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Hive Mind: How Your Nation’s IQ Matters So Much More Than Your Own by Garett Jones
centre right, clean water, corporate governance, David Ricardo: comparative advantage, en.wikipedia.org, experimental economics, Flynn Effect, Gordon Gekko, greed is good, hive mind, invisible hand, Kenneth Arrow, law of one price, meta analysis, meta-analysis, prediction markets, Robert Gordon, Ronald Coase, Saturday Night Live, social intelligence, The Bell Curve by Richard Herrnstein and Charles Murray, The Wealth of Nations by Adam Smith, Thorstein Veblen, wikimedia commons, zero-sum game
The relationship often isn’t as strong as the relationship between, say, a person’s vocabulary test scores and her score on the Raven’s matrices, so there are many exceptions, but the results are clear: IQ scores predict practical social skills. The link between social or emotional intelligence and IQ has been tested for decades. Back in the 1920s, one early social intelligence test, the George Washington Social Intelligence Test, actually found a moderate relationship with overall IQ. That social intelligence test asked about “judgment in social situations, memory for names and faces, and recognition of the mental states behind words.”26 Another social intelligence test had people look at “film clips of brief scenes” showing people’s “emotional states, and their task was to identify that state.” Such tests have a weak to moderate relationship with a person’s IQ.27 Tests of emotional intelligence are better developed, and indeed there’s now a widely used test for “EQ,” the MSCEIT, the Mayer-Salovey-Caruso Emotional Intelligence Test.
Young people in the 1930s and young people in the 1990s alike tended to have a weak, positive relationship between their measured IQ and their later income. So the rumors of IQ’s exploding importance have turned out to be wrong so far: it’s a reasonable guess that they’ll be wrong in the future as well. The paradox of IQ is likely to be with us well into the twenty-first century. Coda: Intelligence Is a Key Ingredient in Emotional Intelligence But isn’t there more than just one kind of intelligence? Aren’t emotional intelligence and social intelligence just as important as narrow IQ-type intelligence? The ability to read people, the ability to get along well with others—those skills are important, and IQ tests can’t be measuring those skills, can they? Social skills seem so different from the abstract pattern-finding of some IQ tests—but then again, being able to remember relevant facts about people you met a few weeks ago or the ability to interpret an ambiguous social situation might involve some of the same memory and puzzle-solving skills that IQ tests try to measure.
That higher-IQ players tend to follow the third piece of advice, “Be perceptive,” is almost obvious: higher-IQ individuals are just more likely to get it, to grok the key ideas, as sci-fi writer Robert Heinlein used to say. Not always, not perfectly, but as we saw in the coda to Chapter 1, on average individuals with high IQ are better at grokking the rules of the social game, they’re more socially intelligent. And as we saw in the last chapter, IQ also tends to predict patient behavior. Those who see the patterns in the Raven’s Progressive Matrices also see the future. That means that in a repeated prisoner’s dilemma, they’ll tend to focus on the rewards of long-term cooperation, not the short-term thrills of punishment or exploitation. My final claim is that higher-IQ people are nicer than most other people—at least when they’re in settings such as the repeated prisoner’s dilemma.
The Globotics Upheaval: Globalisation, Robotics and the Future of Work by Richard Baldwin
agricultural Revolution, Airbnb, AltaVista, Amazon Web Services, augmented reality, autonomous vehicles, basic income, business process, business process outsourcing, call centre, Capital in the Twenty-First Century by Thomas Piketty, Cass Sunstein, commoditize, computer vision, Corn Laws, correlation does not imply causation, Credit Default Swap, David Ricardo: comparative advantage, declining real wages, deindustrialization, deskilling, Donald Trump, Douglas Hofstadter, Downton Abbey, Elon Musk, Erik Brynjolfsson, facts on the ground, future of journalism, future of work, George Gilder, Google Glasses, Google Hangouts, hiring and firing, impulse control, income inequality, industrial robot, intangible asset, Internet of things, invisible hand, James Watt: steam engine, Jeff Bezos, job automation, knowledge worker, laissez-faire capitalism, low skilled workers, Machine translation of "The spirit is willing, but the flesh is weak." to Russian and back, manufacturing employment, Mark Zuckerberg, mass immigration, mass incarceration, Metcalfe’s law, new economy, optical character recognition, pattern recognition, Ponzi scheme, post-industrial society, post-work, profit motive, remote working, reshoring, ride hailing / ride sharing, Robert Gordon, Robert Metcalfe, Ronald Reagan, Second Machine Age, self-driving car, side project, Silicon Valley, Skype, Snapchat, social intelligence, sovereign wealth fund, standardized shipping container, statistical model, Stephen Hawking, Steve Jobs, supply-chain management, TaskRabbit, telepresence, telepresence robot, telerobotics, Thomas Malthus, trade liberalization, universal basic income
The Oxford scholars behind the most influential study of AI automation—Carl Frey and Michael Osborne—argue that the hardest tasks for white-collar robots involve creative intelligence and, as discussed, social intelligence. Creative intelligence means being able to devise new, good ideas and solutions. By social intelligence, Frey and Osborne mean being aware of people’s reactions to events and being able to react appropriately. Typical workplace tasks that draw on social intelligence are negotiation (getting people to cooperate and reconcile differences) and persuasion (getting people to agree on ideas, ways of doing things, etc). It is also important in tasks like assisting and caring for people, providing emotional support, and the like. The parts of jobs which rely heavily on creative and social intelligence are likely to remain sheltered from robots in coming years. A related approach to the “which jobs will be sheltered from robots” question was taken in 2017 by the experts at McKinsey consulting firm in an important study, A Future that Works: Automation, Employment, and Productivity.
The list reflects the fact that management usually involves getting people to do things well and fast. Usually that also means getting people to work with each other—all things that involve social intelligence, which AI is bad at, and establishing personal rapport, trust, and motivation, which RI is bad at. Many occupations related to professional and scientific specializations also come out quite sheltered. These are jobs such as compliance officers, financial examiners, management consultants, event planners, landscape architects, and civil engineers. Again, these are rich in tasks that involve high levels of perception and manipulation, creative intelligence, or social intelligence. Many types of engineers fall into these categories since engineers are typically trying to make things work. Among the professionals, the key to being sheltered is the requirement of being good at in-person human interaction, or dealing with unstable or unknown situations.
The implication of this point is straightforward. These jobs will make our communities more local, and probably more urban. By studying the things that AI-trained robots like Amelia can already do well, we can predict that the jobs that survive competition from AI and the new jobs that will be created are those that stress humanity’s great advantages. Machines have not been very successful at acquiring social intelligence, emotional intelligence, creativity, innovativeness, or the ability to deal with unknown situations. Experts estimate that it will take something like fifty years for AI to attain top-level human performance in social skills that are useful in the workplace, like social and emotional reasoning, coordination with many people, acting in emotionally appropriate ways, and social and emotional sensing.
Superminds: The Surprising Power of People and Computers Thinking Together by Thomas W. Malone
agricultural Revolution, Airbnb, Albert Einstein, Amazon Mechanical Turk, Apple's 1984 Super Bowl advert, Asperger Syndrome, Baxter: Rethink Robotics, bitcoin, blockchain, business process, call centre, clean water, creative destruction, crowdsourcing, Donald Trump, Douglas Engelbart, Douglas Engelbart, drone strike, Elon Musk, en.wikipedia.org, Erik Brynjolfsson, experimental economics, Exxon Valdez, future of work, Galaxy Zoo, gig economy, happiness index / gross national happiness, industrial robot, Internet of things, invention of the telegraph, inventory management, invisible hand, Jeff Rulifson, jimmy wales, job automation, John Markoff, Joi Ito, Joseph Schumpeter, Kenneth Arrow, knowledge worker, longitudinal study, Lyft, Marshall McLuhan, Occupy movement, Pareto efficiency, pattern recognition, prediction markets, price mechanism, Ray Kurzweil, Rodney Brooks, Ronald Coase, Second Machine Age, self-driving car, Silicon Valley, slashdot, social intelligence, Stephen Hawking, Steve Jobs, Steven Pinker, Stewart Brand, technological singularity, The Nature of the Firm, The Wealth of Nations by Adam Smith, The Wisdom of Crowds, theory of mind, Tim Cook: Apple, transaction costs, Travis Kalanick, Uber for X, uber lyft, Vernor Vinge, Vilfredo Pareto, Watson beat the top human players on Jeopardy!
In other words, people who were good at reading emotions in other people’s eyes were also good at working together, even when they were doing so online and couldn’t see each other’s eyes at all! This suggests that social perceptiveness must actually be correlated with a much broader range of interpersonal skills that are just as useful online as face-to-face. For instance, the kind of social intelligence that lets you read emotions in people’s faces might also help you guess what other people are feeling based on what they type and help you predict how they will react to various things you might type back. In other words, the social skills and social intelligence that are so important in a face-to-face world may be at least as important in the increasingly online world of our future. COGNITIVE DIVERSITY MATTERS, TOO In another study,13 we looked at diversity of cognitive style—differences in how people habitually think about the world.
Interpersonal skills may be even more important than we think. I think one of the most overlooked human capabilities that machines will not fully replace anytime soon is interpersonal skills. This opinion is partly based on the research I described in chapter 2, where we found that the collective intelligence of groups depended as much on the social intelligence of the group members as on their cognitive intelligence. It’s also consistent with my own personal observation that the people who succeed in life often seem to be the ones with the most social intelligence, not necessarily the most cognitive intelligence. Now, computers are certainly making progress with their interpersonal skills. For example, my colleagues Roz Picard and Cynthia Breazeal, at the MIT Media Lab, have done fascinating research on how computers can both detect and influence human emotions.8 But I suspect that computers are likely to make much faster progress on cognitive tasks than emotional and interpersonal ones.
That’s the situation our distant human ancestors faced, with one major difference: ancient humans weren’t alone; they lived in groups. In fact, their brains were hardwired to help them connect with each other. Relative to what a similar animal of their body size would need, humans have by far the largest brains in the animal kingdom. And much of that extra brain volume appears to be devoted to what you might call social intelligence.6 If you look at the whole range of primates, including monkeys, apes, and humans, the species whose brains have larger neocortex regions also form larger social groups.7 And that ability to participate effectively in larger social groups was one of the most important evolutionary advantages of our bigger brains. Perhaps the most important reason was that groups could protect themselves from predators much more effectively than individuals could.8 A few people in a group can watch for lions while the others eat mangoes.
Genesis: The Deep Origin of Societies by Edward O. Wilson
In essence, humans progressed to the level of eusociality by essentially the same route as a few other mammal species, for example African wild dogs. They created nest sites, protected by some of the group, from which others could depart to hunt and forage. Upon return of the hunters and gatherers, the food could be distributed around the entire group. This adaptation led to cooperation and a division of labor based on a relatively high level of social intelligence. The scenario shared among many scientists is as follows. About a million years ago the controlled use of fire was achieved. Firebrands from lightning strikes carried to other sites bestowed enormous advantages on all aspects of our ancestors’ existence. The control of fire improved the yield of meat, allowing more animals to be flushed and trapped. Animals killed by the brush fire were also often cooked by it.
The impetus was the cooking of meat, as I’ve cited here, first by lightning-struck ground fires scavenged by the tribal hunters, and later by firebrands carried from site to site. Cooked meat is a high-energy and very digestible food, easily transported by groups on the move. It led to the clustering of band members and gave advantage to conversation and the division of labor. Cooperative and altruistic behavior in service to the group as a whole were achieved in mental evolution. Social intelligence became premium. The campsite talk of the early Homo, beginning with habilis-grade populations, can only be guessed. A general idea of its content can, however, be deduced from conversations within groups of the remaining contemporary hunter-gatherers. Given the importance of this evidence, it is surprising how slow in coming have been careful analyses of the conversations. One, of the Ju/’hoansi (!
., 83–84 Ropalidia marginata (wasp), 93 Saturn, 34 savannas, human evolution and, 112, 113 science: experimentation in, 21, 48, 78, 88–90, 91–92, 103 field observation in, 21, 48, 78, 88–89, 103 human condition and, 9 scientific theory, testing of, 77 Scolytidae (bark beetles), 68 sexual reproduction: DNA exchange in, 31, 35 eusociality and, 63 invention of, 35 mating swarms in, 51 social behavior, 9 evolution of, 71–72, 73, 74–75 in insects, 71–72 origin of, 77 see also eusociality social evolution, 87, 90, 121 competition and, 112 group selection and, 90 social insects, 26, 64, 70 colonies of, see eusocial insect colonies competition in, 91–93 cooperation in, 93–94 evolution of larvae in, 84–85 policing and, 90–91 worker population size and, 89–90 social intelligence, 123 social interaction, 125 social mammals, cooperation among, 58–59 social spiders, 95 social wasps, 67, 93–94 societies: biological evolution of, 18 see also eusociality; groups societies, evolution of: in chironomid midges, 51 evidence for, 51–61 societies, origin of, 31, 32, 35–38 altruism and, 48 sociobiology, sociobiologists, 22, 64, 99, 103 solitary bees, as preadapted to eusociality, 75, 77–78 speciation, 110 see also evolution by natural selection species: definition of, 17, 18 populations of, 17, 18 sphecid (mud dauber) wasps, 69, 73, 74–75 Sphecomyrma, 111 Standen, Emily M., 24 starlings, 52, 54–55, 56, 57 stingless bees (tribe Meliponini), 70 storytelling, 122, 123–25 superorganisms, 18, 78 termites, 18, 24, 64, 67, 69, 70 cockroaches as ancestors of, 96, 98–99 eusocial colonies of, 35–38, 60 evolution of eusociality in, 96–97 Teseo, Serafino, 91 theory, scientific testing of, 77 Theridiidae (cobweb spiders), 95 thrips, 64, 69 Tianmen Mountain, 44 tribalism, 10 Tschinkel, Walter R., 89 Tsuji, Kazuki, 91 vervets, reciprocity among, 36 vespid wasps, 68, 73 warfare, 120 among chimpanzees, 116–18 group selection and, 118 among human societies, 118–19, 120–21, 121 wasps, see also specific species wasps, social, 64 evolution of eusociality in, 73 Wiessner, Polly W., 123–25 Wilson, David Sloan, 87 wolves, pack competition among, 89 worker castes, 24, 60, 67–68, 78, 84–85 Yanomamö, 119, 121 Yellowstone National Park, 89 young, progressive care of, 72, 74–75 ALSO BY EDWARD O.
