammar: descriptive, 188–89 prescriptive, 188–89, 194 Granovetter, Mark, 76–78 Graves’ disease, 111 Great Vowel Shift, 191–93 Green, George, 105–6 growth: exponential, 10–14, 44–45, 46–47, 54–55, 57, 59, 130, 204 hyperbolic, 59 linear, 10, 11 Gumbel, Bryant, 41 Gutenberg, Johannes, 71–73, 78, 95 Hamblin, Terry, 83 Harrison, John, 102 Hawthorne effect, 55–56 helium, 104 Helmann, John, 162 Henrich, Joseph, 58 hepatitis, 28–30 hidden knowledge, 96–120 h-index, 17 Hirsch, Jorge, 17 History of the Modern Fact, A (Poovey), 200 Holmes, Sherlock, 206 homeoteleuton, 89 Hooke, Robert, 21, 94 Hull, David, 187–88 human anatomy, 23 human computation, 20 hydrogen, 151 hyperbolic growth rate, 59 idiolect, 190 impact factors, 16–17 inattentional blindness (change blindness), 177–79 India, 140–41 informational index funds, 197 information transformation, 43–44, 46 InnoCentive, 96–98, 101, 102 innovation, 204 population size and, 135–37, 202 prizes for, 102–3 simultaneous, 104–5 integrated circuits, 42, 43, 55, 203 Intel Corporation, 42 interdisciplinary research, 68–69 International Bureau of Weights and Measures, 47 Internet, 2, 40–41, 53, 198, 208, 211 Ioannidis, John, 156–61, 162 iPhone, 123 iron: magnetic properties of, 49–50 in spinach, 83–84 Ising, Ernst, 124, 125–26, 138 isotopes, 151 Jackson, John Hughlings, 30 Johnson, Steven, 119 Journal of Physical and Chemical Reference Data, 33–35 journals, 9, 12, 16–17, 32 Kahneman, Daniel, 177 Kay, Alan, 173 Kelly, Kevin, 38, 46 Kelly, Stuart, 115 Kelvin, Lord, 142–43 Kennaway, Kristian, 86 Keynes, John Maynard, 172 kidney stones, 52 kilogram, 147–48 Kiribati, 203 Kissinger, Henry, 190 Kleinberg, Jon, 92–93 knowledge and facts, 5, 54 cumulative, 56–57 erroneous, 78–95, 211–14 half-lives of, 1–8, 202 hidden, 96–120 phase transitions in, 121–39, 185 spread of, 66–95 Koh, Heebyung, 43, 45–46, 56 Kremer, Michael, 58–61 Kuhn, Thomas, 163, 186 Lambton, William, 140 land bridges, 57, 59–60 language, 188–94 French Canadians and, 193–94 grammar and, 188–89, 194 Great Vowel Shift and, 191–93 idiolect and, 190 situation-based dialect and, 190 verbs in, 189 voice onset time and, 190 Large Hadron Collider, 159 Laughlin, Gregory, 129–31 “Laws Underlying the Physics of Everyday Life Really Are Completely Understood, The” (Carroll), 36–37 Lazarus taxa, 27–28 Le Fanu, James, 23 LEGO, 184–85, 194 Lehman, Harvey, 13–14, 15 Leibniz, Gottfried, 67 Lenat, Doug, 112 Levan, Albert, 1–2 Liben-Nowell, David, 92–93 libraries, 31–32 life span, 53–54 Lincoln, Abraham, 70 linear growth, 10, 11 Linnaeus, Carl, 22, 204 Lippincott, Sara, 86 Lipson, Hod, 113 Little Science, Big Science (Price), 13 logistic curves, 44–46, 50, 116, 130, 203–4 longitude, 102 Long Now Foundation, 195 long tails: of discovery, 38 of expertise, 96, 102 of life, 38 of popularity, 103 Lou Gehrig’s disease (ALS), 98, 100–101 machine intelligence, 207 Magee, Chris, 43, 45–46, 56, 207–8 magicians, 178–79 magnetic properties of iron, 49–50 Maldives, 203 Malthus, Thomas, 59 mammal species, 22, 23, 128 extinct, 28 manuscripts, 87–91, 114–16 Marchetti, Cesare, 64 Marsh, Othniel, 80–81, 169 mathematics, 19, 51, 112–14, 124–25, 132–35 Matthew effect, 103 Mauboussin, Michael, 84 Mayor, Michel, 122 McGovern, George, 66 McIntosh, J.

Superminds: The Surprising Power of People and Computers Thinking Together
by Thomas W. Malone
Published 14 May 2018

VOTING AS A WAY OF FINDING WHAT’S TRUE In addition to aggregating people’s values and preferences, democracies can also be very useful as a way of aggregating people’s opinions about what is true. For instance, when lots of nonexperts vote on possible answers to a question, they often arrive at an answer that is just as good as one that an expert would give. In the Galaxy Zoo project, for instance, hundreds of thousands of online volunteers are helping astronomers by classifying the shapes and other characteristics of a million galaxies in distant parts of the universe that astronomers have previously observed through telescopes.6 Even though a single volunteer might mistakenly classify an astronomical object, when many volunteers look at that same object and vote on how to classify it, the results of the group’s votes are extremely accurate, allowing the classification to happen much faster than if it were being done by a handful of experts.

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“Pirate Party,” accessed February 20, 2017, https://en.wikipedia.org/wiki/Pirate_Party. 5. Steve Hardt and Lia C. R. Lopes, “Google Votes: A Liquid Democracy Experiment on a Corporate Social Network,” Technical Disclosure Commons, June 5, 2015, http://www.tdcommons.org/dpubs_series/79. 6. “The Story So Far,” Galaxy Zoo, accessed October 21, 2017, https://www.galaxyzoo.org/?_ga=1.247761351.1568972630.1472315428#/story. 7. “About Eyewire, a Game to Map the Brain,” Eyewire, accessed February 20, 2017, http://blog.eyewire.org/about/. 8. Barbara Mellers, Eric Stone, Pavel Atanasov, Nick Rohrbaugh, S. Emlen Metz, Lyle Ungar, Michael Metcalf Bishop, et al., “The Psychology of Intelligence Analysis: Drivers of Prediction Accuracy in World Politics,” Journal of Experimental Psychology: Applied 21, no. 1 (2015): 1; Barbara Mellers, Lyle Ungar, Jonathan Baron, Jamie Ramos, Burcu Gurcay, Katrina Fincher, Sydney E.

Free Speech: Ten Principles for a Connected World
by Timothy Garton Ash
Published 23 May 2016

On occasion, crowdsourcing has generated scientific results that could not have been found by a single researcher, or only at vast expense of time and money. Two researchers sitting in an English pub had the crazy idea of asking the general public to help them scan tens of thousands of photos of galaxies. With mass participation, this Galaxy Zoo not only classified numerous previously unclassified galaxies but also identified a new kind of galaxy.46 A Cambridge mathematician put an open invitation on his blog for people to help him solve a difficult mathematical problem. He called this experiment the Polymath Project. Six weeks later, he announced that they had solved not just the original problem but also a harder one that included the original as a special case.47 When it comes to discussions not of what is but of what should be, of values and norms, the dialogue across frontiers, cultures, faiths and political camps is itself part of the research.

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‘Copyright & Attribution’, Free Speech Debate, http://freespeechdebate.com/en/copyright-attribution/ 44. on the Digital Public Library, see Darnton, ‘The National Digital Public Library Is Launched!’, New York Review of Books, 25 April 2013, http://www.nybooks.com/articles/archives/2013/apr/25/national-digital-public-library-launched/. Europeana, http://www.europeana.eu/portal/ and the Internet Archive, https://archive.org/index.php 45. see Nielsen 2012, 161–63 46. Galaxy Zoo, http://perma.cc/W5M4-PAHW 47. I take these examples from Nielsen 2012, 1–3, 133–42 48. see ‘Gottfrid Svartholm-Warg on Freedom of Speech 2007’, 20 May 2013, http://www.youtube.com/watch?v=FJiWuw7Qk5E 49. see Gabrielle Guillemin, ‘Does ACTA Threaten Online Freedom of Expression & Privacy?’, Free Speech Debate, http://freespeechdebate.com/en/media/acta-the-internet-freedom-of-expression-privacy/ 50. see, for example, University of Exeter, ‘Green and Gold Open Access’, http://perma.cc/A9VW-2VND 51. internet live stats, Google Search Statistics, http://www.internetlivestats.com/google-search-statistics/.