Head, Hand, Heart: Why Intelligence Is Over-Rewarded, Manual Workers Matter, and Caregivers Deserve More Respect by David Goodhart
active measures, Airbnb, Albert Einstein, assortative mating, basic income, Berlin Wall, Bernie Sanders, big-box store, Boris Johnson, Branko Milanovic, British Empire, call centre, Cass Sunstein, central bank independence, centre right, computer age, corporate social responsibility, COVID-19, Covid-19, David Attenborough, David Brooks, deglobalization, deindustrialization, delayed gratification, desegregation, deskilling, different worldview, Donald Trump, Elon Musk, Etonian, Fall of the Berlin Wall, Flynn Effect, Frederick Winslow Taylor, future of work, gender pay gap, gig economy, glass ceiling, illegal immigration, income inequality, James Hargreaves, James Watt: steam engine, Jeff Bezos, job automation, job satisfaction, John Maynard Keynes: Economic Possibilities for our Grandchildren, knowledge economy, knowledge worker, labour market flexibility, longitudinal study, low skilled workers, Mark Zuckerberg, mass immigration, new economy, Nicholas Carr, oil shock, pattern recognition, Peter Thiel, pink-collar, post-industrial society, post-materialism, postindustrial economy, precariat, reshoring, Richard Florida, Scientific racism, Skype, social intelligence, spinning jenny, Steven Pinker, superintelligent machines, The Bell Curve by Richard Herrnstein and Charles Murray, The Rise and Fall of American Growth, Thorstein Veblen, twin studies, Tyler Cowen: Great Stagnation, universal basic income, upwardly mobile, wages for housework, winner-take-all economy, women in the workforce, young professional
A person is unlikely to do well in exams or rise in an organization—whether an inner-city gang or a multinational corporation—without a decent measure of general intelligence. But that is a necessary, not a sufficient condition of what one might call general human capability, which also requires social intelligence, judgment, imagination, and so on. These are qualities that are only partially captured by IQ-type tests—or, indeed, exams more generally. We know, for example, that some people with very high cognitive functioning, and usually very high IQs, are “on the spectrum” for autism and lack social intelligence. Most of us have no idea of our own IQ or that of the people we work with and know well, but we do have a sense of some people being “brighter” than others. However, it is not a given that the people we regard as the brightest people in our social circles would also be those with the highest IQs.
But inclusions often require new exclusions, in this case those who do not have the good fortune or aptitude to acquire a university degree—which is a majority of adults in most rich countries. And people no more earn their upbringing or innate intelligence than they earn being born into a rich family. Although IQ-type tests and exams measure raw cognitive ability, they do not capture things like social intelligence and imagination that we today associate with a rounded, capable person. Intelligence is a complex, fuzzy, and often highly context-dependent phenomenon, as I will unpack in Chapter Three, but in the United Kingdom, United States, and France—though less so elsewhere in continental Europe—it is the most abstract forms of reasoning that have historically attracted the most prestige. Michael Young argued sixty years ago, in his critique of meritocracy, that people blessed with advanced cognitive skills can feel less obligation to those of below-average intelligence than the rich felt traditionally to the poor.
One reason why the language and methods of cognitive assessment have swept all before it in recent years is because they appear to make selecting people fair and easy to measure. Indeed, one of the reasons for the academic drift in education is that it is easier to mark and measure written tests than tests of manual skill or speaking ability. This means that people with reasonable ability in writing skills and a university degree are often preferred even in forms of employment, such as a manager in a department store, suitable to someone with high social intelligence or so-called domain-specific skills derived from long experience of doing one thing. Is a better balance between Head, Hand, and Heart achievable? Yes. Human norms and values lie behind the market signals of supply and demand, and they can change with surprising speed as we may witness in the aftermath of the Covid-19 crisis. In most European countries at least 40 percent of the economy is under direct or indirect public control (the figure is a bit less in the United States), and the corporate sector is sensitive to shifts in public attitudes and values.
The Education of Millionaires: It's Not What You Think and It's Not Too Late by Michael Ellsberg
affirmative action, Black Swan, Burning Man, corporate governance, creative destruction, financial independence, follow your passion, future of work, hiring and firing, job automation, knowledge worker, lateral thinking, Lean Startup, Mark Zuckerberg, means of production, mega-rich, meta analysis, meta-analysis, new economy, Norman Mailer, Peter Thiel, profit motive, race to the bottom, Sand Hill Road, shareholder value, side project, Silicon Valley, Skype, social intelligence, Steve Ballmer, survivorship bias, telemarketer, Tony Hsieh
You have to do all of this advice giving with clean intentions, with humility, and in a total spirit of service. Usually, you can’t do it right away. You must already have built up some rapport and trust together. And you must do it extremely tactfully, with a great deal of social intelligence. (If you feel you need to brush up on your own social intelligence—including your sense of tact—a great place to start is the book Social Intelligence: The New Science of Human Relationships by Daniel Goleman. I highly recommend this book: social intelligence is something we learn almost nothing about in our formal education.) With all these caveats in place, if you can give someone a loving wake-up call in an area of their life where they’ve got a major blind spot, or just some well-placed advice that helps them overcome a problem or get one step closer to an important goal, they will be forever grateful.
Langan in turn possessed little of this kind of intelligence, and thus was never able to gain much of a toehold in the world of practical achievement. In his book, Gladwell shows that once a person has demonstrated passable logical, analytic, and academic skills, other factors have much more influence on real-world results—specifically, creativity, innovative thinking, and practical and social intelligence. To the extent that we develop these aptitudes in our lives, we tend to do so out in the real world, not in formal institutions.5 This book is your guide for developing practical success skills in the real world. I focus on seven key skills that will be crucial if you want to succeed in your work and career. These practical skills are not meant to be a replacement for college. Indeed, a classic college education—in its most elite conception—is not meant to teach practical skills at all.
See Brand of you Self-education andragogy versus pedagogy bootstrapping of business skills for entrepreneurs and e-books “education of millionaires” skills and Internet lifelong learning non-graduate success profiles practical versus academic intelligence and success Shaw, George Bernard Simmons, Joseph Simmons, Russell on contributing needs, focus on Skyes, Charles Smith, “Beedle,” Smith, Brent Social intelligence SPIN Selling Spirituality advice, giving to mentors and successful persons Stanley, Thomas J. Startup Genome Project Stier, Debbie Strauss, Ferdinand Stumpf, Joe Success and educating self. See Self-education entrepreneurial versus employee mind-set expertise, teaching to others and luck and relationships and risk-taking self-created. See Entrepreneurs skills of success and spiritual struggle value, relationship to money Sullivan, Dan Summit Series Systems theory Taylor, Mark, on higher education, problems of Teachers.
Against Empathy: The Case for Rational Compassion by Paul Bloom
affirmative action, Albert Einstein, Asperger Syndrome, Atul Gawande, Columbine, David Brooks, Donald Trump, effective altruism, Ferguson, Missouri, impulse control, meta analysis, meta-analysis, Paul Erdős, period drama, Peter Singer: altruism, publication bias, Ralph Waldo Emerson, replication crisis, Ronald Reagan, social intelligence, Stanford marshmallow experiment, Steven Pinker, theory of mind, Walter Mischel, Yogi Berra
Some people use empathy as referring to everything good, as a synonym for morality and kindness and compassion. And many of the pleas that people make for more empathy just express the view that it would be better if we were nicer to one another. I agree with this! Others think about empathy as the act of understanding other people, getting inside their heads and figuring out what they are thinking. I’m not against empathy in that sense either. Social intelligence is like any sort of intelligence and can be used as a tool for moral action. We will see, though, that this sort of “cognitive empathy” is overrated as a force for good. After all, the ability to accurately read the desires and motivations of others is a hallmark of the successful psychopath and can be used for cruelty and exploitation. The notion of empathy that I’m most interested in is the act of feeling what you believe other people feel—experiencing what they experience.
But there is a related sense that has to do with the capacity to appreciate what’s going on in the minds of other people without any contagion of feeling. If your suffering makes me suffer, if I feel what you feel, that’s empathy in the sense that I’m interested in here. But if I understand that you are in pain without feeling it myself, this is what psychologists describe as social cognition, social intelligence, mind reading, theory of mind, or mentalizing. It’s also sometimes described as a form of empathy—“cognitive empathy” as opposed to “emotional empathy,” which is most of my focus. Later in this chapter, I’ll talk about cognitive empathy, rather critically, but right now we should just keep in mind that these two sorts of empathy are distinct—they emerge from different brain processes, they influence us in different ways, and you can have a lot of one and a little of the other.
Successful therapists and parents have a lot of cognitive empathy, but so too do successful con men, seducers, and torturers. Or take bullies. There is a stereotype of bullies as social incompetents who take their frustrations out on others. But actually, when it comes to understanding the minds of people, bullies might be better than average—more savvy about what makes other people tick. This is precisely why they can be so successful at bullying. People with low social intelligence, low “cognitive empathy”? Those are more often the bullies’ victims. I’ll end with a classic fictional example of the power of cognitive empathy. This comes from George Orwell’s 1984—not in the character of the protagonist Winston Smith but in that of O’Brien, who deceives Winston into thinking of him as a friend but later reveals himself as an agent of the Thought Police and ultimately becomes Winston’s torturer.
The Mind in the Cave: Consciousness and the Origins of Art by David Lewis-Williams
Instead, we can move on to see what mental modules Mithen identifies and how he believes the generalization of these modules explains what happened at the Transition. He proposes four mental modules: – social intelligence, – technical intelligence, – natural history intelligence, and – linguistic intelligence. For instance, anatomically archaic people (who did not have generalized intelligence) could learn multi-stage procedures for making stone artefacts (technical intelligence), but this degree of complexity could not spill over into elaborate kinds of social relations (social intelligence). Indeed, he argues that there was little interaction, or accessibility, between intelligence modules prior to the Transition. The minds of archaic people were like Swiss army knives: they comprised a set of gadgets each dedicated to a specific task.
Yet, even though hominids such as the Neanderthals had it, visual symbolism arose, or at any rate flowered, only at the Transition (some researchers argue for an earlier date for the first signs of symbolic behaviour). So, what happened? Prior to the Transition, intentional communication and classification were probably sealed in the social intelligence chapel, while mark-making and the attribution of meaning, which both implicate material objects, were probably ensconced in chapels of non-social intelligence. At the Transition, accessibility between chapels made art possible by allowing intentional communication to escape into the domain of mark-making. Some reservations Evolutionary psychology as a sub-discipline has its critics.10 Unfortunately, there is a muddying of the waters with political correctness. Some critics find that the tenets of evolutionary psychology are uncomfortably close to freemarket economics, which they abhor.
At this time of neurological demolition, new mental abilities became viable. For instance, metaphorical thought became possible as a result of traffic between chapels. People could think of, say, social relations in terms of natural history intelligence – thus totemism was born: people could speak of human groups as if they were animal species. Similarly, anthropomorphism (the ascription of human characteristics to animals) was achieved by traffic from social intelligence through to the chapel of natural history: animals became like people. Then, too, for the comparatively complex subsistence strategies of the Upper Palaeolithic there had to be traffic between technical intelligence and natural history intelligence. Improved hunting equipment (technical intelligence) was of no use without integrating it with knowledge of the environment in which it was to be used and the behaviour of the animals to be hunted (natural history intelligence).
Catching Fire: How Cooking Made Us Human by Richard Wrangham
The social brain hypothesis is very important in explaining a major benefit of being intelligent. Indeed, the advantages are so strong that we might expect all social primates to have developed big brains and high intellect. Yet there is wide variation. Lemurs are as small-brained as typical mammals. Apes have bigger brains than monkeys, and humans have the biggest brains of all. The social brain hypothesis does not explain these variations. It sets up this problem: if social intelligence is so important, why do some group-living species have smaller brains than others? Diet provides a major part of the answer. In 1995 Leslie Aiello and Peter Wheeler proposed that the reason some animals have evolved big brains is that they have small guts, and small guts are made possible by a high-quality diet. Aiello and Wheeler’s head-spinning idea came from the realization that brains are exceptionally greedy for glucose—in other words, for energy.
Species with relatively low muscle mass have been found to have relatively large brains. The general lesson is that bigger brains must be paid for somehow. How animals with small guts make use of their energy savings depends on what matters to them. In primates the tendency to use energy saved by smaller guts for added brain tissue is particularly strong, presumably because most primates live in groups, where extra social intelligence has big payoffs. The expensive tissue hypothesis predicted that major rises in human brain size would be associated with increases in diet quality. Aiello and Wheeler identified two such rises. The first brain-size expansion was around two million years ago from australopithecines to Homo erectus. In line with the Man-the-Hunter scenario, the scientists credited this rise in brain size to the increased eating of meat.
“Effect of Cooking Temperature and Cooking Time on Warner-Bratzler Tenderness Measurement and Collagen Content in Rabbit Meat.” Meat Science 66:91-96. Conklin-Brittain, N., R. W. Wrangham, and C. C. Smith. 2002. “A Two-Stage Model of Increased Dietary Quality in Early Hominid Evolution: The Role of Fiber.” In Human Diet: Its Origin and Evolution, P. Ungar and M. Teaford, eds., 61-76. Westport, CT: Bergin & Garvey. Connor, R. C. 2007. “Dolphin Social Intelligence: Complex Alliance Relationships in Bottlenose Dolphins and a Consideration of Selective Environments for Extreme Brain Size Evolution in Mammals.” Philosophical Transactions of the Royal Society of London Series B 362:587-602. Coon, C. S. 1962. The History of Man: From the First Human to Primitive Culture and Beyond., 2nd ed. London: Jonathan Cape. Coppinger, R., and L. Coppinger. 2000.
The Age of the Infovore: Succeeding in the Information Economy by Tyler Cowen
Albert Einstein, Asperger Syndrome, business cycle, Cass Sunstein, cognitive bias, David Brooks, en.wikipedia.org, endowment effect, Flynn Effect, framing effect, Google Earth, impulse control, informal economy, Isaac Newton, loss aversion, Marshall McLuhan, Naomi Klein, neurotypical, new economy, Nicholas Carr, pattern recognition, phenotype, placebo effect, Richard Thaler, selection bias, Silicon Valley, social intelligence, the medium is the message, The Wealth of Nations by Adam Smith, theory of mind
Now, I receive all sorts of email, so this didn’t sink in immediately. At first I found it vaguely insulting, a bit like the “crank” emails I receive with conspiracy theories about the Federal Reserve System. But I investigated the question further and the more I read about the phenomenon, the more I saw that, while I do not fit the typical public conception of an autistic or suffer from “low social intelligence,” I have many of the cognitive strengths and weaknesses of autism. In other words, I have an autistic cognitive style. I’ve since come to believe that this is a common cognitive pattern, including among some very successful people. I was surprised by Kathleen’s message. A forty-one-year-old upper-middle-class white male who all his life felt like he belonged to the dominant group in American society, was suddenly faced with the suggestion that he could be part of a minority, and a very beleaguered minority at that.
That’s one view, but it is a hypothesis, not a fact. We could just as easily produce another hypothesis and say that the “real autistics” are the successful people who are very consistently autistic but never diagnosed because they achieve high social status and maybe they had happy childhoods as well. They’ve mastered autistic styles of learning and so they have many achievements, including a good working grasp of social intelligence. Success stories don’t have to be classified as cases of “mild autism”; they may well be better understood as cases of effective autistic learning. In the field of autism research, scientific breakthroughs have come from researchers who are themselves autistic. Michelle Dawson, an autistic researcher in Montreal, insisted to her colleagues that they pursue the notion of giving the Raven’s Progressive Matrices IQ test to autistics.
., 49 Amazon.com, 47, 62, 85 amusia, 179–80 Anarchy, State, and Utopia (Nozick), 142 Andersen, Hans Christian, 166 animal intelligence, 224 AOL, 47 Argentina, 206–7 Ariely, Dan, 80–81, 124 articulable interests, 87 Asperger, Hans, 28, 189–90 Asperger’s LiveJournal discussion group, 35 Asperger’s syndrome and aesthetic values, 174, 180–81 behaviors and traits associated with, 30–31 community building in, 214 and discrimination, 197 high achievers with, 23, 24, 26, 166–67 media coverage of, 34, 154 perseverations, 169 relation to autism, 22 and support groups, 23–24, 35 Atkinson, Michael, 157 atonal music, 182–86, 187, 188 attention spans, 53–55 Attwood, Tony, 213 Australia, 207 authenticity, 142–46 autism and autistic individuals, 15–40 behaviors and traits associated with, 30–31 (see also specific traits) and Buddhism, 92–94 as a cognitive profile, 17–18, 194 cognitive strengths associated with, 15, 17–19, 21, 23, 30, 37, 39, 40, 57, 166–67, 189 cognitive weaknesses associated with, 19–20, 21, 27, 37, 57, 166 and communication, 20, 35, 73–74, 132–33, 168, 212–13, 218 defining, 16–17, 23, 39–40 diagnostic criteria for, 39 and education, 107, 109–11, 115, 215 in fiction, 147–48, 160–66 (see also Holmes, Sherlock) high achievers with, 23, 24–26, 28–30, 166–68, 180–82 mobilizing talents of, 214–15 and politics, 194–200, 203, 209 public perception of, 15–16, 22, 31, 32–33, 176, 221–22 rates of, 36, 37–38 “recovery” from, 26–27 social hostility toward, 38–39 social intelligence and interactions, 20–21, 27, 31–35, 170, 212 and stories, 129–32, 135–36, 140–41 variance of outcomes in, 21, 23, 39 See also Asperger’s syndrome; neurodiversity Autreat conference, 152 Baggs, Amanda, 35 Bailenson, Jeremy, 86–87 Bainbridge, David A., 34 Barber, Benjamin R., 198 Baron-Cohen, Simon, 24 Bartók, Béla, 166 beauty, 41. See also aesthetic values Bedpost.com, 11–12 behavioral economics, 124–25, 126 Bell, Gordon, 98 Bell, Joseph, 160 Belmonte, Matthew, 28–29 Bewitched, 128 Bildungsroman (life development story), 119 Bittman, Mark, 56 BitTorrent, 24 Black, Fischer, 96–97 Blackburn, Jared, 170 Blogger.com, 47 blogs, 45–46, 74–78, 85–86, 119 Bollywood, 127 Boswell, James, 168 Bourdieu, Pierre, 177 Boyden, Ed, 97 Brafman, Ori, 124 Brafman, Rom, 124 Bridgewater Treatise (Roget), 29 Brightkite.com, 12 Brochet, Frederic, 79 Buddhism, 91–96, 99–100, 105, 191 Buffett, Warren, 30 Burke, Edmund, 203 business meetings, 114 Canada, 207 Carr, Nicholas, 54 Carroll, Lewis, 166 catastrophe in art, 175 Cavendish, Henry, 166 The Celestine Prophecy (Redfield), 101 cell phones, 72, 76 Cervantes Saavedra, Miguel de, 120 Chapman, Sandi, 32 children with autism, 37 Chile, 206–7 choice at the margin, 143, 144, 145 Chopra, Deepak, 101 Cicero, 89 CNN.com, 135 Cohen, Bram, 24 collecting, 102–5 communication, 65–89 and autistics, 20, 32, 35, 73–74, 132–33, 168, 212–13, 218 email, 66, 67–68, 70, 71, 78 Facebook, 81–84 and framing effects, 78–81, 82–83, 89 importance of the medium, 65, 67, 69 instant messaging (IM), 50–51, 66–71, 84 micro-blogging, 74–78 print media, 43–44, 66, 201 RSS (Really Simple Syndication), 85–86 texting, 72–74 verbal communication, 20, 35 written communication, 35, 213 community building, 214 compassion for others, 32–35 competition, 89, 142 complements, problem of, 102–3 concentration.
Alchemy: The Dark Art and Curious Science of Creating Magic in Brands, Business, and Life by Rory Sutherland
3D printing, Alfred Russel Wallace, barriers to entry, basic income, Black Swan, butterfly effect, California gold rush, call centre, Captain Sullenberger Hudson, Cass Sunstein, cognitive dissonance, Daniel Kahneman / Amos Tversky, Dava Sobel, delayed gratification, Donald Trump, double helix, Downton Abbey, Elon Musk, Firefox, George Akerlof, gig economy, Google Chrome, Google X / Alphabet X, Grace Hopper, Hyperloop, Ignaz Semmelweis: hand washing, IKEA effect, information asymmetry, James Dyson, John Harrison: Longitude, loss aversion, low cost airline, Mason jar, Murray Gell-Mann, Peter Thiel, placebo effect, race to the bottom, Richard Feynman, Richard Thaler, Rory Sutherland, shareholder value, Silicon Valley, social intelligence, Steve Jobs, supply-chain management, the map is not the territory, The Market for Lemons, The Wealth of Nations by Adam Smith, ultimatum game, universal basic income, Upton Sinclair, US Airways Flight 1549, Veblen good
After all, any theatre selling tickets at a discount clearly has plenty to spare, and from this it might be reasonable to infer that the entertainment on offer isn’t all that good. No one wants to spend £100–£200 on tickets, a meal, car-parking and babysitting, only to find that you would have had more fun watching television at home; in avoiding discounted theatre tickets, people are not being silly – they are showing a high degree of second-order social intelligence. Despite my friend’s discovery, her colleagues continued to demand that she discount tickets. She patiently explained to them that any discount would reduce the demand, so that they would end up selling fewer tickets at a lower price, but they would insist that she included a discount anyway. They persisted in acting this way because, even though it was empirically the wrong thing to do, in economic terms it sounded logical.
Not only would we reliably infer from the presence of tables and chairs that the café is open, I also believe we go deeper still – I think we subliminally deduce that any place that goes to the trouble of erecting chairs on the street will serve coffee that, at the very least, is unlikely to be terrible. That seems a silly use of mental energy – surely the way to determine whether the coffee is good is to buy one and find out? ‘I knew the coffee was going to be good because of the chairs,’ sounds like a very silly sentence, but hold on a moment – maybe, using psycho-logic and a bit of social intelligence, we can identify a connection. For a start, someone who invests in new chairs and goes to the trouble of placing them on the pavement every day is not lazy, and has also invested in their business. Furthermore, they seem to expect their business to be a success – had they not, they would not have undertaken the expense. The chairs don’t promise perfection, but they are a reliable indicator of at least reasonable quality.
Install technology that optimises this narrow function. Declare success, using metrics based on your original definition of function. Capture cost savings for yourself and walk away. The overly simplistic model of advertising assumes that we ask ‘What is the advertisement saying?’ rather than ‘What does it mean that the advertiser is spending money to promote his wares?’, even though we clearly use social intelligence to decode the advertising we see. An example that emphasises the significance of our interpretation of information occurred in eastern Europe under communism; when a product was advertised there, demand often went down. This was because under communism anything desirable was in short supply, so people inferred that the government would only promote something that was of such hopelessly crappy quality that people wouldn’t be willing to queue for it.
Emergence by Steven Johnson
A Pattern Language, agricultural Revolution, Brewster Kahle, British Empire, Claude Shannon: information theory, complexity theory, Danny Hillis, Douglas Hofstadter, edge city, epigenetics, game design, garden city movement, Gödel, Escher, Bach, hive mind, Howard Rheingold, hypertext link, invisible hand, Jane Jacobs, Kevin Kelly, late capitalism, Marshall McLuhan, mass immigration, Menlo Park, Mitch Kapor, Murano, Venice glass, Naomi Klein, new economy, New Urbanism, Norbert Wiener, pattern recognition, pez dispenser, phenotype, Potemkin village, price mechanism, profit motive, Ray Kurzweil, slashdot, social intelligence, Socratic dialogue, stakhanovite, Steven Pinker, The Death and Life of Great American Cities, The Wealth of Nations by Adam Smith, theory of mind, Thomas Kuhn: the structure of scientific revolutions, traveling salesman, trickle-down economics, Turing machine, Turing test, urban planning, urban renewal, Vannevar Bush
The brain has increased threefold in size in the 3 million years since Australopithecus afarensis evolved, going from around 400 cubic centimeters to its current size of about 1350 cubic centimeters. The increase in brain size is likely to have had many causes, but one key factor upon which many theorists agree is the need for greater social intelligence shorthand for the ability to process information about the behavior of others and to react adaptively to their behavior. It is likely that there was a need for greater social intelligence because the vast majority of nonhuman primate animals are social animals, living in groups that range from as few as two individuals to as many as two hundred.” Baron-Cohen, 13–14. We don’t know: “. . . the network of the brain is created by cellular movement during development and by the extension and connection of increasing numbers of neurons.
That exploitation—a furtive pass concealed from the alpha male—is only possible because he is capable of building theories of other minds. Is it conceivable that this skill simply derives from a general increase in intelligence? Could it be that humans and their close cousins are just smarter than all those other species who flunk the mind-reading test? In other words, is there something specific to our social intelligence, something akin to a module hardwired into the brain’s CPU—or is the theory of minds just an idea that inevitably occurs to animals who reach a certain threshold of general intelligence? We are only now beginning to build useful maps of the brain’s functional topography, but already we see signs that “mind reading” is more than just a by-product of general intelligence. Several years ago, the Italian neuroscientist Giaccamo Rizzollati discovered a region of the brain that may well prove to be integral to the theory of other minds.
That social complexity demands formidable mental skills: instead of outfoxing a single predator, or caring for a single infant, humans mentally track the behavior of dozens of individuals, altering their own behavior based on that information. Some evolutionary psychologists believe that the extraordinary expansion of brain size between Homo habilis and Homo sapiens (brain mass trebled over the 2-million-year period that separates the two species) was at least in part triggered by an arms race between Pleistocene-era extroverts. If successfully passing on your genes to another generation depended on a nuanced social intelligence that competed with other social intellects for reproductive privileges, then it’s not hard to imagine natural selection generating a Machiavellian mental toolbox in a surprisingly short period. The group element may even explain the explosion in sheer cranial size: social complexity is a problem that scales well—build a module that can analyze one person’s mind, and all you need to do is throw more resources at the problem, and you can analyze a dozen minds with the same tools.