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See also Charlie Hebdo; Cohen, Patrick; Dieudonné; Dilhac, Marc-Antoine; Errera, Roger; French language; Ricoeur, Paul; Voltaire; Wackenheim, Manuel ‘Free-Born John’ (John Lilburne), 372–73, 374 freedom of information, 48, 78, 119, 123, 125, 127, 325, 328–34, 338, 358, 380 freedom of speech/expression, 152; Catch-22 of, 103–4; and Christianity, 272–73; clothing, tattoos as expression, 124; and Confucianism, 110; dangerous speech, 135–38; and dialogue between civilisations, 96–98, 110–11; European Convention on Human Rights, 34; four forces determining, 213; freedom from seeing/hearing, 125–27; how to implement, 79–81; and incitement to violence, 132–33; and individual sovereignty, 370–71; on the internet, 93–94; and Islam, 272–80; justifications for limiting, 86–95; law, norms, practices for, 81–86; and money, 367–69 (368f); press freedom, 183–89; rationale for, 73–79; ‘regardless of frontiers,’ 127–28; and religion, 208; threats to, 121; World Values Survey, 101 freedom of the press, 48, 183–89, 337–38 Freedom (software), 179 freedom to connect, 32 freespeechdebate.com, 2–3 (3f); assassin’s veto discussion, 130; blocked within China, 44; challenge principle, 320; civility discussion, 250–51; community standards of, 61; in Egypt, 278; legal hurdles to set up, 36; licence, 165–66; machine and human translation on, 95, 105, 176, 210; one-click-away principle, 126; pnyx on, 206; in Poland, 288; republication of cartoons, 143, 148; in Turkey, 278; use of pseudonyms on, 67, 316–17 French language, 47, 48, 85, 110, 123, 174, 175f, 176, 185, 210, 244, 278 Fry, Stephen, 136 Fujimori, Alberto, 190 Funes, Ireno, 305 Furedi, Frank, 90 Gaddafi, Muammar, 88 ‘Gafa, les,’ 48 Galaxy Zoo, 166 Galilei, Galileo, 152 Gandhi, Mohandas, 91, 98, 108, 148–49, 158, 251, 346, 378 Garcia, Cindy Lee, 71 Gates, Bill, 54 Gawker, 294–95 ‘Gay Girl in Damascus,’ 314 Gaza Strip, 140 Gazeta Wyborcza, 144 GCHQ (Government Communications Headquarters), 320, 329, 337, 343 Geller, Pamela, 134, 276 Gellner, Ernest, 223 George III, 22 Georgia, 349 German language, 76, 83, 140, 174, 205, 222, 309–10, 323 Germany, 18, 37, 55, 76, 79, 85, 125–26, 129, 140, 150, 156, 157–59, 161, 171, 175f, 189, 196–98, 198f, 201f, 203, 210, 212–13, 217, 227–28, 260, 287–89, 291, 302–3, 304–6, 308, 326, 330, 332, 334, 346, 355, 374.

Blockchain Revolution: How the Technology Behind Bitcoin Is Changing Money, Business, and the World
by Don Tapscott and Alex Tapscott
Published 9 May 2016

If you were smart and hardworking in India, your merit would bring you reputation. The world would be flatter, more meritocratic, more flexible, and more fluid. Most important, technology would contribute to prosperity for everyone, not just wealth for the few. Some of this has come to pass. There have been mass collaborations like Wikipedia, Linux, and Galaxy Zoo. Outsourcing and networked business models have enabled people in the developing world to participate in the global economy better. Today two billion people collaborate as peers socially. We all have access to information in unprecedented ways. However, the Empire struck back. It has become clear that concentrated powers in business and government have bent the original democratic architecture of the Internet to their will.

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See also Microfinance blockchain IPOs, 82–84 blockchain transformations of, 8, 18–19, 58–63, 64, 128 frameworks for accounting and corporate governance, 73–79 Golden Eight of, 61–63, 64, 86 identity issues, 61, 64, 78–79 paradoxes of traditional finance, 55–57 players in blockchain ecosystem, 285 prediction markets, 84–85 reputation and credit score, 79–82 retail services, 71–73 smart devices and IoT, 159 from stock exchanges to block exchanges, 63, 65–66 Financial stability, 295 Financial utility, 69–70 Firefox Web, 129 First era of the Internet, 3–4, 12–14, 15, 39, 49, 92, 95, 106, 124, 265, 281–82, 299–300 “Float,” 45 FNY Capital, 83 Food industry, 138–39, 157–58 Ford, Henry, 246 Forde, Brian, 247, 282, 286, 287, 305 Foreign aid, 20–21, 188–92 Formation costs, 179 Fragmenting public discourse, 212–13 Free agent nation, 110 Freedom of Information laws, 208–9 Free press, 243–46 Free speech, 243–46 Freitas, Miguel, 246 Funding, in financial services, 62–63, 64 Fund-raising, 179 Futarchy, 220 Future Crimes (Goodman), 276 Future-proofing, 152, 197 Galaxy Zoo, 12 Gauck, Joachim, 52 Gault, Mike, 199 Gemini, 284, 291 Gems, 94–95 Gender differences, in banking access, 178, 192 Germany, 27, 51–52 GetGems, 245 Gibson, William, 255 GitHub, 89, 138 Global solution networks (GSNs), 283, 300–307 Global standards networks, 304–6 “God Protocol, The” (Szabo), 4–5 Gold, 34, 95, 199, 254, 260 Goldcorp Challenge, 223 Golden Eight, 61–63, 64, 86 Goldman Sachs, 66, 70, 71, 284 Goodman, Marc, 276 Google, 13, 96, 118, 140, 143, 161, 180, 255, 270, 275 Gore, Al, 212 Governance, 24, 283, 288–89, 307 distributed power, 33–35, 273 in financial services, 73–79 new framework for blockchain, 298–307 regulations vs., 296–97 Government Digital Service, U.K., 205 Governments, 9, 13, 23, 197–225 alternative models of politics and justice, 218–21 Big Brother, 244, 274–75 blockchain voting, 215–17 design principles in, 201–3 empowering people to serve selves and others, 207–11 engaging citizens to solve big problems, 221–23 Estonia example, 197–99, 203, 204, 206–7 in financial services industry, 70 high-performance services and operations, 203–7 players in blockchain ecosystem, 286–87 second era of democracy, 211–15 stifling or twisting bitcoin, 263–65 tools of twenty-first-century, 223–25 Grande, Ariana, 228 Greifeld, Bob, 65, 66, 84 Guardtime, 199 Guez, Bruno, 238 Gun rights, 200–201, 276 Gupta, Vinay, 226, 227 Hacking, 39, 40, 41, 118–19, 138, 151–52, 243–44 boundary decisions, 112–14 business model innovation, 142–44 DAEs, 273–74 smart things, 168–69 Hagel, John, 94 Haiti earthquake of 2010, 20–21, 188–89 remittances, 183 Haldane, Andrew, 9 Hamel, Gary, 110 Hanks, Tom, 78 Hanson, Robin, 220 Hashcash, 34 Hash rate, 241, 260 Hash value, 32 Hawking, Stephen, 274 Health care, 151, 158 Heap, Imogen, 21, 226, 227–28, 229, 231–35 Hearn, Mike, 69, 164–65, 271, 282 HedgeStreet, 84 Hedgy, 105 Herstatt risk, 59–60 Hewlett-Packard, 150 Hierarchies, 12, 88, 93–101, 105–6 High latency, 256–57 Hill, Austin, 28 design principles, 38, 40–41, 43, 51 financial services, 63, 65–67, 76 implementation challenges, 262, 272 Holacracy, 48–49, 88 Hollywood Stock Exchange, 84 Home management, 161, 275 Homomorphic encryption, 28 Honduras, 193–95 Honesty, 10, 11 Horizontal search, 97 Humanitarian aid, 20–21, 188–92 Human Rights Watch, 200 Hyperledger Project, 69–70, 285, 305 IBM, 39, 111, 118, 129–30, 150, 153 IBM Connections, 139 IBM Institute for Business Value, 163 Ideagoras, 137, 138 Identity, 3–4, 14–16, 264–65.

Open: The Story of Human Progress
by Johan Norberg
Published 14 Sep 2020

I had never heard of her before, but she has classified 40,000 galaxies on her own and has detected 10 per cent of all known hyper-fast stars – stars whose velocity deviate substantially from the normal velocity of stars. One reason I had never heard of her is that she does not work in any observatory and does not even have an education in astronomy. She is a housewife from Puerto Rico with two children. Through the Galaxy Zoo online platform, where scientists have published photos of the starry sky, 200,000 amateur astronomers have helped to classify more than 150 million galaxies.10 Who could have guessed that one of the best would turn out to be a housewife in Puerto Rico? No one. No government would have planned for it, and no research group would have included her in its team.

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(Fukuyama), 362–5 End of Work, The (Rifkin), 312 Engels, Friedrich, 33, 36, 162, 206, 247, 256 English Civil War (1642–1651), 148, 183, 184, 201 Enigma machine, 124–6 Enlightenment, 4, 5, 6, 13, 103, 154–60, 165–6, 195–6 Environmental Performance Index, 327 Ephesus, 45 Epic of Gilgamesh, The, 38 Epicurus, 134–5 Epstein, Richard, 320 equality matching, 262–6, 267 Erasmus, 152 Erdogan, Recep Tayyip, 354 Ethiopia, 72, 130 ethnocentrism, 219, 271 Etruscan civilization (c. 900–27 BC), 43 Eubulus, 47 eugenics, 109 Euphrates river, 37 Euripides, 132 European Organization for Nuclear Research, 306 European Parliament, 325 European Union (EU) Brexit (2016–), 9, 14, 118, 238, 240–41, 349, 354, 379 common currency, 280–81 freedom of movement, 118, 343 migration crisis (2015–), 10, 114, 115, 342–3, 358 subsidies in, 280 trade and, 272 United States, trade with, 19 Evans, Oliver, 203 Evolution of God, The (Wright), 249 evolutionary psychology, 14, 23, 225 exoticism, 84 Expressionism, 198 Facebook, 239, 309 Falwell, Jerry, 113–14 Farage, Nigel, 241 farming, see agriculture Fascist Italy (1922–1943), 105, 219 FedEx, 319 Feifer, Jason, 290–92 Fenway Park, Boston, 223 Ferdinand II, King of Aragon, 97, 98, 106 Ferguson, Charles, 314 Fermi, Enrico, 105 Ferney, France, 153 feudalism, 92, 194, 202, 208 fight-or-flight instinct, 15, 346, 348–9 filter bubbles, 239 financial crisis (2008), 10, 15, 62, 254, 333, 358, 359–60 fire, control of, 32–3, 76 Flanders, 208 fluyts, 100 Flynn effect, 109 Fogel, Robert, 276 folk economics, 258–62 football, 223–4, 245–6 Forbes, 274 Ford, Henry, 203 Fortune 500 companies, 82 Fox News, 82, 302, 354 France, 151 American Revolutionary War (1775–83), 201 automation in, 313 Cathars, 94, 142 Cobden–Chevalier Treaty (1860), 53–4 corruption in, 345 Dutch War (1672–8), 101 Encyclopédie, 154 free zones in, 180–81 Huguenots, persecution of, 97, 99, 101, 158, 193 immigration in, 115 Jews, persecution of, 96, 97, 254 languages in, 289 Minitel, 313 Revolution (1789–99), 201, 292 Royal Academy of Sciences, 156 ruin follies, 287 St Bartholomew’s Day massacre (1572), 97 Thököly Uprising (1678–85), 137 Uber in, 320 University of Paris, 140, 141–2, 143 Francis I, Emperor of Austria-Hungary, 178 Franciscans, 144 Franklin, Benjamin, 107 Franks, 92 free speech, 127, 131–2, 160, 163–5, 343 Chicago principles, 164–5 emigration for, 152–3 university campuses, 163–5 free trade, see under trade Fried, Dan, 289 Friedman, Benjamin, 253 Friedman, David, 284 Friedman, Thomas, 325 Friedrich Wilhelm I, King of Prussia, 153 Fukuyama, Francis, 362–5 Fulda, Germany, 179, 180 Future and Its Enemies, The (Postrel), 300 Future of Nostalgia, The (Boym), 288 Galatia, 90 Galaxy Zoo, 80 Galilei, Galileo, 146, 150 Gallup, 164 game theory, 26 Gandhi, Indira, 326 gas lighting, 297 Gates, William ‘Bill’, 274, 277, 309 Gauls, 90, 91, 92 gay rights, 113, 336 Geary, Patrick, 288–9 gender equality, 113, 114 General Motors, 64 generations baby-boom generation (1946–64), 294, 340 generation X (1965–80), 340 immigration and, 106, 110–11, 113–14 interwar generation (1928–45), 340 millennial generation (1981–96), 340 nostalgia and, 291, 293–4, 296 genetically modified organisms (GMO), 299, 301 Geneva, Switzerland, 152, 153 Genghis Khan, 94–5, 96, 174 Genoa, Republic of (1005–1797), 73, 178 George II, King of Great Britain and Ireland, 193 George III, King of Great Britain and Ireland, 103, 193 George Mason University, 257, 258 Georgia, 365 Georgia, United States, 349 German Conservative Party, 254 Germany automatic looms, 179 Berlin Wall, fall of (1989), 10, 340, 341, 363, 364 Bronze Age migration, 75 budget deficits, 60 COVID-19 pandemic (2019–20), 12 guilds in, 190 immigration in, 114, 115 Jews, persecution of, 99, 104–6, 109, 220, 233 migration crisis (2015–), 342–3 Nazi period (1933–45), 104–6, 109, 124, 220, 233, 353 Neolithic migration, 74 protectionism in, 314 Reichstag fire (1933), 353 Thirty Years War (1618–48), 150 United States, migration to, 104, 107–8, 111 Weimar period (1918–33), 353 al-Ghazali, 139 Gholia, 89 Gibbon, Edward, 90 Gilder, George, 314 Gilgamesh, 38 Gillis, John, 291 Gingrich, Newton, 313 Gini coefficient, 273 Gintis, Herbert, 36 global history, 13 global price crisis (2010–11), 11 global warming, 75, 323, 325, 326–34 globalization, 4, 55, 270 backlashes against, 9, 14, 54, 57 cities and, 35 classical world, 43–50 conspiracy theories on, 323 disease and, 11, 77–9 United States and, 19 Westernization, 4 Glorious Revolution (1688), 101, 185–8, 190, 193 Goa, India, 146–7 golden nugget theory, 5 Golden Rule, 251–2 Golding, William, 219, 243, 244 Goldstone, Jack, 5, 133, 353 Goodness Paradox, The (Wrangham), 227 Google, 309, 311 Gordon, Thomas, 201 Göring, Hermann, 106 gossip, 229 Goths, 92 Gottlieb, Anthony, 135 Great Awakening (1730–55), 102 Great Depression (1929–39), 54–5, 56, 254 Great Enrichment, 167, 204 Great Recession (2007–9), 254–5, 358, 359–60 Great Transformation, The (Polanyi), 37 Great Vanishing, 134–5 Great Wall of China, 178 Greece, ancient, 127–32, 169 Athens, 47, 53, 89, 90, 131–2, 134 Axial Age, 129 cosmopolitanism, 87–8 golden nugget theory, 5 Ionian enlightenment, 127–9 Mycenae, 88 philosophy, 13, 70, 127–32, 134–5, 136 Phoenicians, relations with, 43, 44, 45, 46 science, 127–32, 136 Sparta, 47, 54, 90, 132 trade, attitudes towards, 47, 54 xenophobia in, 90 Green New Deal, 302 Greene, Joshua, 216, 259 Greenland, 51 Gregorian calendar, 137, 152 Gregory IX, Pope, 142 Gregory XIII, Pope, 152 gross domestic product (GDP), 68–9, 257, 278–9 Grotius, Hugo, 147, 152–3 groupthink, 83 Guangzhou, Guangdong, 352 guilds, 190 Gutenberg, Johannes, 146 Haber, Fritz, 105 Habsburg Empire (1282–1918) anti-Semitism in, 254 Austria, 151, 179, 190 refugees, 99 Spain, 98–9, 208 Hadrian, Roman Emperor, 91 Hadrian’s Wall, 47 Hagley Park, West Midlands, 286–7 Haidt, Jonathan, 163, 229, 344, 348, 357 Haile Selassie, Emperor of Ethiopia, 72 Hamas, 365 Hangzhou, Zhejiang, 173 Hanseatic League (1358–1862), 53 Hanson, Robin, 282 Hanway, Jonas, 298 Happy Days, 294 Harari, Yuval Noah, 38 Harriot, Thomas, 150 Hartsoeker, Nicolaas, 159 Harvard Business Review, 313 Harvard University, 116, 122, 137, 253, 309, 313 Haskell, Thomas, 206 Hässelby, Stockholm, 217–18, 245 Hayashi, Stuart, 370 Hayek, Friedrich, 1, 7, 29, 300, 325 Hebrew Bible, 248–50 Hegel, Georg Wilhelm Friedrich, 288, 365 Helm, Dieter, 328, 331 