The Patterning Instinct: A Cultural History of Humanity's Search for Meaning by Jeremy Lent
"Robert Solow", Admiral Zheng, agricultural Revolution, Albert Einstein, Alfred Russel Wallace, Atahualpa, Benoit Mandelbrot, Bretton Woods, British Empire, Buckminster Fuller, Capital in the Twenty-First Century by Thomas Piketty, cognitive dissonance, commoditize, complexity theory, conceptual framework, dematerialisation, demographic transition, different worldview, Doomsday Book, en.wikipedia.org, European colonialism, failed state, Firefox, Francisco Pizarro, Georg Cantor, happiness index / gross national happiness, hedonic treadmill, income inequality, Intergovernmental Panel on Climate Change (IPCC), Internet of things, invention of gunpowder, invention of writing, Isaac Newton, Johann Wolfgang von Goethe, Johannes Kepler, Lao Tzu, Law of Accelerating Returns, mandelbrot fractal, mass immigration, megacity, Metcalfe's law, Mikhail Gorbachev, Nicholas Carr, Norbert Wiener, oil shale / tar sands, out of africa, peak oil, Pierre-Simon Laplace, QWERTY keyboard, Ray Kurzweil, Sapir-Whorf hypothesis, Scientific racism, scientific worldview, shareholder value, sharing economy, Silicon Valley, Simon Kuznets, social intelligence, South China Sea, Stephen Hawking, Steven Pinker, technological singularity, the scientific method, theory of mind, Thomas Kuhn: the structure of scientific revolutions, Thomas Malthus, Thorstein Veblen, Turing test, ultimatum game, urban sprawl, Vernor Vinge, wikimedia commons
How could our capacity for displacement give rise to this idea? As infants, we quickly learn that people can disappear and then reappear, sometimes minutes, hours, or even days later. From this, we realize that people continue to exist even while they have disappeared. This soon becomes an essential ingredient of our social intelligence, allowing us to imagine, for example, what others would feel or think if they were here. It's a relatively simple step to apply the same practice of displacement to the thoughts and feelings of a dead person. Given the central role of social intelligence in human cognition, it may be easier for us to think of someone still existing but not being physically present than to conceive of that person ceasing to exist altogether. And the tendency for the deceased to reappear to us in dreams adds another important node to this particular pattern of meaning.20 To explore this, a group of researchers presented kindergarten-age children with a puppet show in which an anthropomorphized mouse was killed and eaten by an alligator.
Responders, in fact, frequently reject offers below thirty dollars, and the most popular amount offered by proposers is fifty.20 It seems we humans have evolved a powerful sense of fairness. So powerful, in fact, that we would rather walk away with nothing than permit someone else to take unfair advantage of us. Researchers call this “altruistic punishment.” These results, and others like them, suggest that, over thousands of generations, our social intelligence was molded by cooperative group dynamics to evolve an innate sense of fairness and a drive to punish those who flagrantly break the rules, even at our own expense. This intrinsic sense of fairness is, in the view of some researchers, the extra ingredient that led to the evolutionary success of our species and created the cognitive foundation for values in our modern world such as freedom, equality, and representative government.21 It is, however, abundantly clear from any casual perusal of the daily news, not to mention the calamities of history, that cooperation is not the only force driving human affairs.
A captive bonobo named Kanzi, famous for his advanced linguistic skills, was apprenticed for three years in the art of making a simple Oldowan stone tool but was unable to do so.25 These tools give archaeologists a good idea of how our ancestors might have procured their food. They would now have been able to dig up termite colonies or scavenge big game carcasses in the savannah, cutting through bones into the nutritious marrow. The extra calories available to them would have fueled the development of their larger brains, which demanded more metabolic energy. Their larger brains, in turn, gave them the social intelligence to thrive in their newly complex societies, creating a positive feedback cycle, leading to the evolution of even more powerful brains capable of developing more complex tools.26 It was, at first, a tediously slow feedback effect. For a million years, hominids got by just fine on their Oldowan technology, but then a breakthrough occurred. A new species of hominid, Homo erectus, began producing far more elaborate tools, with sharp points and bilateral symmetry, known as the Acheulean industry.
The Geeks Shall Inherit the Earth: Popularity, Quirk Theory, and Why Outsiders Thrive After High School by Alexandra Robbins
airport security, Albert Einstein, Columbine, game design, hive mind, out of africa, selective serotonin reuptake inhibitor (SSRI), Skype, Slavoj Žižek, social intelligence, Steve Jobs, Steve Wozniak, The Wisdom of Crowds, trickle-down economics
But when researchers began measuring aggression alongside perceived popularity, they found an undeniably strong link. Recent studies conclude that aggressive behaviors are now often associated with high social status. Psychologists no longer view aggression as a last-resort tactic of social misfits. Now they see aggression as a means toward social success. (This does not, however, mean it is admired. As author Daniel Goleman wrote in Social Intelligence, “being manipulative—valuing only what works for one person at the expense of the other—should not be seen as socially intelligent.”) Some researchers describe a “popularity cycle”: Initially, a girl rises through the ranks to popularity. She might stay popular for a while, but at some point, she could be perceived as too popular. Maybe she’s getting too many perks, drawing too much attention from too many boys, or distancing herself too far from old friends.
.; Aikins, Julie Wargo; and Cillessen, Antonius H. N. “Moderators of the Association Between Relational Aggression and Perceived Popularity,” Aggressive Behavior, Vol. 34, 2008. See also Kiefer. See also Horn, Stacey S. “Mean Girls or Cultural Stereotypes: Essay Review,” which discusses the debate over whether social aggression is fundamentally negative. “should not be seen as socially intelligent”: See Goleman, Daniel. Social Intelligence, New York: Bantam, 2006. “popularity cycle”: See Eder, Donna. “The Cycle of Popularity: interpersonal relations among female adolescents,” Sociology of Education, Vol. 58, Issue 3, July 1985. distancing herself too far from old friends: See, for example, Adler, Patricia A. and Adler, Peter. “Dynamics of Inclusion and Exclusion in Preadolescent Cliques,” Social Psychology Quarterly, Vol. 58, No. 3, September 1995.
“the ones you point out”: Interview. Blue: Blue and I had enough discussions about this topic that I believed that he was not realistically any danger to himself or others. A surprising number answered yes: Interviews. “The needs of students”: Interview. “robust” and “remarkable”: See Puckett. See also Rose and Swenson. See also LaFontana. See also Andreou, Eleni. “Social Preference, Perceived Popularity and Social Intelligence: Relations to Overt and Relational Aggression,” School Psychology International, Vol. 27, 2006, which states, “Relational aggression may predict increased perceived popularity.” the foundation for eventual racism: See, for example, Adler and Adler, 1995. his family moved there from Plattsburgh: See, for example, Belluck, Pam and Wilgoren, Jodi. “Shattered Lives—A special report,” The New York Times, June 29, 1999.
The Great Reset: How the Post-Crash Economy Will Change the Way We Live and Work by Richard Florida
banking crisis, big-box store, blue-collar work, business cycle, car-free, carbon footprint, collapse of Lehman Brothers, congestion charging, creative destruction, deskilling, edge city, Edward Glaeser, falling living standards, financial innovation, Ford paid five dollars a day, high net worth, Home mortgage interest deduction, housing crisis, if you build it, they will come, income inequality, indoor plumbing, interchangeable parts, invention of the telephone, Jane Jacobs, Joseph Schumpeter, knowledge economy, low skilled workers, manufacturing employment, McMansion, Menlo Park, Nate Silver, New Economic Geography, new economy, New Urbanism, oil shock, Own Your Own Home, pattern recognition, peak oil, Ponzi scheme, post-industrial society, postindustrial economy, reserve currency, Richard Florida, Robert Shiller, Robert Shiller, secular stagnation, Silicon Valley, Silicon Valley startup, social intelligence, sovereign wealth fund, starchitect, the built environment, The Wealth of Nations by Adam Smith, Thomas L Friedman, total factor productivity, urban decay, urban planning, urban renewal, white flight, young professional, Zipcar
But two sets of skills matter more now: analytical skills, such as pattern recognition and problem solving, and social intelligence skills, such as the situational sensitivity and persuasiveness required for team building and mobilization. Jobs that demand high analytical skills, such as medicine and bioengineering, and social intelligence skills, such as psychiatry and management, are not only increasing in numbers faster than other jobs but also pay much more. Moving from a job in the bottom quarter of analytical-skill levels to one in the top quarter—from travel agent to, say, accountant—means an average of an additional $18,700 in pay; the gap between jobs that are low and high in social intelligence skills is even greater: $25,100. The reverse is true when it comes to physical skills: moving between a job in the bottom quarter and one in the top quarter of physical demands would be accompanied by, on average, an $8,100 drop in wages.6 The challenge on the jobs front is twofold.
The Empathic Civilization: The Race to Global Consciousness in a World in Crisis by Jeremy Rifkin
agricultural Revolution, Albert Einstein, animal electricity, back-to-the-land, British Empire, carbon footprint, collaborative economy, death of newspapers, delayed gratification, distributed generation, en.wikipedia.org, energy security, feminist movement, global village, hedonic treadmill, hydrogen economy, illegal immigration, income inequality, income per capita, interchangeable parts, Intergovernmental Panel on Climate Change (IPCC), Internet Archive, invention of movable type, invention of the steam engine, invisible hand, Isaac Newton, James Watt: steam engine, Johann Wolfgang von Goethe, Mahatma Gandhi, Marshall McLuhan, means of production, megacity, meta analysis, meta-analysis, Milgram experiment, Nelson Mandela, new economy, New Urbanism, Norbert Wiener, off grid, out of africa, Peace of Westphalia, peak oil, peer-to-peer, planetary scale, scientific worldview, Simon Kuznets, Skype, smart grid, smart meter, social intelligence, supply-chain management, surplus humans, the medium is the message, the scientific method, The Wealth of Nations by Adam Smith, The Wisdom of Crowds, theory of mind, transaction costs, upwardly mobile, uranium enrichment, working poor, World Values Survey
And that means establishing close and smooth relations so that everyone can share information easily and coordinate effectively.33 Goleman et al. refer to this new empathic style of management as “affiliative” and suggest that it “represents the collaborative competence in action.”34 The Columbia University Business School in New York City is one of a number of business schools that has introduced social intelligence pedagogy directly into its MBA curriculum. Its Program on Social Intelligence (PSI) “is organized around the psychological capabilities involved in collaborating with, motivating, and leading others” and draws together faculty from the psychology department and the business school to provide experiential opportunities, both in the classroom and in the community, to develop empathic skills.35 While classical economic theory states that individuals rationalize the sale of their labor power to maximize their income and profit, it turns out that most employees put a higher value on a caring boss, adding credence to the new empathic style of management.
The idea behind this global software business is to encourage thousands of people to empathize with the plight of others who are experiencing glitches with their software programming and codes and freely give time and expertise to help solve their problems. The notion of economic altruism no longer seems like an oxymoron. Adam Smith would, no doubt, be incredulous. Nonetheless, Linux works and has become a competitor with Microsoft on the world stage. The new insights into human beings’ empathic nature has even caught the attention of human resources management who are beginning to put as much emphasis on social intelligence as professional skills. The ability of employees to empathize across traditional ethnic, racial, cultural, and gender boundaries is increasingly regarded as essential to corporate performance, both within the workplace and in external market relations. Learning how to work together in a thoughtful and compassionate manner is becoming standard operating procedure in a complex, interdependent world.
While one’s sensations and feelings make possible the initial connection with the other, they are quickly filtered by way of past memories and organized by the various powers of reason at our disposal to establish an appropriate emotional, cognitive, and behavioral response. The entire process is what makes up empathetic consciousness. As mentioned in Chapter 1, empathy is both an affective and cognitive experience. Reason, then, is the process by which we order the world of feelings in order to create what psychologists call pro-social behavior and sociologists call social intelligence. Empathy is the substance of the process. Reason becomes increasingly sophisticated as social constructs become more complex, human differentiation more pronounced, and human exchange more diverse. Greater exposure to others increases the volume of feelings that need to be organized. Reason becomes more adept at abstracting and managing the flood of embodied feelings. We get closer to a cosmopolitan mind.
The Charisma Myth: How Anyone Can Master the Art and Science of Personal Magnetism by Olivia Fox Cabane
airport security, cognitive dissonance, Elon Musk, en.wikipedia.org, hedonic treadmill, Lao Tzu, Nelson Mandela, Parkinson's law, Peter Thiel, placebo effect, Ralph Waldo Emerson, randomized controlled trial, risk tolerance, social intelligence, Steve Jobs
In controlled experimental settings, leaders’ positive emotional contagion was shown to improve not only their followers’ moods, performance, and effectiveness but also the followers’ perception of the leaders’ effectiveness.3 Emotional contagion can of course have a corresponding negative effect, and it’s worth increasing your awareness of your own internal states, as well as your skill in handling your emotions, in order to manage the consequences of this propagation. Chapter 12 will help you do this. The potency of your emotional contagion is one good measure of your level of charisma. When researching Social Intelligence, author Daniel Goleman analyzed a video of Herb Kelleher, the charismatic cofounder of Southwest Airlines, strolling through the corridors of the airline’s hub. Goleman said, “We could practically see him activate the oscillators in each person he encountered.” Conscious Mirroring Have you ever noticed that people who have been married for many years often end up looking like each other?
Harvard Business Review (January 2004). 2. Ronald E. Riggio, The Charisma Quotient: What It Is, How to Get It, How to Use It (New York: Dodd Mead, 1988). 3. J. E. Bono and R. Ilies, “Charisma, Positive Emotions and Mood Contagion,” The Leadership Quarterly 17, no. 4 (2006): 317–34. 4. Ker Than, “Why Some Old Lovers Look Alike,” LiveScience, February 14, 2006. 5. D. Goleman and R. Boyatzi, “Social Intelligence and the Biology of Leadership,” Harvard Business Review (September 2008). 6. N. Gueguen, C. Jacob, and A. Martin, “Mimicry in Social Interaction: Its Effect on Human Judgment and Behavior,” European Journal of Social Sciences 8, no. 2 (2009). 7. Heini Hediger, The Psychology and Behaviour of Animals in Zoos and Circuses (New York: Dover Publications, 1955). 8. Allan and Barbara Pease, The Definitive Book of Body Language (New York: Bantam, 2006). 9.