Henrich, Joseph, 36 Hercules, 87 Herodotus, 132 Hewlett-Packard, 304 Higgs, Robert, 337 Hill, Christopher, 182 Hinduism, 136, 149, 354 von Hippel, William, 24, 25, 262, 284 Hippocrates, 128 Hispanic people, 110–11 Hitler, Adolf, 104–5, 353 Hobbes, Thomas, 9, 152, 226 Hofer, Johannes, 288 Holmgren, Pär, 325 Holocaust (1941–5), 109, 220 Holy Roman Empire (800–1806), 155, 181, 288 Homestead Acts, 171 Homo economicus, 34, 36 Homo erectus, 76, 267 Homo sapiens, 3, 21, 23, 30–33, 76, 259–62, 282, 371 homosexuality, 79, 113–14, 336 Homs, Syria, 82 Honeywell, 303 Hong Kong, 53, 235, 316 Hoover, Herbert, 55 horseshoes, 203 House of Wisdom, Baghdad, 136 Household Narrative, The, 297 housing, 375–6 Huguenots, 97, 99, 101, 158, 193 human rights, 87, 147, 213 humanitarianism, 204–7 Hume, David, 151, 154, 194 Hungary, 105, 190, 235, 237, 354, 357 hunkering down, 121, 165 Huns, 93 hunter-gatherer societies death rate, 9 disease and, 78 division of labour and, 29, 32, 40–41, 57 equality matching, 262–3, 265 inbreeding and, 78 isolation and, 52 migration, 73–4, 78–9 physical fallacy, 268 race and, 232 trade, 265 tyranny of cousins, 230 Huntington, Samuel, 110, 362–3, 365–6 Hussein, Saddam, 345 Hussey, Edward, 287 Hutchins, Robert Maynard, 165 Hutus, 230–31 Hypatia, 134 hyper-fast stars, 80 IBM, 305, 307, 319 Ibn al-Haytham, 156 Ibn Hayyan, Jabir, 156 Ibn Rushd, 137–8, 143, 144, 145 ice core drilling, 49 Identity & Violence (Sen), 231 identity politics, 241 al-Idrisi, Muhammad, 137 immigration birth rates and, 115 crime and, 110, 119 culture and, 69–73, 116, 119, 120–23 disgust and, 336, 371 division of labour and, 117 empires and, 84–106 European migration crisis (2015–), 10, 114, 115, 118, 342–3 exoticism, 84 GDP and, 68 innovation and, 81–4 Islam and, 112–14, 255 labour market and, 115, 116–19 opposition to, 69, 70, 114–23, 223, 254–5 productivity and, 68, 81, 117, 204 protectionism and, 66–7 self-selection and, 107, 112 skilled vs unskilled, 66, 82, 102, 116, 117 trade and, 35, 66–7, 234–5 tribalism and, 223, 235–6, 240, 243 urban vs rural areas, 114 welfare and, 118, 281 zero-sum thinking and, 254–5, 259 immigration in United States, 102–14 crime and, 110, 119 innovation and, 81–2, 202 overestimation of, 115, 223 tribalism and, 223, 240 zero-sum thinking and, 254–5, 259 In Defence of Global Capitalism (Norberg), 270 in vitro fertilization, 298–9 inbreeding, 78 India, 42, 45, 46, 56, 75, 129, 136, 140, 146, 270 Arabic numerals, 70, 137 engineering in, 269 Hindu nationalism, 354 industrialization, 207 Maurya Empire (323–184 BC), 53 Mughal Empire (1526–1857), 98, 148, 149, 215 national stereotypes, 235 Pakistan, relations with, 366 pollution in, 326 poverty in, 276, 326 Indo-European language, 75 Indonesia, 41 Industrial Revolution; industrialization, 5, 6, 13, 54, 132, 180, 339 in Britain, 182, 188–99, 202 in China, 169, 172–3, 207 climate change and, 326 in Dutch Republic, 101 in India, 207 in Japan, 71 in United States, 202, 291–2 in Vietnam, 207 inequality, 273, 349 Inglehart, Ronald, 339 ingroups and outgroups, 217–47 fluidity, 230–38 political, 224–5, 238–42 zero-sum relationships and, 252–5 Innocent III, Pope, 233 InnoCentive, 126–7 innovation, 4, 6, 10, 27, 80 ancient world, 32, 42, 44, 46 authoritarianism and, 318 bureaucratic inertia and, 318–21 canon and, 195 cities and, 40, 53, 79 creative destruction, 57, 179, 182, 190 cultural evolution, 28 immigration and 81–4 patent systems, 189–90 population and, 27, 51, 53 Schumpeterian profits, 273–5 resistance to, 10, 179–81 zero-sum thinking and, 266–9 Inquisition, 150 France, 94, 143 Portugal, 100 Spain, 97, 98 intellectual property, 58 Intergalactic Computer Network, 307 International Monetary Fund (IMF), 117 Internet, 57, 275, 278, 306–11, 312, 313 interwar generation (1928–45), 340 Inuit, 22, 51 Ionian enlightenment, 127–9 IQ (intelligence quotient), 109 Iran, 365 Ireland, 104, 108–9, 111, 112, 379 iron, 172 Isabella I, Queen of Castile, 97 Isaiah, 46 Isaura Palaia, Galatia, 90 Isenberg, Daniel, 296 Isis, 89 Islam; Islamic world Arab Spring (2011), 10, 342 clash of civilizations narrative, 237, 365 conflict within, 365 efflorescence, 6, 53, 136–41 fundamentalism, 112, 134, 139, 351 Koran, 137, 250–51 migration from, 112–14 orthodox backlash, 148–9 philosophy, 5, 13 science, 70, 132, 136–41 values in, 112, 113 Islamic State, 351, 365–6 Islamic world, 5, 6, 13, 53, 70 Israel, 111, 365 Italy, 6, 151, 169 anti-Semitism in, 254 Fascist period (1922–1943), 105 Genoa, Republic of (1005–1797), 73, 178 guilds in, 190 Lombard League (1167–1250), 181 Ötzi, 1–2, 8–9, 73, 74 Padua, 144, 146 Papacy in, 155, 181 Renaissance, 6, 150, 153, 169 United States, migration to, 104, 109 Venice, Republic of (697–1797), 53, 144, 152, 174, 181 Jacobs, Jane, 39–40, 79, 264 James II and VII, King of England, Scotland and Ireland, 185–6 Jamestown, Virginia, 200 Japan housing in, 376 kimonos, 73 Meiji Restoration (1868), 53, 70–71 protectionism, 314 Tokugawa Shogunate (1600–1868), 54 United States, migration to, 104, 236, 335 Japanning, 156 JavaScript, 310 jealous emulation, 154–7 jeans, 73 Jefferson, Thomas, 103, 184, 201, 205 Jenner, Edward, 296 Jerusalem, 87, 251 Jesus, 250 Jews in Abbasid Caliphate, 136 anti-Semitism, 254–5, 356 Ashkenazim, 99 Babylonian captivity, 87, 249 Bible, 46, 72, 248–50 Black Death and, 355–6 in Britain, 101, 193 in Dutch Republic, 99, 100, 150 in Germany, 99, 104–6, 109, 111, 254 Inquisition and, 97, 98 in Israel, 111 Mongol invasion and, 95 Muhammed and, 251 Nazirites, 72 in Ottoman Empire, 98 persecution of, 11, 95–7, 109, 220, 233, 251, 355–6 in Poland, 111, 220 in Roman Empire, 90, 93, 94 Sephardim, 99 in Song Empire, 170 in Spain, 97, 98, 99, 140 in United States, 102, 109 Jim Crow laws (1877–1965), 106, 254 Job Buddy, 375 Jobless Future, The (Aronowitz), 312 Jobs, Steven, 82, 304 John Chrysostom, 135 John III Sobieski, King of Poland, 237, 238 Johnson, Samuel, 191, 197 Johnson, Steven, 306 Jones, Rhys, 51 Joule, James Prescott, 196 Judaism, 46, 72, 93, 94, 96, 97 Jupiter, 145 Jurchen people, 172 Justinian I, Byzantine Emperor, 134, 224 Kahn, Robert, 307 Kandinsky, Wassily, 220–21, 289 Kant, Immanuel, 154 Karakorum, Mongol Empire, 96 al-Karaouine, Morocco, 137 Kearney, Denis, 109 keels, 44 Kenya, 21–2 Khayyam, Omar, 137 al-Khwarizmi, 137 Kiesling, Lynne, 328 Kim Jong-il, 314–15 kimonos, 73 King, Martin Luther, 19 King, Steven, 111 Kipling, Rudyard, 70 Klee, Paul, 220–21, 289 Know-Nothings, 108–9 Kodak, 319 Koran, 137, 250–51 Kramer, Samuel Noah, 37, 292 Krastev, Ivan, 342–3 Krugman, Paul, 309 Ku Klux Klan, 254 Kublai Khan, 174 Kurds, 136 Kushim, 37–8 labour mobility, 69, 374–7 lacquerware, 156 lactose, 75 Lao Tzu, 129 lapis lazuli, 70 Late Bronze-Age Collapse (1200–1150 BC), 44, 49, 54 Lebanon, 43, 236 Lee, William, 179 leisure, 199 Lenin, Vladimir, 256 Lesbos, 141 Levellers, 183–4, 186 Leviathan (Hobbes), 152 Levinovitz, Alan Jay, 290 Levy, David, 205 Lewis, David Levering, 140 Libanius, 49 liberalism, 14, 183, 334–40 colonialism and, 214 disgust and, 335, 336 dynamism and, 301 economic, 185, 336 Islam and, 112–14 security and, 334–40, 378 slave trade and, 205 universities and, 163 Libya, 48, 89, 366 Licklider, Joseph Carl Robnett, 307 life expectancy, 4, 169, 339 light bulbs, 297 Lilburne, John, 183 Lincoln, Abraham, 203 Lind, Amanda, 