., 101, 112 Kipling, Rudyard, 118 Kosslyn, Stephen, 68 Krauss, Stephen, 70 Langer, Ellen, 25 language, 20, 136, 144, 186 Lao Tzu, 24 “lasts,” 177 leadership, 2, 3 compassion needed for, 83 Leahy, Robert, 32 lectures, 139–40 left frontal lobes, 88 life, enjoying, 17–18 limbic resonance, 146 Lincoln, Abraham, 74, 136 listening, 14, 17, 26, 100, 128–31, 142, 184, 231, 232, 241 Little Prince, The (Saint-Exupéry), 185 logic, 144, 163 lovable book, 90 love at first sight, 153 Lowndes, Leil, 185 Lurie, Bob, 40 Madonna, 98 Mao Zedong, 112, 220 marketing, 169 Martinez, Angel, 83 meditation, 12, 15, 16, 18, 45 meetings, 72–73, 96–97 memory cards, 189–90 mental discomfort, 31–41, 43, 44, 65 metaphors, 189, 190, 233 Method acting, 12, 68 Metta, 87–90, 239–40 Michelangelo, 27 microexpressions, 22, 182 mindfulness discipline, 15, 45 Mindful Path to Self-Compassion, The (Germer), 87 mindset shift, 15–16, 224 mind wandering, 16 mirror, 155 mirror neurons, 145 Miss Piggy, 92–93 MIT, 73 MIT Media Lab, 20, 126, 140 moms, 3 Monitor Group, 40 Monroe, Marilyn, 1, 4 Multiple Sclerosis Association, 203 Muppet Show, The, 92–93 music, 70–71, 95, 96, 174 Musk, Elon, 98–99 Mussolini, Benito, 104, 220 Napoleon I, Emperor of the French, 74, 201, 204 narcissism, 85 neediness, 75 Neff, Kristin, 86 negative associations, 131–34, 142 negativity, 37, 38–39, 40, 42, 46 neutralizing, 47–51, 58, 59, 65, 66, 202, 236 suppressing, 52 negativity bias, 48–49 negotiations, 100, 130 NeuroLeadership Institute, 38 neuronal connections, 68 neuroscience, 11 Newman, Paul, 68 New Scholars, 147–49 New York Times, 188 Ney, Marshal, 204 Nicklaus, Jack, 67 nocebo effect, 25–26 nodding, 10, 106, 149, 160, 161, 162, 164 numbers, 189–90 Obama, Barack, 109 Ochsner, Kevin, 22n OfficeMax, 184 Onassis, Aristotle, 153–54 open-ended questions, 123 Oracle, 119 oscillators, 146 outgoing personalities, 10 owning the stage, 193–94 oxytocin, 73, 170, 198 Paramount Equity, 109, 215 Parkinson’s Law, 55 patience, 100, 103 pauses, 10, 106, 130–31, 141, 234 pausing, 129 in presentations, 196–97 Pavlov, Ivan, 132 PayPal, 98 Penn, Sean, 68 performance, 53, 58 performance review, 174 Perot, Ross, 216 Persia, 132 personality, 10, 107–10, 113 personal magnetism, 6 personal space, 150–53 Peter Pan, 71 phenylethylamine (PEA), 153 phones, 183–85, 186 physical discomfort, 28–31, 42, 43, 59, 65, 66 physicians, 3 pictures, 136–39, 142 pitch, 140 placebo effect, 25, 26, 36, 55, 74 Play-Doh, 173–74 posture, 21, 91, 97, 147, 149, 150, 156–63, 164 authority charisma and, 106 in presentations, 198 Powell, Colin, 5, 104, 112 power, 5, 6, 13, 18–20, 21, 26, 27, 31, 67, 94, 100, 130, 139, 142, 162, 191, 224, 229–30, 231, 234 praise, 207–11 presence, 5–6, 12, 13–18, 26, 27, 31, 63, 129, 142, 154, 224, 229–30, 235 anxiety and, 32 appearance of, 191 body language and, 21 focus charisma and, 100, 231 techniques for, 15 presentations, 7, 72, 187–200, 215, 232, 233–34 charismatic message in, 188–90 colors at, 191 mid-course corrections, 197–99 Q&As at, 190 rehearsals of, 192–93 supporting points in, 189 warmth in, 194–95 Rao, Srikumar, 53n rationalization, 170–71, 186 reality: mind’s view of, 47–49, 50 rewriting, 51, 52–58, 59–60, 65, 66, 202, 236–37 reassurance, 161, 162, 164 resentment, 57, 58, 75, 130, 207–11 resilience, 64–65 responsibility, 210 responsibility transfer, 34–37, 42, 45, 60, 100, 202, 235–36 Rice, Condoleezza, 5 Riggio, Ronald, 143–44 Rock, David, 38 Rocky III, 71 role-playing, 96 romance, 2, 174 Rome, 120 Roosevelt, Franklin Delano, 136, 194 Saint-Exupéry, Antoine de, 185 sarcasm, 56 satisfaction, 58, 237 Schiro, Tom, 83 Schnabel, Arthur, 130 seating choices, 152–53, 242 Seinfeld, Jerry, 192, 193 self-acceptance, 85 self-compassion, 84–90, 103, 181, 239 self-confidence, 84, 85–86, 94–95 self-consciousness, 199 self-criticism, 38–39, 40, 42, 50, 86–87, 90 self-doubt, 39–41, 42, 43 self-esteem, 84–85, 94–95 self-evaluation, 85 self-warmth, 84 separation distress, 154 shame, 45–46, 50, 90 Sicilienne, The, 196 Sinatra, Frank, 198, 216 situations, 107, 110–13 smiling, 24, 141–42, 184 social comparison, 85 Social Intelligence, 146 social situations, 3 social skills, 23 social smile, 22 soft focus, 155 sounds, 15, 235 Southwest Airlines, 146 space, 158–59 speaking, 131–39, 142, 241 see also presentations Stalin, Joseph, 104, 220 Stanford Business School, 40 Stanford University, 157, 159 statistics, 189–90 status, 134, 160, 232 authority charisma and, 104–7, 231 stories, 189, 190, 233 Streep, Meryl, 68 stress, 2, 38, 41, 52, 53, 154–55 visualization and, 71 stress hormones, 38, 52, 170 stress system, 170, 174, 202 students, 3 suicide, 73 sympathy, 82 Tan, Chade-Meng, 45–46 teachers, 116 technical skills, 23 tempo, 140, 141, 142 tension, 59–60, 61 Teresa, Mother, 88, 112 Tesla Motors, 98–99 Texas, University of, 116 Thatcher, Margaret, 112 Thich Nhat Hanh, 44 threat response, 38 tone, 140 apologies and, 181 criticism and, 179 Tonight Show, The, 192 Top Gun, 71 traffic, 56 true smile, 24 trust, 2, 152 uncertainty, 32–37, 42, 101, 167 Uslan, Michael, 40 Vangelis, 71 vision, 203–5, 231, 234 visionary, 210 visionary charisma, 98, 101–2, 103, 107, 108, 109, 110, 112, 136, 167, 231 visualization, 67–74, 96, 231, 238 body language and, 68, 69, 73, 97 of funeral, 78–79, 83 of goodwill, 81 of historical counselors, 74 of invisible angel wings, 81, 158, 171, 174, 194 kindness charisma and, 103 before meetings, 72–73 of Metta, 88–89 for phone calls and e-mails, 183 practice for, 69 before presentations, 72 voice, 21, 139–42, 182 volume, 140–41, 193–94 vulnerability, 216–18, 221, 243 Walmart, 198 Walton, Sam, 198, 216 warming up, 93–97, 103, 172 warmth, 5, 6, 13, 18–20, 26, 27, 67, 74, 81, 92, 94, 97, 101, 106, 109, 123, 130, 139, 142, 150, 155, 156, 158, 161, 162, 163, 164, 172, 176, 182, 224, 229–30, 231, 232 anxiety and, 32 body language and, 21, 234 criticism and, 179 focus charisma and, 100 handshakes and, 121 kindness charisma and, 102–4, 231 on phone, 185 in presentations, 191, 194–95, 197 self-, 84 vocal, 141–42 Weiss, Alan, 144 white knights, 120 Williams, Redford, 170 willpower, 94 Winfrey, Oprah, 75, 108, 109, 110–11 Wise Brain Bulletin, 73 Wiseman Institute, 80 worst-case scenario, 50, 51 writing, 54, 56, 57
Data for the Public Good by Alex Howard
23andMe, Atul Gawande, Cass Sunstein, cloud computing, crowdsourcing, Hernando de Soto, Internet of things, Kickstarter, lifelogging, Network effects, openstreetmap, Silicon Valley, slashdot, social intelligence, social software, social web, web application
The challenge is for the men and women entrusted with coordinating response to identify signals in the noise. First responders and crisis managers are using a growing suite of tools for gathering information and sharing crucial messages internally and with the public. Structured social data and geospatial mapping suggest one direction where these tools are evolving in the field. A web application from ESRI deployed during historic floods in Australia demonstrated how crowdsourced social intelligence provided by Ushahidi can enable emergency social data to be integrated into crisis response in a meaningful way. The Australian flooding web app includes the ability to toggle layers from OpenStreetMap, satellite imagery, and topography, and then filter by time or report type. By adding structured social data, the web app provides geospatial information system (GIS) operators with valuable situational awareness that goes beyond standard reporting, including the locations of property damage, roads affected, hazards, evacuations and power outages.
Heart of the Machine: Our Future in a World of Artificial Emotional Intelligence by Richard Yonck
3D printing, AI winter, artificial general intelligence, Asperger Syndrome, augmented reality, Berlin Wall, brain emulation, Buckminster Fuller, call centre, cognitive bias, cognitive dissonance, computer age, computer vision, crowdsourcing, Elon Musk, en.wikipedia.org, epigenetics, friendly AI, ghettoisation, industrial robot, Internet of things, invention of writing, Jacques de Vaucanson, job automation, John von Neumann, Kevin Kelly, Law of Accelerating Returns, Loebner Prize, Menlo Park, meta analysis, meta-analysis, Metcalfe’s law, neurotypical, Oculus Rift, old age dependency ratio, pattern recognition, RAND corporation, Ray Kurzweil, Rodney Brooks, self-driving car, Skype, social intelligence, software as a service, Stephen Hawking, Steven Pinker, superintelligent machines, technological singularity, telepresence, telepresence robot, The Future of Employment, the scientific method, theory of mind, Turing test, twin studies, undersea cable, Vernor Vinge, Watson beat the top human players on Jeopardy!, Whole Earth Review, working-age population, zero day
The machine learning algorithms would then process all of the videos that were labeled for a particular expression—happiness or confusion, for instance—and then find all of the common points on the faces in all of those clips. The software then knew what that expression looked like and could continue to improve with additional examples and feedback. This work led to el Kaliouby developing her first emotional social-intelligence prosthesis, which consisted of a pair of glasses with an outward-facing webcam and user-facing LEDs. During a conversation, the device detected a listener’s expression and gave real-time feedback to the wearer as to whether the person they were speaking with was engaged, neutral, or bored using green, amber, and red LEDs respectively. By the end of her time at Cambridge, el Kaliouby had developed a system that was accurate 88 percent of the time and that could recognize far more expressions than just the basic emotions in real-world settings.
The problem becomes even more critical if we’re talking about a crisis call center using automated suicide prevention software, where the wrong response could result in tragic consequences. Then there’s the matter of people using emotional prosthetics to deal with shortcomings in users’ emotional intelligence. We’ve already heard about Rana el Kaliouby’s early efforts with MindReader, the social intelligence prosthesis for autistic users. This is likely just the beginning of what will be a broad array of emotional assistance devices. Using augmented reality and emotional pattern recognition, any number of emotion reading tools could be possible. Just imagine a wearable prosthetic for people with brain damage similar to Elliot’s at the beginning of chapter 3. What a difference a device like that could make to someone’s life!
Some of the work being done with affective technologies may end up contributing to those solutions, as well as to improvements in more mainstream education. As described earlier, much of the initial research and development in affective computing has led to devices that could eventually aid people on the autism spectrum. Skin conductivity devices, such as iCalm, the Q sensor, and Embrace, and emotional social-intelligence prosthetics like MindReader only hint at the potential. Consider the strides that have been made in interface development as researchers design new ways to help those with different sensory challenges and handicaps. Ray Kurzweil developed a portable reader for the blind. Various methods have sought to use computers to make up for lost sight, hearing, or mobility. There are even brain-computer interfaces (BCIs) that seek to give paraplegics and those with locked-in syndrome the ability to communicate and maneuver devices such as wheelchairs using only their thoughts.
RDF Database Systems: Triples Storage and SPARQL Query Processing by Olivier Cure, Guillaume Blin
Amazon Web Services, bioinformatics, business intelligence, cloud computing, database schema, fault tolerance, full text search, information retrieval, Internet Archive, Internet of things, linked data, NP-complete, peer-to-peer, performance metric, random walk, recommendation engine, RFID, semantic web, Silicon Valley, social intelligence, software as a service, SPARQL, web application
See Succinct data structures (SDSs) SELECT, 12 Select-project-join (SPJ), 134 Semantic Index approach, 98, 99 Semantic Web, 4, 5, 43 applications, building, 78 stack, 41 Sesame, 143 SHARD. See Scalable high-performance, robust, and distributed (SHARD) Shared-disk architecture, 21 Shared-memory architecture, 21 Shared-nothing architecture, 21 SHER. See Scalable highly expressive reasoner (SHER) SIB. See Social Intelligence BenchMark (SIB) Sideways information passing (SIP), 162 SimpleDB, 34 Simple knowledge organization system (SKOS), 6, 70 SIP. See Sideways information passing (SIP) SKOS. See Simple knowledge organization system (SKOS) Social Intelligence BenchMark (SIB), 78 Solid-state drives (SSDs), 9 Spanner system, 39 SPARQL, 53 endpoint, 170 extensions, 223 protocol and RDF Query, 52 queries, 56, 124 query language, 74, 143 variable graph, 153 SPARQL 1.1, 58 graph management, 59 graph update, 58 SPARQL-to-SQL query rewriting solution, 136 transformation, 107 SPJ.
The SPARQL Performance Benchmark (SP2Bench; http://dbis.informatik.uni-freiburg.de/index.php?project=SP2B) includes a benchmark built around DBLP computer science bibliography scenario. The data is generated in N-triples format. The 12 provided queries include filtering requirements (inequality test) and an ASK query. The data generated includes blank nodes, containers, and long URIs. No use of inference is necessary. The Social Intelligence BenchMark (SIB; http://www.w3.org/wiki/Social_ Network_Intelligence_BenchMark) includes a benchmark built around popular social networks.The data generator is generating a huge volume of data (all data associated with one person, having on average 30 friends and a few hundred pictures and posts, is evaluated at 1 MB). The provided 20 SELECT queries include filtering requirements (range of value, regex, and equality test) and the optional use of transitive properties, negation, aggregation, and subqueries.
Future Shock by Alvin Toffler
Albert Einstein, Brownian motion, Buckminster Fuller, Charles Lindbergh, cognitive dissonance, Colonization of Mars, corporate governance, East Village, global village, Haight Ashbury, information retrieval, invention of agriculture, invention of movable type, invention of writing, longitudinal study, Marshall McLuhan, mass immigration, Menlo Park, New Urbanism, Norman Mailer, post-industrial society, RAND corporation, social intelligence, the market place, Thomas Kuhn: the structure of scientific revolutions, urban renewal, Whole Earth Catalog, zero-sum game
Gross of Wayne State University, Eleanor Sheldon and Wilbert Moore of the Russell Sage Foundation, Daniel Bell and Raymond Bauer of Harvard. We are witnessing, says Gross, a "widespread rebellion against what has been called the 'economic philistinism' of the United States government's present statistical establishment." This revolt has attracted vigorous support from a small group of politicians and government officials who recognize our desperate need for a post-technocratic social intelligence system. These include Daniel P. Moynihan, a key White House adviser; Senators Walter Mondale of Minnesota and Fred Harris of Oklahoma; and several former Cabinet officers. In the near future, we can expect the same revolt to break out in other world capitals as well, once again drawing a line between technocrats and post-technocrats. The danger of future shock, itself, however, points to the need for new social measures not yet even mentioned in the fast-burgeoning literature on social indicators.
A sensitive system of indicators geared to measuring the achievement of social and cultural goals, and integrated with economic indicators, is part of the technical equipment that any society needs before it can successfully reach the next stage of eco-technological development. It is an absolute precondition for post-technocratic planning and change management. This humanization of planning, moreover, must be reflected in our political structures as well. To connect the super-industrial social intelligence system with the decisional centers of society, we must institutionalize a concern for the quality of life. Thus Bertram Gross and others in the social indicators movement have proposed the creation of a Council of Social Advisers to the President. Such a Council, as they see it, would be modeled after the already existing Council of Economic Advisers and would perform parallel functions in the social field.
The designation of agencies to watch over the indicators of change in the quality of life would carry us a long way toward that humanization of the planner which is the essential first stage of the strategy of social futurism. * Proponents differ as to whether the Council of Social Advisers ought to be organizationally independent or become a part of a larger Council of Economic and Social Advisers. All sides agree, however, on the need for integrating economic and social intelligence. TIME HORIZONS Technocrats suffer from myopia. Their instinct is to think about immediate returns, immediate consequences. They are premature members of the now generation. If a region needs electricity, they reach for a power plant. The fact that such a plant might sharply alter labor patterns, that within a decade it might throw men out of work, force large-scale retraining of workers, and swell the social welfare costs of a nearby city—such considerations are too remote in time to concern them.
Everything Bad Is Good for You: How Popular Culture Is Making Us Smarter by Steven Johnson
Columbine, complexity theory, corporate governance, delayed gratification, edge city, Flynn Effect, game design, Marshall McLuhan, pattern recognition, profit motive, race to the bottom, sexual politics, social intelligence, Steve Jobs, the market place
In the gameworld, you're dealing with real people through the mediating channels of 3 D graphics and text chat; real ity shows drop flesh-and blood people into the same shared space for months at a E V E R Y T H I N G B A D I S G O O D F O R Yo u 95 time, often limiting their contact with the outside world. Reality program participants are forced to engage face-to face with their comrades, and that engagement invariably taps their social intelligence in ways that video games can only dream of. And that social chess becomes part of the audience's experience as well . This, of course, was the ap peal of that pioneering reality show, MTV's The Real World, which didn't need contests and fabulous prizes to lure its viewers; it j ust needed a group of people thrust together in a new space and forced to interact with one another. The role of audience participation is one of those prop erties that often ends up neglected when the critics assess these shows.
(Reality programming embraces and extends the logic of game shows, j ust as shows like The Sopranos and Six Feet Under expand on the template originally created by the soap opera .) But the rules and the " right answers " have increased in complexity since Herbert Stempel took his famous dive . " Playing" a reality show requires you to both adapt to an ever-cha nging rulebook, and scheme your way through a minefield of personal relationships. To succeed in a show like The Apprentice or Survivor, you need social intelligence, not j ust a mastery of trivia. When we watch these shows, the part of our brain that monitors the emotional lives of the people around us-the part that tracks subtle shifts in in tonation and gesture and facial expression-scrutinizes the action on the screen , looking for clues. We trust certain characters impl icitly, and vote others off the island in a hea rtbeat. Traditional narrative shows also tri gger emo tional connections to the characters, but those connections don't have the same participatory effect, because traditional narratives aren't explicitly about strategy.
Disarming the Narcissist: Surviving and Thriving With the Self-Absorbed by Wendy T. Behary
Empathy, this felt sense of the other, is the ability and the willingness to imagine walking in the other person’s shoes. It can be differentiated from sympathy in that it is not simply feeling sorrow for another’s pain, it is the art of tuning in to it, allowing it to resonate within your own body and mind. It is one of the most powerfully connective qualities of a healthy relationship, and its absence can be devastating. Daniel Goleman, in his book Social Intelligence (2006), suggests that someone who doesn’t empathize with others can treat them as objects rather than as people. Now You See Him, Now You Don’t The narcissist’s lack of empathy can manifest in different ways. For example, if you are finally able to wedge a word into a conversation with a narcissist, asking him to tune in to your world, he’s likely to suddenly become the amazing Houdini, disappearing before your very eyes.
Children of the Self-Absorbed: A Grown-Up’s Guide to Getting Over Narcissistic Parents. Oakland, CA: New Harbinger Publications. Giesen-Bloo, J., R. van Dyck, P. Spinhoven, W. van Tilburg, C. Dirksen, T. van Asselt, I. Kremers, M. Nadort, and A. Arntz. 2006. “Outpatient Psychotherapy for Borderline Personality Disorder: Randomized Trial of Schema-Focused Therapy vs. Transference-Focused Therapy.” Archives of General Psychiatry 63(6):649–658. Goleman, D. 2006. Social Intelligence: The New Science of Human Relationships. New York: Bantam. Gottman, J., and N. Silver. 2004. The Seven Principles for Making Marriage Work. New York: Orion. Hotchkiss, S. 2003. Why Is It Always About You? The Seven Deadly Sins of Narcissism. New York: Free Press. Iacoboni, M. 2009. Mirroring People: The New Science of How We Connect with Others. New York: Farrar, Straus, and Giroux. O’Donohue, J. 2000.
In Our Own Image: Savior or Destroyer? The History and Future of Artificial Intelligence by George Zarkadakis
3D printing, Ada Lovelace, agricultural Revolution, Airbnb, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, animal electricity, anthropic principle, Asperger Syndrome, autonomous vehicles, barriers to entry, battle of ideas, Berlin Wall, bioinformatics, British Empire, business process, carbon-based life, cellular automata, Claude Shannon: information theory, combinatorial explosion, complexity theory, continuous integration, Conway's Game of Life, cosmological principle, dark matter, dematerialisation, double helix, Douglas Hofstadter, Edward Snowden, epigenetics, Flash crash, Google Glasses, Gödel, Escher, Bach, income inequality, index card, industrial robot, Internet of things, invention of agriculture, invention of the steam engine, invisible hand, Isaac Newton, Jacquard loom, Jacques de Vaucanson, James Watt: steam engine, job automation, John von Neumann, Joseph-Marie Jacquard, Kickstarter, liberal capitalism, lifelogging, millennium bug, Moravec's paradox, natural language processing, Norbert Wiener, off grid, On the Economy of Machinery and Manufactures, packet switching, pattern recognition, Paul Erdős, post-industrial society, prediction markets, Ray Kurzweil, Rodney Brooks, Second Machine Age, self-driving car, Silicon Valley, social intelligence, speech recognition, stem cell, Stephen Hawking, Steven Pinker, strong AI, technological singularity, The Coming Technological Singularity, The Future of Employment, the scientific method, theory of mind, Turing complete, Turing machine, Turing test, Tyler Cowen: Great Stagnation, Vernor Vinge, Von Neumann architecture, Watson beat the top human players on Jeopardy!, Y2K
He argued that when individuals live within a group and enter into a diverse set of cooperative, competitive and mutualistic relationships, individuals with the ability to predict the behaviour of others will achieve the greatest reproductive success. He coined the term ‘social intelligence’ to describe the mental toolbox that is essential to maintain social cohesion. Therefore, there is selective pressure to have the ability to ‘read’ other people’s minds. Early humans were dependent on retaining harmonious social relationships within their group for their survival. This involved much manipulation of other people’s emotions, fears and wants. Today, six million years after we parted ways with the chimpanzees, the instinctive need to belong to a group dominates our personal and social life. Social rejection hurts: exile is a terrible punishment; separation from family and friends a personal tragedy. Our high-level consciousness, or general intelligence, seems to have evolved as part of social intelligence. But what did it mean to be a human before the advent of high-level consciousness?
A. 61–2, 68 Hofstadter, Douglas 186–8 Hohlenstein Stadel lion-man statuette 3–5, 19–20 holistic approach to knowledge 174–5 holistic scientific methods 41–2 Holocene period 10 Holy Scripture, authority of 113–14 homeostasis 173 Homo erectus 6–7, 8, 10 Homo habilis 6, 12 Homo heidelbergensis 7 Homo sapiens archaic species 7, 8, 10 emergence of modern humans 8 Homo neanderthalensis (Neanderthals) 4, 7–8, 9–10 Homo sapiens sapiens 9–10 human ancestors aesthetic practices 9 archaic Homo sapiens 7, 8, 10 arrival in Europe 3–5 australopithecines 5, 6, 22 changes in the Upper Palaeolithic Age 9–10, 11 common ancestor with chimpanzees 5 emergence of art in Europe 3–5 emergence of modern humans 8 exodus from Africa 3–4, 6–7, 8–9 Homo erectus 6–7, 8, 10 Homo habilis 6, 12 Homo heidelbergensis 7 Homo sapiens 7, 8, 10 Homo sapiens sapiens 9–10 in Africa 5–7 Neanderthals (Homo neanderthalensis) 4, 7–8, 9–10 Human Brain Project (HBP) xiv–xvi, 164–5, 287 see also brain (human) human culture, approaches to understanding 74–9 human replicas, disturbing feelings caused by 66–73 humanity becoming like machines (cyborgs) 79–85 future of 304–17 Hume, David 139–40 humors theory of life 31–4 humour, and theory of mind 54 Humphrey, Nicholas 11 hunter-gatherer view of the natural world 20–2 hydraulic and pneumatic automata 32–6 IBM (International Business Machines) 230, 263, 264 Ice Age Europe 4, 10, 21–2 iconoclasm 67 idealism versus materialism 92–4 identity theory 144–5 imagined world of the spirits 22–3, 25, 27 inanimate objects, projection of theory of mind 15–18 Incompleteness Theorem (Gödel) 180, 186, 206–9, 211–16 inductive logic 196, 197 information disembodiment of 146–52 significance of context 151–2 the mind as 123–5 information age 232–4 information theory 147–52 Ingold, Tim 20 intelligence, definitions of 48–9, 52 intelligent machines as objects of love 48–59 Internet brain metaphor 43 collection and manipulation of users’ data 250–3 origins of 238 potential for sentience 214–15 Internet of things 251–3 intuition 200, 211 Iron Man (film) 82 Ishiguro, Hiroshi 72 Islam 102 Jacquard loom 225 James, William 162 Johnson, Samuel 140 Kasparov, Garry 263 Kauffman, Stuart 295 Kempelen, Wolfgang von 37 Kline, Nathan 79 Koch, Christof 167–8 Krauss, Lawrence 244–5 Krugman, Paul 269 Kubrick, Stanley 56, 257 Kuhn, Thomas 29, 75 Kurzweil, Ray 126, 270–1 Lang, Fritz 50 language and genesis of the modern mind 13–15 and human relationship with objects 15–18 evolution of 13–15 naming of objects 16–17 LeCun, Yann 255 Leibniz, Gottfried Wilhelm 116–17, 218–20 Lettvin, Jerry 293 liberty, end of 313–17 life algorithms of 292–6 origins of 181–3 Life in the Bush of Ghosts (Tutuola) 19 linguistics, descriptions of reality 75 lion-man statuette of Stadel cave 3–5, 19–20 Llull, Ramon (Doctor Illuminatus) 218 Locke, John 139 