72 Lindsey, Brink, 301 literacy, 15, 57, 168 in Britain, 188, 198 in China, 148 in Dark Ages, 50 empathy and, 246–7 in Greece, 128–9 in Renaissance, 146, 148 Lithuania, 238 Little Ice Age, 148 lobbying, 280, 329 Locke, John, 100, 152, 185, 186, 201 Lombard League, 181 London, England, 190, 193–4, 197 7/7 bombings (2005), 341 London Bridge stabbings (2019), 120 Long Depression (1873–86), 253–4 Lord of the Flies (Golding), 219, 243, 244 Lord’s Resistance Army, 365 Louis IX, King of France, 96 Louis XIV, King of France, 237 Louis XVI, King of France, 201 love, 199 Lucas, Robert, 167 Lucy, 24–5 Lugh, 89 Lul, 111 Luther, Martin, 150, 356 Lutheranism, 99, 356 Lüthi, Max, 351 Lysenko, Trofim, 162 Lyttelton family, 286 Macartney Mission (1793), 176 Macedonian Empire (808–148 BC), 84, 87–9 Madison, James, 337 madrasas, 138 Madrid train bombings (2004), 341 Maduro, Nicolás, 354, 380 Magna Carta (1215), 5 Magris, Claudio, 219 Malacca, 100 Maltesholm School, Hässelby, 217–18, 245 mammoths, 76 Manchester United, 246 Manichaeism, 93 Mann, Thomas, 79 Mansfield, Edward, 271 Mao Zedong, 53, 162, 315, 316, 317, 355 Marcus Aurelius, Roman Emperor, 91 Marduk, 87 de Mariana, Juan, 147 markets, 37 humanitarianism and, 204, 206 immigration and, 68 tribalism, 247 ultimatum game, 34–5 Marley, Robert ‘Bob’, 72 marriage, 199 Marshall, Thurgood, 335 Marx, Karl, 33, 36, 162, 169, 247, 255–6 Marxism, 33, 36, 162, 182, 256, 268 Mary II, Queen of England, Scotland and Ireland, 186, 193 Maryland, United States, 349 Maslow, Abraham, 339, 341 al-Masudi, 136 mathematics, 70, 134, 135, 137, 156 Maurya Empire (323–184 BC), 53 Mauss, Marcel, 71 McCarthy, Joseph, 335 McCarthy, Kevin, 108 McCloskey, Deirdre, 167, 189, 191–2, 198 McConnell, Addison Mitchell ‘Mitch’, 108 McKinsey, 313 measles, 77 media, 346–9, 370 Medicaid, 119 Medina, 251 Medusa, 88 Meiji Restoration (1868), 53, 70–71 Mencken, Henry Louis, 325, 353 Mercury, 89 Merkel, Angela, 343 Mesopotamia, 37–43, 45, 70, 292–3 Metaphysics (Aristotle), 142 Mexico, 73, 77, 257 United States, migration to, 110, 122, 223, 240, 255 Miami, Florida, 120 Micro-80 computers, 304 Microsoft, 305–6, 309 middle class, 60–61 Migration Advisory Committee, UK, 118 Miletus, 127 militarism, 214 Mill, John Stuart, 124, 160, 164, 176, 319 millennial generation (1981–96), 340 Milton, John, 150 Ming Empire (1368–1644), 54, 148, 175, 177–8, 179, 215 minimal group paradigm, 220–22 Minitel, 313 Mobutu Sese Seko, 187 Mokyr, Joel, 157, 195, 196–7 Molyneux, Stefan, 84 Mongol Empire (1206–1368), 53, 84, 94–7, 138, 139, 173–4, 352–3 monopolies, 182, 189 Monte Testaccio, 48 Montesquieu, 89, 94 Moral Consequences of Growth, The (Friedman), 253 Moral Man and Immoral Society (Niebuhr), 253 Moriscos, 97 mortgages, 375 Moscow Institute of Electronic Engineering, 304 most-favoured-nations clause, 53–4 Mughal Empire (1526–1857), 98, 148, 149, 215 Muhammed, Prophet of Islam, 251 Murray, William Vans, 104 Muslims migration of, 112–14, 170, 255 persecution of, 97, 106, 233, 355 Mutz, Diana, 271 Mycenae, 88 Myth of Nations, The (Geary), 288–9 Myth of the Rational Voter, The (Caplan), 258 Naipaul, Vidiadhar Surajprasad, 167 Napoleonic Wars (1803–15), 288 National Aeronautics and Space Administration (NASA), 126, 127 National Library of Medicine, US, 12 National Science Foundation, US, 313 National Security Agency, US, 313 national stereotypes, 235 nationalism, 9, 11, 13, 16 civic nationalism, 377–8 clash of civilizations narrative, 237 cultural purity and, 69, 70, 71, 352 immigration and, 69, 70, 82 nostalgia and, 287–8, 351 World War I (1914–18), 214 zero-sum thinking, 253, 254, 259, 272 nativism, 14, 122, 176, 223, 254, 349–51, 358 Natural History Museum, London, 124, 125 Naturalism, 198 Nazi Germany (1933–45), 104–6, 109, 124, 220, 233, 353 Nazirites, 72 Neanderthals, 30–33, 75, 76 Nebuchadnezzar, Babylonian Emperor, 46 neckties, 72 negative income tax, 374–5 Neilson, James Beaumont, 194 Nemeth, Charlan, 83 Neo-Classicism, 198 Neolithic period (c. 10,000–4500 BC), 74 Netflix, 309, 310 Netherlands, 99 von Neumann, John, 105 neurasthenia, 291 New Atlantis (Bacon), 147 New Guinea, 41 New Testament, 250 New York, United States crime in, 246, 334 September 11 attacks (2001), 10, 114, 340–42 New York Times, 291, 297, 325 New York University, 223 New York Yankees, 223 Newcomen, Thomas, 196 Newton, Isaac, 158–9, 201 Nicomachean Ethics (Aristotle), 131 Niebuhr, Reinhold, 253 Nietzsche, Friedrich, 365 Nîmes, France, 73 Nineteen Eighty-Four (Orwell), 230, 368 Nineveh, Assyria, 248–9 Nixey, Catherine, 134 Nobel Prize, 82, 105, 276 non-market societies, 34, 35 Nordhaus, William, 273–4 North American Free Trade Agreement (NAFTA), 63, 64 North Carolina, United States, 102 North Korea, 54, 314–15, 366 North Star, 44 nostalgia, 14, 286–95, 313, 351 Not Fit for Our Society (Schrag), 107 novels, 188–9, 246–7 nuclear power, 301, 327, 328, 329, 332 nuclear weapons, 105, 290, 306 O’Rourke, Patrick Jake, 280 Oannes, 267 Obama, Barack, 66, 240, 329 obsidian, 22, 29 occupational licensing, 376–7 Ögedei Khan, 96 Ogilvie, Sheilagh, 179 Oklahoma, United States, 218–19 Old Testament, 46, 72, 248–50 olive oil, 48 Olorgesailie, 21–2 omnivores, 299 On Liberty (Mill), 160 one-year-old children, 26 open society, 6 open-mindedness, 35, 112 Opening of the mouth’ rite, 70 Orbán, Viktor, 354, 380 de Orta, Garcia, 146–7 Orwell, George, 230, 368 Osman II, Ottoman Sultan, 148 Ottoman Empire (1299–1923), 84, 94, 98, 148, 215, 220, 237, 353 Ötzi, 1–2, 8–9, 73, 74 overpopulation, 81, 160 Overton, Richard, 183 Pacific islands, 52 Paine, Thomas, 56, 158, 247 Pakistan, 70, 366 Pallas Athena, 89 Pallavicino, Ferrante, 150 Palmer, Tom Gordon, 15 Panthers and Pythons, 243–4 Papacy, 102, 142, 143, 152, 155, 178 Papin, Denis, 179, 180 Paris, France exiles in, 152, 153 University of Paris, 140, 141–2, 143 parochialism, 216 patent systems, 58, 82, 189–90, 203, 314 in Britain, 179, 189–90, 203, 314 in China, 58 in France, 189 immigrants and, 82 in Netherlands, 189 in United States, 203 PayPal, 310 Peasants’ Revolt (1381), 208 peer review, 127 Pence, Michael, 108 penny universities, 166 Pericles, 131 Permissionless Innovation (Thierer), 299 Perry, Gina, 243 Perseus, 87–8 Persia, ancient, 84, 86–7, 88, 95, 129, 215 Abbasid period (750–1258), 136 Achaemenid Empire (550–330 BC), 86–7, 88 Greeks, influence on, 129 Mongols, influence on, 95 Safavid Empire (1501–1736), 149 Sasanian Empire (224–651), 134 personality traits, 7 Pertinax, Roman Emperor, 91 Pessimists Archive, 290, 297, 298 Pessinuntia, 89 Peters, Margaret, 66 Peterson Institute for International Economics, 60 Petty, William, 296 Philip II King of Spain, 98 Phoenicia (2500–539 BC), 43–6, 49, 70, 128–9 Phoenicia dye, 44 Phrygians, 89 physical fallacy, 267–8 Physics (Aristotle), 142 Pietists, 153 Pinker, Steven, 23, 243, 266, 324 Plague of Justinian (541–750), 77 Plato, 130, 131, 132, 134, 352 pluralism, 85, 129, 357 Plutarch, 45–6 Poland Battle of Vienna (1683), 237, 238 Dutch Republic, migration to, 99 Holocaust (1941–5), 220 immigration, 116 Israel, migration to, 111 United Kingdom, migration to, 120 United States, migration to, 108, 109 Polanyi, Karl, 37 polio, 293 pollution, 326, 347 Polo, Marco, 174 Popper, Karl, 6, 26, 127, 129, 130, 182–3, 237, 362 population density, 28 populism, 9, 13, 14, 16, 324, 