locked-in syndrome 307 logic x–xi, 195–202 logical substitution method 180, 183, 186 Lokapannatti (early Buddhist story) 34 London forces 107 love conscious artefacts as objects of 48–59 human need for 55–6 human relationships with androids 53–9 Lovelace, Ada 62, 226–7, 228 Luddites 268 Machine Intelligence Research Institute 58–9 machine metaphor for life 36–8 Magdalenian period 21 magnetoencephalography (MEG) 159–60, 161 Maillardet, Henri 218 Marconi, Guglielmo 239 Maria (robot in Metropolis) 50, 51 Marlowe, Christopher 63 Mars colonisation 291 Marx, Groucho 205 materialism versus idealism 92–4 mathematical dematerialisation view 92 mathematical foundations of the universe 103–6 mathematical reflexivity 186–7 mathematics 31 formal logical systems 200–11 views on the nature of 136 Maturana, Humberto 294 McCarthy, John 256, 307 McCorduck, Pamela 45, 67 McCulloch, Warren S. 36, 175, 176–8, 256, 293 Mead, Margaret 175 mechanical metaphor for life 36–8 mechanical Turk 37 medicine, development of 31–2 meditation 157 memristors 286–7 Menabrea, Luigi 226, 227 Mesmer, Franz Anton 40 mesmerism 40 Mesopotamian civilisations 30 metacognition 184 metamathematics 202, 205, 207 metaphors confusing with the actual 44–5 for life and the mind 28–47 in general-purpose language 75 misunderstanding caused by 308–13 Metropolis (1927 film) 50, 51 Middle Palaeolithic 6 Miller, George 154, 155 Milton, John 1 mind altered states 110, 111 as pure information 123–5 aspects of 85–7 debate over the nature of 91–4 disembodiment of 42 empirical approach 143–6 quantum hypothesis 106–9 scientific theory of 152–3 search for a definition 189–91 self-awareness 86–7 separate from the body 110–15 view of Aristotole 137–8 mind-body problem 32, 114–19, 129–31 Minsky, Marvin 178, 256 modern mind big bang of 10, 12–15 birth of 10–15 impacts of the evolution of language 13–15 monads 117, 119 monism versus dualism 92–3 Moore’s Law 244–5, 263, 270–1, 287 moral decision-making 277–8 Moravec paradox 275–6 Morris, Ian 222 Morse, Samuel 42 mud metaphor for life 29–31, 45 My Life in the Bush of Ghosts (music album) 19 Nabokov, Vladimir 167 Nagel, Thomas 120, 121 Nariokotome boy 7 narratives 18–27, 75 see also metaphor Neanderthals (Homo neanderthalensis) 4, 7–8, 9–10 Negroponte, Nicholas 243–4 neopositivism 141 neural machines 282–7 neural networks theory 36 neural synapses, functioning of 117–19 neuristors 286–7 neurodegenerative diseases xiii–xiv, 163–4 Neuromancer (Gibson) 36 neuromorphic computer archtectures 286–7 neurons, McCulloch and Pitts model 177–8 neuroscience 158, 306–8 Newton, Isaac 38, 103 Nike’s Fuel Band 81 noetic machines (Darwins) 284 nootropic drugs 81 Nouvelle AI concept 288 Offray de La Mettrie, Julien 37 Ogawa, Seiji 158–9 Omo industrial complex 6 On the Origin of Species (Darwin) 289–90 ‘ontogeny recapitulates phylogeny’ concept 10 Otlet, Paul 239–40 out-of-body experiences 110–11 Ovid 49, 64 Paley, William 289 panpsychism 92, 117, 252 paradigm shifts 75 in the concept of life 29–47 Pascal, Blaise 219–20 Penrose, Roger 106–9, 117, 211–12, 214 Pert, Candace B. 170 physics, gaps in the Standard Model 105 Piketty, Thomas 267, 269 pineal gland 115–16 Pinker, Steven 13, 275 Pinocchio story 56 Pitts, Walter 36, 177–8, 256, 293 Plato 134, 143, 152, 176, 189, 305 central role of mathematics 103–6 idea of reality 78, 83 influence of 95–106 notion of philosopher-kings 98–9 separation of body and mind 112 The Republic 97–101, 309, 310 theory of forms 99–101, 104, 106 Platonism 101–2, 135–7, 139, 142, 146, 147, 182, 189, 190, 242–3, 296 Pleistocene epoch 7 Poe, Edgar Allan 79 Polidori, John William 60, 62 Popov, Alexander 239 Popper, Karl 98 Porter, Rodney 282 posthuman existence 147 postmodernism 208 post-structuralist philosophers 75–9 precautionary principle 64–5 predicate logic 198–200, 206 Principia Mathematica 205–6, 207 Prometheus 29–30, 63–4 psychoanalysis 50 psychons 118, 119 Pygmalion narrative 49–52 qualia of consciousness 120–3, 157 Quantified Self movement 81–2 quantum hypothesis for consciousness 106–9 quantum tunnelling 118–19 Ramachandran, Vilayanur 70 rationalism 116 Reagan, President Ronald 237 reality, impact of acquisition of language 15–18 reductionism 41–2, 104–5, 121, 184 reflexivity 183–4, 186–9 religions condemnation of human replicas 67 seeds of 22–3, 25–6 Renaissance 34, 103, 139, 218 RepRap machines 290 res cogitans (mental substance) 38, 113–14 res extensa (corporeal substance) 38, 113–14 resurrection beliefs 126–7 RoboCop 80 robot swarm experiments 287–8 robots human attitudes towards 50–1 rebellion against humans 53, 57–9 self-replication 289–92 see also androids Rochester, Nathaniel 256 Romans 31 Rubenstein, Michael 287–8, 291 Russell, Bertrand viii, 92, 198, 204, 205–6, 207, 208, 215 Russell, Stuart 270 Sagan, Carl 133 Saygin, Ayse Pinar 69 science as a cultural product 75–9 influence of Aristotle 134–8 influence of Descartes 113–19 influence of Plato see Plato scientific method 102–5, 121 scientific paradigms 75 scientific reasoning, as unnatural to us 133–4, 137 scientific theory, definition 166, 196 Scott, Ridley 53 Searle, John, Chinese Room experiment 52, 71 Second Commandment (Bible) 67 second machine age, impact of AI 266–9 Second World War 234–6 self-awareness 16, 86–7, 157, 215–16, 273–5 self-driving vehicles 263–4 self-organisation in cybernetic systems 273–4 in living things 292 self-referencing 186–9, 215–16 see also reflexivity self-referencing paradoxes 204–6 self-replicating machines/systems 179–82, 289–92 sensorimotor skills, deficiency in AI 275–6 servers, dependence on 245–9 Shannon, Claude 147–52, 154, 176, 230–1, 256 Shaw, George Bernard Shaw 49–50 Shelley, Mary, Frankenstein 40, 60–5, 165 Shelley, Percy Bysshe 60, 62, 63–4 Shickard, Wilhem 219 Silvester II, Pope 35 Simmons, Dan 160 simulated universe concept 127–9 smart drugs 81 Snow, C. P. xv–xvi Snowden, Edward 124–5, 250–1 social intelligence 11–12 social media 250 social networks 83–4, 124–5 social origins of language 13–15 Socrates 96–7, 99–100, 111–12 speech and language, genetic link 13–15 Spielberg, Steven 56–7 spirit of life (élan vital) 40–1 split-brain patients 23–4 Stanhope, Lord 220 Star Trek 54–5, 57, 80, 82, 278 steam engine 31 Stoker, Bram 62 stone tools see tool-making stories see narratives string theory 92, 105 Strong Anthropic Principle 127–9 structuralism 74–5 subjective experience 120–3, 157–8 swarm intelligence 287–8 syllogisms 195–6 symbolic logic, limitations of 275–6 systemic scientific method 41–2 talking head, stories about 35–6, 58 Talmud 45 Talmy, Leonard 15 Talos (robotic giant of Crete) 33 Target (retail company) 250 technology, as a cultural product 75–9 Tegmark, Max 270 Teilhard de Chardin, Pierre 126, 127, 245 telecommunications development 238–43 telegraph metaphor for the brain 42–3 Terminator films 57, 66, 83 The Dice Man (1971 novel) 213 The Invincible (Stanisl´aw Lem) 288, 289 The Matrix films 57, 66, 76, 77, 78, 82 The Six Million Dollar Man (television series) 79–80, 83 The Tempest (Shakespeare) xvii The Time Machine (H.
Designing Your Life: How to Build a Well-Lived, Joyful Life by Bill Burnett, Dave Evans
David Brooks, fear of failure, financial independence, game design, Haight Ashbury, invention of the printing press, iterative process, knowledge worker, market design, science of happiness, Silicon Valley, Silicon Valley startup, Skype, social intelligence, Steve Jobs
Chapter 8 Designing Your Dream Job 1. https://test.naceweb.org/press/faq.aspx. Chapter 9 Choosing Happiness 1. Peter Salovey and John D. Mayer, “Emotional Intelligence,” Imagination, Cognition and Personality 9 (1990): 185−211. 2. Dan Goleman is the author of Emotional Intelligence (New York: Bantam, 1995) and the follow-up book Social Intelligence: The New Science of Human Relationships (New York: Bantam, 2006) from which we draw the notion of the “wisdom of the emotions.” For an informative and interesting summary of these ideas go to Dan’s Social Intelligence Talks at Google at https://www.youtube.com/watch?v=-hoo_dIOP8k. 3. For more on Dan Gilbert’s ideas on “synthesizing happiness” watch his TED Talk, “The Surprising Science of Happiness,” http://www.ted.com/talks/dan_gilbert_asks_why_are_we_happy and read Stumbling on Happiness (New York: Knopf, 2006). 4.
Survival of the Friendliest: Understanding Our Origins and Rediscovering Our Common Humanity by Brian Hare, Vanessa Woods
Cass Sunstein, cognitive bias, desegregation, Donald Trump, drone strike, income inequality, Jane Jacobs, Law of Accelerating Returns, meta analysis, meta-analysis, microbiome, Milgram experiment, Nelson Mandela, New Urbanism, nuclear winter, out of africa, phenotype, Ray Kurzweil, Richard Florida, Ronald Reagan, selective serotonin reuptake inhibitor (SSRI), self-driving car, smart cities, social intelligence, Stanford marshmallow experiment, stem cell, Steven Pinker, The Death and Life of Great American Cities, theory of mind, Tim Cook: Apple, trade route, white flight, zero-sum game
Belyaev bred the foxes to decrease their fear of people, likely allowing an evolutionarily ancient social skill they use in interactions with one another to flourish in a new context, in a relationship with humans. Unconstrained by fear, foxes could use social skills, such as cooperative communication, more flexibly. Problems that were previously confronted alone became social problems that were easily solved with cooperative partners. Cooperative communication had been enhanced, but contrary to what most hypotheses of cognitive evolution predicted, it had been an accident. This kind of social intelligence is just another side effect of fearfulness being replaced by friendliness.19 The fox work provided strong evidence that the basic skill behind the cooperative communication we observed in dogs was the product of domestication. We had also discovered that this skill we found in dogs was not simply the product of an individual dog interacting with humans for hundreds, if not thousands, of hours before they were adults.
The same toddlers who can’t put their drinks down without spilling them, or make it to the toilet in time, have a theory about how other minds work.32 These early-emerging social skills give us an edge, allowing even those of us with underdeveloped brains to use others to solve sophisticated problems. Our ability to understand others at a young age also allows us to inherit knowledge acquired over generations, giving us a unique survival advantage. BABY BALLOONS In order to mark the moment that we domesticated ourselves, we need to identify when we developed this unparalleled social intelligence. What makes this possible are fossilized Homo sapiens skulls that hint at brain development. There are two relevant physical markers for our brain development. The first is the giant hole we have in our head when we are born. Unlike most mammals who are born with fully developed skulls, Homo sapiens and Neanderthal babies’ skull bones are unconnected so they can squeeze through the birth canal.
The Secret of Our Success: How Culture Is Driving Human Evolution, Domesticating Our Species, and Making Us Smarter by Joseph Henrich
agricultural Revolution, capital asset pricing model, Climategate, cognitive bias, Daniel Kahneman / Amos Tversky, delayed gratification, demographic transition, endowment effect, experimental economics, experimental subject, Flynn Effect, impulse control, Monkeys Reject Unequal Pay, Nash equilibrium, out of africa, phenotype, placebo effect, profit maximization, randomized controlled trial, risk tolerance, side project, social intelligence, social web, Steven Pinker, The Wisdom of Crowds, theory of mind, ultimatum game
Here the idea is that natural selection made us highly social and cooperative, and then by working together we conquered the globe.10 Thus, the three common explanations for our species’ ecological success are (1) generalized intelligence or mental processing power, (2) specialized mental abilities evolved for survival in the hunter-gatherer environments of our evolutionary past, and/or (3) cooperative instincts or social intelligence that permit high levels of cooperation. All of these explanatory efforts are elements in building a more complete understanding of human nature. However, as I’ll show, none of these approaches can explain our ecological dominance or our species’ uniqueness without first recognizing the intense reliance we have on a large body of locally adaptive, culturally transmitted information that no single individual, or even group, is smart enough to figure out in a lifetime.
However, the point stands that the humans did not obviously dominate their fellow apes on either working memory or information processing speed, despite our much larger brains. Based on this evidence, it would seem hard to argue that our species’ ecological dominance can be readily traced to our dazzling working memory or raw information processing speeds. The True Machiavellians Now, let’s consider strategic conflict. We are a highly social species, so perhaps our global dominance has its origins in our social intelligence. One leading view on which selection pressures drove the expansion of human brains and created our fancy mental abilities is called the Machiavellian intelligence hypothesis. This view emphasizes that our brains and intelligence are specialized for dealing with other people and argues that our brain size and intelligence arose from an “arms race” in which individuals competed in an ever-escalating battle of wits to strategically manipulate, trick, exploit, and deceive each other.
Nature Communications 5:3677. doi:10.1038/ncomms4677. Rasmussen, K., G. Herring, and H. Moltke. 1908. The People of the Polar North: A Record. London: K. Paul, Trench, Trübner & Co. Reader, S. M., Y. Hager, and K. N. Laland. 2011. “The evolution of primate general and cultural intelligence.” Philosophical Transactions of the Royal Society B: Biological Sciences 366 (1567):1017–1027. Reader, S. M., and K. N. Laland. 2002. “Social intelligence, innovation, and enhanced brain size in primates.” Proceedings of the National Academy of Sciences, USA 99 (7):4436–4441. Real, L. A. 1991. “Animal choice behavior and the evolution of cognitive architecture.” Science 253:980–86. Reali, F., and M. H. Christiansen. 2009. “Sequential learning and the interaction between biological and linguistic adaptation in language evolution.” Interaction Studies 10 (1):5–30.