379–82 authoritarianism and, 325, 350–51 complexity and, 324 nostalgia and, 295, 324, 351 trade and, 19 zero-sum thinking and, 254, 259, 274 pornography, 113, 336 Portugal Empire (1415–1999), 100, 146–7, 178 guilds in, 190 Inquisition, 100 Postrel, Virginia, 300, 312, 326 pound locks, 172 poverty, 4, 168, 213, 270 in Britain, 256 in China, 4, 316 immigration and, 66, 69, 81, 121 in Japan, 71 Jeff Bezos test, 275–9 Preston, Lancashire, 190 priests, 41, 128 printing, 146, 153, 171 Pritchard, James Bennett, 43 productivity cities and, 40 foreign trade and, 57, 59, 63 free goods and, 278 immigration and, 68, 81, 117, 204 programming, 8 Progress (Norberg), 12–13 progressives, 286, 300–302 Proserpina, 89 protectionism, 13, 15, 16, 54–5 Great Depression (1929–39), 54–5 immigration and, 66–7 Internet and, 314 Trump administration (2017–), 19, 57–8 Protestantism, 99, 104, 148, 149, 153, 169, 178, 237 Prussia (1701–1918), 153, 288 Psychological Science, 335 Puerto Rico, 80 Pufendorf, Samuel, 147 purchasing power, 59, 61, 63, 66, 198 Puritanism, 99, 102 Putin, Vladimir, 14, 353–4 Putnam, Robert, 121, 165 Pythagoras, 137 Pythons and Panthers, 243–4 al-Qaeda, 351 Qianlong, Qing Emperor, 153 Qing Empire (1644–1912), 148, 149, 151, 153, 175–7, 179 Quakers, 99, 102, 206 Quarantelli, Enrico, 338 Quarterly Journal of Economics, The, 63 race; racism, 76–7, 206, 231–4, 358–9 railways, 53, 179, 202, 296, 297 Rammstein, 274 RAND Corporation, 307 Raphael, 137 Rastafari, 72 Rattlers and Eagles, 218–19, 236, 243, 252 reactive aggression, 227–8 Reagan, Ronald, 63, 111 Realism, 198 realistic conflict theory, 222 Reconquista (711–1492), 139 Red Genies, 236 Red Sea, 75 Reformation, 148, 155 refugees crime and, 119 European migration crisis (2015–), 10, 114, 115, 281, 342–3 integration of, 117–18 German Jews (1933–45), 104–6, 109 Rembrandt, 99 reminiscence bump, 294 Renaissance, 5, 6, 132, 143, 145–6, 149–50, 215 Republic of Letters, 157–9, 165, 195 Republic, The (Plato), 352 Republican Party, 164, 225, 238, 240, 301 Reynell, Carew, 184 Reynolds, Glenn, 308 Ridley, Matthew, 20–21, 80 right to work laws, 65 Rizzo, Frank, 334 Road to Serfdom, The (Hayek), 325 Robbers Cave experiment (1954), 218–19, 236, 243, 252, 371 Robbins, Caroline, 200–201 Robertson, Marion Gordon ‘Pat’, 114 Robinson, James, 185, 187, 200 rock paper scissors, 26 Rogers, Will, 282 Roman Law, 5 Romanticism, 198, 287, 296–7 Rome, ancient, 47–50, 89–94, 132 Antonine Plague (165–80), 77 assimilation, 91–2 chariot racing, 224 Christianity in, 90, 93–4, 133–4 citizenship, 91 cosmopolitanism, 89–91 fall of, 54, 94 gods in, 89–90 golden nugget theory, 5 globalization, 45–6, 47–50 haircuts, 72 Latin alphabet, 45 philosophy, 70, 136 Phoenicians, relations with, 43, 44 Sabines, relations with, 89 Social War (91–88 BC), 91 trousers, attitudes towards, 92 Romulus, 89, 90 Rotterdam, Holland, 158 Rousseau, Jean-Jacques, 226 Royal Navy, 205 Royal Society, 156, 157, 158, 196 Rubin, Paul, 258 ruin follies, 286–7 rule of law, 68, 189, 269, 334, 343, 358, 379 Rumbold, Richard, 183–4 Rushdie, Salman, 73 Ruskin, John, 206, 297 Russia Imperial period (1721–1917), 154, 289–90 Israel, migration to, 111 Mongol period (1237–1368), 95, 352 Orthodox Christianity, 155 Putin period (1999–), 14, 15, 347, 353–4, 365, 367 Soviet period (1917–91), 162, 302–5, 315, 317 United States, relations with, 236 Yamnaya people, 74–5 Rust Belt, 58, 62, 64–6, 349 Rwandan Genocide (1994), 230–31 Sabines, 89 Safavid Empire (1501–1736), 149 safety of wings, 374 Saint-Sever, France, 180 Salamanca school, 147, 150 Sanders, Bernard, 302 Santa Fe Institute, 216 SARS (severe acute respiratory syndrome), 3, 162 Saudi Arabia, 365 Scandinavia Bronze Age migration, 75 Neolithic migration, 74 United States, migration to, 104, 108 see also Sweden scapegoats, 11, 83, 253, 268, 349, 355–61 Black Death (1346–53), 352, 355–6 Great Recession (2007–9), 255 Mongol invasion (1241), 95 Schmandt-Besserat, Denise, 38 School of Athens, The (Raphael), 137 School of Salamanca, 147, 150 Schrag, Peter, 107 Schrödinger, Erwin, 105, 128, 129, 132 Schumpeter, Joseph, 277 Schumpeterian profits, 273–5 science, 127–66 in China, 4, 13, 70, 153, 156, 162–3, 169–73 Christianity and, 133–5, 141–6, 149–50 Enlightenment, 154–9 experiments, 156–7 Great Vanishing, 134–5 in Greece, 127–32 jealous emulation and, 154–7 in Islamic world, 70, 132, 136–41 Renaissance, 145–6 Republic of Letters, 157–9, 165, 195 sclera, 25 Scotland, 101, 194 Scotney Castle, Kent, 287 Sculley, John, 304 sea peoples, 43 sea snails, 44 Seinfeld, Jerry, 224 Seleucid Empire (312–63 BC), 88 self-esteem, 372, 379 Sen, Amartya, 231 Seneca, 49, 91 Sephardic Jews, 99 September 11 attacks (2001), 10, 114, 340–42, 363 Septimius Severus, Roman Emperor, 91 Servius, Publius, 90 Seven Wonders of the World, 45 Seville, Spain, 91, 139 sex bonobos and, 226 encoding and, 233 inbreeding, 78 views on, 113, 336 SGML (Standard Generalized Markup Language), 307 Shaftesbury, Lord, see Cooper, Anthony Ashley Sherif, Muzafer, 219, 220, 222, 243, 252 Shia Islam, 149 Shining, The, 335 shirts, 72 Siberia, 76 Sicily, 89 Sierra Leone, 365 Siger of Brabant, 143, 144 Sikhism, 149 Silicon Valley, 311 Silk Road, 171, 174, 352 silver processing, 49 Simler, Kevin, 282 Simmel, Georg, 266 Simon, Julian, 81 Simple Rules for a Complex World (Epstein), 320 Singapore, 53 skilled workers, 36, 45, 66, 95, 97, 101, 117 Slater, Samuel, 202 slavery, 86, 156, 205–6, 232 in British Empire, 182, 199, 200, 205 in Mesopotamia, 40, 41, 43 in Rome, 47, 48 in Sparta, 54 in United States, 103, 106, 205, 232 smallpox, 77, 197, 293, 296 Smith, Adam, 21, 59, 192, 194, 205, 280 Smith, Fred, 319 smoke detectors, 234 Smoot–Hawley Tariff Act (1930), 55 snack boxes, 20 Snow, Charles Percy, 105 social media, 239, 347, 370 social status, 281–5 Social War (91–88 BC), 91 Socrates, 130, 131–2, 330 solar power, 328, 329, 331, 332 Solomon, King of Israel, 38, 45 Solyndra, 329 Song Empire (960–1279), 53, 169–75 Sony, 319 Soros, George, 323 South Korea, 314, 366 South Sudan, 365 Soviet Union (1922–91), 162, 302–5, 315, 317 Sovu, Rwanda, 231 Sowell, Thomas, 267–8 Spain, 97–101, 184, 207 Almohad Caliphate (1121–1269), 137–8 amphorae production, 48 al-Andalus (711–1492), 97, 137–9, 140 Columbus’ voyages (1492–1503), 178 Dutch Revolt (1568–1648), 98–9, 101 Empire (1492–1976), 147, 178, 182 guilds in, 190 Inquisition (1478–1834), 97, 98 Jews, persecution of, 97–8, 106, 140 Madrid train bombings (2004), 341 Muslims, persecution of, 97, 106 Reconquista (711–1492), 97, 138–9, 140 regional authorities, 152 Roman period (c.218 BC–472 AD), 48, 91 Salamanca school, 147, 150 sombreros, 73 Uber in, 320 vaqueros, 73 Spanish flu (1918–19), 77 Sparta, 47, 54, 90, 132 Spencer, Herbert, 165, 214 Spinoza, Baruch, 100, 150, 153 Spitalfields, London, 190 sports, 199, 223–4, 232–3, 245–6 Sri Lanka, 100, 365 St Bartholomew’s Day massacre (1572), 97 St Louis, SS, 109 Standage, Tom, 166 Stanford University, 307, 311 Star Trek, 246, 259 stasists, 301–2 Statute of Labourers (1351), 208 steam engine, 179, 180, 189, 194, 203, 296 steamships, 53, 202 Stenner, Karen, 242, 343, 348, 350, 357 Stockholm, Sweden, 217–18 Stranger Things, 294 Strasbourg, France, 153 strategic tolerance, 86–96 Strindberg, August, 239 Suarez, Francisco, 147 suits, 72 Sumer (4500–1900 BC), 37–43, 45, 55, 292–3 Summers, Larry, 329 Sunni Islam, 148, 149, 238, 365 superpowers, 338–9 supply chains, 11, 62, 66 Sweden DNA in, 73 Green Party, 325 Lind dreadlocks affair (2019), 72 immigration in, 114, 115, 118, 281 manufacturing in, 65 Muslim community, 114 Neolithic migration, 74 refugees in, 118, 281, 342 United States, migration to, 107 Sweden Democrats, 281 swine flu, 3 Switzerland, 152, 153 Sylvester II, Pope, 137 Symbolism, 198 Syria, 42, 82, 342, 365, 366 tabula rasa, 225 Tacitus, 91 Taiwan, 316, 366 Taizu, Song Emperor, 170 Tajfel, Henri, 220, 221–2 Tandy, Geoffrey, 124–6 Tang Empire (618–907), 84, 170, 177, 352 Tanzania, 257 Taoism, 129, 149 tariffs, 15, 56, 373 Anglo–French Treaty (1860), 53–4 Great Depression (1929–39), 54–5 Obama’s tyre tariffs (2009), 66 Trump’s steel tariffs (2018), 272 Tasmania, 50–53, 54 Tatars, 238 taxation in Britain, 72, 187, 188, 189 carbon tax, 330–31 crony capitalism and, 279–80 immigration and, 69 negative income tax, 374–5 in Song Empire, 172 in Spanish Netherlands, 98 Taylor, Robert, 306 TCP/IP protocol, 307 technology, 296–9 automation, 63, 312–13 computers, 302–14 decline, 51–2 Internet, 57, 275, 278, 306–11, 312 nostalgia and, 296–9, 313 technocrats, 299–300, 312, 313–14, 326–9 technological decline, 51–2 telescopes, 145–6 Teller, Edward, 105 Temple of Artemis, Ephesus, 45 Temple of Serapis, Alexandria, 134 Tencent, 311 terrorism, 10, 114, 229, 340–41, 363 Tetlock, Philip, 160 textiles, 172–3 Thales, 127 Thierer, Adam, 299 third-party punishment game, 35 Thirty Years War (1618–48), 72, 97, 148, 150 Thomas Aquinas, Saint, 142–3, 144–5 Thoreau, Henry David, 203 Thracians, 130 Thucydides, 131, 132 Tiangong Kaiwu, 153 Tibetans, 85 Tierra del Fuego, 52–3 Tigris river, 37, 139 Timurid Empire (1370–1507), 139 tin, 42 Tokugawa Shogunate (1600–1868), 54 Toledo, Spain, 140 tolerance, 86–114, 129 Tomasello, Michael, 25 ‘too big to fail’, 280 Tower of Babel, 39 Toynbee, Arnold, 382 trade, 13, 19–23, 28–9, 129, 140, 363, 373 backlashes against, 19, 54–67, 254 benefit–cost ratio, 60, 61, 62 Britain, 181–99 competitive advantage, 28–9 division of labour and, 28, 31, 57 Great Depression (1929–39), 54–5 Greece, ancient, 47 humanitarianism and, 204–7 Mesopotania, 37–43 migration and, 35, 66–7, 234–5 morality of, 33–6 Phoenicia, 43–6 Rome, ancient, 47–50 snack boxes, 20 United States, 19, 57–8, 202–3 zero-sum thinking and, 248, 252–66, 270–72 trade unions, 64, 65, 272, 374 Trajan, Roman Emperor, 91 Trans-Pacific Partnership, 58 Transparency International, 381 Treaty of Trianon (1920), 354 Treaty of Versailles (1919), 353 Trenchard, John, 201 Treschow, Michael, 65 Trevor-Roper, Hugh, 215, 356 tribalism, 14, 217–47, 362, 368–72 fluid, 230–38 political, 224–5, 238–42, 378, 379 media and, 348, 370 threats and, 241, 350, 370 Trollboda School, Hässelby, 218 Trump, Donald, 9, 14, 240, 313, 321, 322, 354, 365, 367, 380 immigration, views on, 223 presidential election (2016), 238, 241, 242, 349, 350 stasism, 301, 302 steel tariffs (2018), 272 trade, views on, 19, 57–8 zero-sum attitude, 248 Tunisia, 45, 48 Turing, Alan, 124 Turkey; Turks, 70, 74, 136, 156, 354, 357, 365 turtle theory, 121–2 Tutsis, 230–31 Twilight Zone, The, 260–61 Twitter, 84, 239, 245 Two Treatises of Government (Locke), 186, 201 tyranny of cousins, 229, 230 tyre tariffs, 66 Tyre, 45 Uber, 319–20 Uganda, 365 Ukraine, 75, 116, 365 ultimatum game, 34–6 umbrellas, 298 uncertainty, 321–6 unemployment, 62, 373–4, 376, 377 ‘unicorns’, 82 United Auto Workers, 64 United Kingdom, see Britain United Nations, 327 United States, 199–203 Afghanistan War (2001–14), 345 America First, 19, 272 automation in, 313 Bureau of Labor Statistics, 65 California Gold Rush (1848–1855), 104 China, trade with, 19, 57, 58–9, 62–3, 64 Chinese Exclusion Act (1882), 254 citizenship, 103 Civil War (1861–5), 109 climate change polices in, 328 Constitution (1789), 102, 202 consumer price index, 277 COVID-19 pandemic (2019–20), 12 crime in, 110, 119, 120, 346 Declaration of Independence (1776), 103, 201, 202 dynamism in, 301–2 Federalist Party, 103 free trade gains, 60, 61 Great Depression (1929–39), 54–5, 254 gross domestic product (GDP), 257 Homestead Acts, 171 housing in, 376 immigration, see immigration in United States Industrial Revolution, 202, 291–2 innovation in, 53, 203, 298–9 intellectual property in, 58 Internet in, 306–14 Iraq War (2003–11), 345 Jim Crow laws (1877–1965), 106, 254 Know-Nothings, 108–9 Ku Klux Klan, 254 labour mobility in, 374, 376–7 lobbying in, 280, 329 Manhattan Project (1942–6), 105 manufacturing, 62–6 McCarthy era (1947–57), 335 Medicaid, 119 middle class, 60–61 NAFTA, 63, 64 National Library of Medicine, 12 national stereotypes, 235, 236 nostalgia in, 290–92, 294 open society, 169, 199–203 patent system, 203 political tribalism in, 224–5, 238, 240 populist movement, 254 presidential election (2016), 238, 241, 242, 349, 350 railways, 202 Revolutionary War (1775–83), 102–3, 200–201 Robbers Cave experiment (1954), 218–19, 236, 243, 252, 371 Rust Belt, 58, 62, 64–6, 349 Saudi Arabia, relations with, 365 Senate, 108 September 11 attacks (2001), 10, 114, 340–42, 363 slavery in, 103, 106, 205 Smoot–Hawley Tariff Act (1930), 55 Supreme Court, 108, 335 tariffs, 66, 272 trade deficits, 60, 270 Trump administration (2017–), see Trump, Donald unemployment in, 373, 376 universities, 163–5, 241 Vietnam War (1955–75), 345 Watergate scandal (1972–4), 345 World War II (1939–45), 56, 64, 335 Yankees, 58 United Steelworkers, 64, 272 universal basic income (UBI), 374, 375 universities, 140 University Bologna, 140 University of California, Berkeley, 311 University of Cambridge, 140 University of Chicago, 165 University of Leeds, 357 University of London, 201 University of Marburg, 153 University of Oxford, 140, 144, 145, 328 University of Padua, 144, 146 University of Paris, 140, 141–2, 143 University of Pennsylvania, 271 University of Salamanca, 140 University of Toulouse, 144 unskilled workers, 36, 66, 102, 117 untranslatable words, 288 Ur, 55 urbanization, see cities Uruk, Sumer, 39 US Steel, 64 Usher, Abbott Payson, 196 Uyghurs, 85, 174 vaccines, 12, 296, 299 Vandals, 92 Vanini, Lucilio, 150 vaqueros, 73 Vargas Llosa, Mario, 213, 261 Vatican Palace, 137 Vavilov, Nikolai, 162 Venezuela, 354 Venice, Republic of (697–1797), 53, 144, 152, 174, 181 Vermeer, Johannes, 99 Vespucci, Amerigo, 146 Vienna, Austria, 95, 237, 238 Vienna Congress (1815), 288 Vietnam, 171, 207, 270, 345 Virgil, 91 Virginia Company, 200 vitamin D, 74 de Vitoria, Francisco, 147 Vladimir’s choice, 221, 252, 271 Voltaire, 153, 193 Walton, Sam, 277 Wang, Nina, 315 War of the Polish Succession (1733–8), 289–90 Ward-Perkins, Bryan, 50 warfare, 216–17, 243 Warren, Elizabeth, 302 washing of hands, 10, 335 Washington, George, 103, 205 Washington, DC, United States, 280 Watergate scandal (1972–4), 345 Watson, John, 291 Watson, Peter, 79 Watt, James, 172, 189, 194, 274 Weatherford, Jack, 95 Web of Science, 159 Weber, Maximilian, 204 WeChat, 311 Weekly Standard, 312 welfare systems, 118, 281, 374 Wengrow, David, 42 West Africa Squadron, 205 Western Roman Empire (395–480), 94, 135 Westernization, 4–5 Wheelan, Charles, 20 Whig Party, 185, 201 White House Science Council, 313 white supremacists, 84, 351, 367 Whitechapel, London, 190 Who Are We?

Shadow Work: The Unpaid, Unseen Jobs That Fill Your Day
by Craig Lambert
Published 30 Apr 2015

Indeed, service from an actual person, whether in a fine-dining restaurant or on a customer-service phone call, is a twenty-first-century luxury. NONETHELESS, IF THE work is interesting, some organizations can attract support from unpaid shadow-working assistants. The burgeoning field of citizen science is a prime example. The Galaxy Zoo project is a joint venture of astronomers at Johns Hopkins University in the United States and Portsmouth and Oxford universities in England. It enlists lay astronomers in classifying galaxies from telescope images based on shape. In its first year, more than 150,000 participants contributed more than fifty million classifications, at times sending in 60,000 per hour.

First Light: Switching on Stars at the Dawn of Time
by Emma Chapman
Published 23 Feb 2021

The Milky Way is part of a group of galaxies called the Local Group, stretching around 10 million light years across. Galaxies come in lots of different shapes and sizes, so that we can divide them into multiple morphological groups. For example, there are the spirals, the ellipticals, the irregulars and the barred spirals. The Local Group is a ‘galaxy zoo’, containing a good few of the different types. The three largest galaxies are, in order, Andromeda, the Milky Way and the Triangulum Galaxy, and they are also the only spiral galaxies in the local group. You might have heard of the Large Magellanic Cloud and Small Magellanic Cloud, which are the fourth and sixth most massive galaxies in the Local Group, but aside from them you are unlikely to have come across the others.

You've Been Played: How Corporations, Governments, and Schools Use Games to Control Us All
by Adrian Hon
Published 14 Sep 2022

Fans tout the educational potential of games like Kerbal Space Program and Factorio, both worthy of Locke’s hopes that learning become “a play and recreation,” or Arma 3’s Laws of War add-on that teaches players about the Geneva Convention.19 They contribute to citizen science games to identify astronomical oddities (Galaxy Zoo), classify coral reefs (NASA NeMO-Net), investigate protein folding (Fold.it), and map neurones in 3D (Eyewire).20 And they become outraged when anyone challenges their status, like in 2010 when movie critic Roger Ebert bizarrely suggested, “Video games can never be art.”21 Video games clearly have great potential to help educate people and advance science.