Behave: The Biology of Humans at Our Best and Worst by Robert M. Sapolsky
autonomous vehicles, Bernie Madoff, biofilm, blood diamonds, British Empire, Broken windows theory, Brownian motion, car-free, clean water, cognitive dissonance, corporate personhood, corporate social responsibility, Daniel Kahneman / Amos Tversky, delayed gratification, desegregation, different worldview, double helix, Drosophila, Edward Snowden, en.wikipedia.org, epigenetics, Flynn Effect, framing effect, fudge factor, George Santayana, global pandemic, hiring and firing, illegal immigration, impulse control, income inequality, John von Neumann, Loma Prieta earthquake, long peace, longitudinal study, loss aversion, Mahatma Gandhi, meta analysis, meta-analysis, Mohammed Bouazizi, Monkeys Reject Unequal Pay, mouse model, mutually assured destruction, Nelson Mandela, Network effects, out of africa, Peter Singer: altruism, phenotype, placebo effect, publication bias, RAND corporation, risk tolerance, Rosa Parks, selective serotonin reuptake inhibitor (SSRI), self-driving car, Silicon Valley, social intelligence, Stanford marshmallow experiment, Stanford prison experiment, stem cell, Steven Pinker, strikebreaker, theory of mind, transatlantic slave trade, traveling salesman, trickle-down economics, twin studies, ultimatum game, Walter Mischel, wikimedia commons, zero-sum game
Well, duh; the brain needs to “get it right” with all its parts. But in a distinctive way in the frontal cortex. The point of the previous chapter was the brain’s plasticity—new synapses form, new neurons are born, circuits rewire, brain regions expand or contract—we learn, change, adapt. This is nowhere more important than in the frontal cortex. An oft-repeated fact about adolescents is how “emotional intelligence” and “social intelligence” predict adult success and happiness better than do IQ or SAT scores.33 It’s all about social memory, emotional perspective taking, impulse control, empathy, ability to work with others, self-regulation. There is a parallel in other primates, with their big, slowly maturing frontal cortices. For example, what makes for a “successful” male baboon in his dominance hierarchy? Attaining high rank is about muscle, sharp canines, well-timed aggression.
The picture of the bullies is no surprise either, starting with their disproportionately coming from families of single moms or younger parents with poor education and employment prospects. There are generally two profiles of the kids themselves—the more typical is an anxious, isolated kid with poor social skills, who bullies out of frustration and to achieve acceptance. Such kids typically mature out of bullying. The second profile is the confident, unempathic, socially intelligent kid with an imperturbable sympathetic nervous system; this is the future sociopath. There is an additional striking finding. You want to see a kid who’s really likely to be a mess as an adult? Find someone who both bullies and is bullied, who terrorizes the weaker at school and returns home to be terrorized by someone stronger.43 Of the three categories (bully, bullied, bully/bullied), they’re most likely to have prior psychiatric problems, poor school performance, and poor emotional adjustment.
That still doesn’t tell us why for some people novelty seeking means frequently switching their openings in chess games, while for others it means looking for a new locale because it’s getting stale being a mercenary in the Congo. No gene or handful of genes that we are aware of will tell us much about that. The Neuropeptides Oxytocin and Vasopressin Time for a quick recap from chapter 4. Oxytocin and vasopressin are involved in prosociality, ranging from parent/offspring bonds to monogamous bonds to trust, empathy, generosity, and social intelligence. Recall the caveats: (a) sometimes these neuropeptides are more about sociality than prosociality (in other words, boosting social information gathering, rather than acting prosocially with that information); (b) they most consistently boost prosociality in people who already lean in that direction (e.g., making generous people more generous, while having no effect on ungenerous people); and (c) the prosocial effects are within groups, and these neuropeptides can make people crappier to outsiders—more xenophobic and preemptively aggressive.
Humans Are Underrated: What High Achievers Know That Brilliant Machines Never Will by Geoff Colvin
Ada Lovelace, autonomous vehicles, Baxter: Rethink Robotics, Black Swan, call centre, capital asset pricing model, commoditize, computer age, corporate governance, creative destruction, deskilling, en.wikipedia.org, Freestyle chess, future of work, Google Glasses, Grace Hopper, industrial cluster, industrial robot, interchangeable parts, job automation, knowledge worker, low skilled workers, Marc Andreessen, meta analysis, meta-analysis, Narrative Science, new economy, rising living standards, self-driving car, sentiment analysis, Silicon Valley, Skype, social intelligence, Steve Jobs, Steve Wozniak, Steven Levy, Steven Pinker, theory of mind, Tim Cook: Apple, transaction costs
Those patterns looked very familiar to Pentland, who has spent years studying highly successful, creative people and groups. They all do those same things. In this study of groups, performance “depended upon how good the group members were at harvesting ideas from all of the participants and eliciting reactions to each new one,” he observed. It made sense that the groups with the best social skills would be most successful because what the “socially intelligent participants in our collective intelligence experiment may have been doing was enabling better idea flow by guiding the group toward briefer presentations of more ideas, encouraging responses, and ensuring that everyone contributed equally.” The operational value of social skills was explained. The mystery of how those skills make groups more effective was solved. The people who made teams most effective may or may not have been the best knowledge workers.
Both boys and girls receive testosterone as they develop before birth—boys much more than girls, obviously, though exact amounts vary within sexes—and we all produce it through our lives, males producing more than females. Much previous research had shown that testosterone affects social behavior in a big way. In children of both sexes, higher levels of fetal testosterone mean not only less eye contact at age one, but also poorer social understanding in general at age four and poorer social intelligence, as measured by the RME and other tests, at ages six to eight. That is, in the first way testosterone affects the brain, organizing it before birth, it seems to preprogram the brain for weaker social abilities. The researchers who gave women small doses of testosterone—the effect of which is only temporary—were investigating the second way it affects the brain, activating various processes from moment to moment.
Mythology of Work: How Capitalism Persists Despite Itself by Peter Fleming
1960s counterculture, anti-work, call centre, clockwatching, commoditize, corporate social responsibility, creative destruction, David Graeber, Etonian, future of work, G4S, Goldman Sachs: Vampire Squid, illegal immigration, Kitchen Debate, late capitalism, Mark Zuckerberg, market bubble, market fundamentalism, means of production, neoliberal agenda, Parkinson's law, post-industrial society, post-work, profit maximization, profit motive, quantitative easing, Results Only Work Environment, shareholder value, social intelligence, The Chicago School, transaction costs, wealth creators, working poor
With managers speaking out against the unsustainable force driving the injunction to produce, it is easy to conclude that capitalism itself is drawing upon an anti-work thematic, acknowledging parallels between managers’ own predicament and the conditions they expect from those they manage. However, this conclusion risks approaching the issue from the wrong angle. That the extra and ‘free’ work common is at the centre of the late-capitalist mode of production is without question. We work beyond the stipulations of our contracts, using our social intelligence to bypass the counterproductive rules of domination, even after hours, and avoid the impossible principles of neoliberal reason. The Italian autonomist movement has taught us much about this. The common is the working class’s shock absorber, cushioning (and facilitating) entire lives that have been put to work. It represents a social reservoir that picks up the slack of an unworkable system.
I think this is why we see more self-sufficient ideals entering the lexicon of management and HRM in the late 1990s, including distributive leadership, self-managing teams, flexi-work and the portfolio career. The message is clear. Rather than exhorting employees to display love towards the firm, which often resulted in satirized displays of deference, the corporation aims instead to tap the social intelligence already existing (including negative aptitudes such as fear, discussed in the last chapter). Even Tom Peters, the erstwhile guru of ‘strong cultures’, changed his mind about the efficacy of indoctrination. Instead he favoured ‘liberation management’, whereby the independent qualities of workers were tapped and utilized (Peters, 2003). There are a number of important reasons for this shift in how workers are exploited.
The Social Animal: The Hidden Sources of Love, Character, and Achievement by David Brooks
Albert Einstein, asset allocation, assortative mating, Atul Gawande, Bernie Madoff, business process, Cass Sunstein, choice architecture, clean water, creative destruction, Daniel Kahneman / Amos Tversky, David Brooks, delayed gratification, deliberate practice, disintermediation, Donald Trump, Douglas Hofstadter, Emanuel Derman, en.wikipedia.org, fear of failure, financial deregulation, financial independence, Flynn Effect, George Akerlof, Henri Poincaré, hiring and firing, impulse control, invisible hand, Joseph Schumpeter, labor-force participation, longitudinal study, loss aversion, medical residency, meta analysis, meta-analysis, Monroe Doctrine, Paul Samuelson, Richard Thaler, risk tolerance, Robert Shiller, Robert Shiller, school vouchers, six sigma, social intelligence, Stanford marshmallow experiment, Steve Jobs, Steven Pinker, the scientific method, The Spirit Level, The Wealth of Nations by Adam Smith, Thorstein Veblen, transaction costs, Walter Mischel, young professional
While most men are fertile, there is wide variation among the hairier sex when it comes to stability. Men are much more likely to have drug and alcohol addictions. They are much more likely to murder than women, and much, much more likely to abandon their children. There are more lemons in the male population than in the female population, and women have found that it pays to trade off a few points in the first-impression department in exchange for reliability and social intelligence down the road. So while Rob was looking at cleavage, Julia was looking for signs of trustworthiness. She didn’t need to do this consciously—thousands of years of genetics and culture had honed her trusting sensor. Marion Eals and Irwin Silverman of York University have conducted studies that suggest women are on average 60 to 70 percent more proficient than men at remembering details from a scene and the locations of objects placed in a room.
CHAPTER 10: INTELLIGENCE 1 “The Dunsinane Reforestation” Christopher Hitchens, Hitch 22 (New York: Twelve, 2010), 266. This exchange is based on a conversation the author witnessed between Hitchens and Salman Rushdie, two masters of these kinds of games. 2 Male babies make less Matt Ridley, The Agile Gene: How Nature Turns on Nurture (New York: Perennial, 2004), 59. 3 a person’s emotional state Daniel Goleman, Social Intelligence: The New Science of Human Relationships (New York: Bantam Dell, 2006) 139. 4 verbal memory and verbal fluency John Medina, Brain Rules: 12 Principles for Surviving and Thriving at Work, Home, and School (Seattle, WA: Pear Press, 2008), 262. 5 They don’t necessarily talk more Michael S. Gazzaniga, Human: The Science Behind What Makes Us Human (New York: Harper Perennial, 2008), 96. 6 Varieties of Capitalism Peter A.
Gilbert Sale and Suzanne Sale (New York: Penguin Books, 2004), 45. 7 Norepinephrine Fisher, 53. 8 Phenylethylamine Ayala Malakh Pines, Falling in Love: Why We Choose the Lovers We-Choose (New York: Routledge, 2005), 154. 9 “The caudate is also” Fisher, 69. 10 Arthur Aron Sadie F. Dingfelder, “More Than a Feeling,” Monitor on Psychology 38, no. 2 (February 2007): 40, http://www.apa.org/monitor/feb07/morethan.aspx. 11 Neuroscientist Jaak Panksepp Daniel Goleman, Social Intelligence: The New Science of Human Relationships (New York: Bantam Dell, 2006) 192. 12 A person in love Helen Fisher, “The Drive to Love: The Neural Mechanism for Mate Selection,” in The New Psychology of Love, eds. Robert J. Sternberg and Karin Weis (New Haven, CT: Yale University Press, 2006), 92–93. 13 A crucial answer came P. Read Montague, Peter Dayan, and Terrence J. Sejnowski, “A Framework for Mesencephalic Domanine Systems Based on Predictive Hebbian Learning,” Journal of Neuroscience 16, no. 5 (March 1, 1996): 1936–47, http://www.jneurosci.org/cgi/reprint/16/5/1936.pdf. 14 The main business Read Montague, Your Brain Is (Almost) Perfect: How We Make Decisions (New York: Plume, 2007), 117. 15 Dennis and Denise Brett W.
Transcend: The New Science of Self-Actualization by Scott Barry Kaufman
Albert Einstein, David Brooks, desegregation, Donald Trump, fear of failure, happiness index / gross national happiness, hedonic treadmill, helicopter parent, impulse control, job satisfaction, longitudinal study, Menlo Park, meta analysis, meta-analysis, Nelson Mandela, phenotype, Ralph Waldo Emerson, randomized controlled trial, Rosa Parks, science of happiness, Silicon Valley, Snapchat, social intelligence, Steven Pinker, theory of mind
—Abraham Maslow, Motivation and Personality (1954) Self-Transcendent Values B-loving people are high in universal concern (commitment to equal opportunity, justice, and protection for all people), universal tolerance (acceptance and understanding of those who are different from oneself, and promoting harmony and peace among diverse groups), trustworthiness and dependability for close loved ones, and benevolence and caring toward close friends and family.26 The greatest character strengths of B-loving people are kindness, love, zest for life, gratitude, perspective, forgiveness, social intelligence, appreciation, teamwork, hope, fairness, curiosity, judgment, humility, love of learning, humor, and spirituality.27 B-loving people also score high on some agency-related traits, such as grit, industriousness, productiveness, organization, and responsibility. Therefore, B-loving people show that agency and communion need not be at odds with each other. In his 1966 book The Duality of Human Existence, the psychologist David Bakan emphasized the importance of integrating two essential modes of human existence: agency and communion.28 According to Bakan, agency involves self-protection, self-assertion, separation, and isolation, whereas communion involves participation, contact, openness, unity, and “non-contractual co-operation.”
GROWTH CHALLENGE #16: USE YOUR SIGNATURE STRENGTHS IN NEW WAYS Strength Opposite Absence Excess Wisdom and Knowledge Creativity Triteness Conformity Eccentricity Curiousity Boredom Disinterest Nosiness Judgment Gullibility Uneffectiveness Cynicism Love of learning Orthodoxy Complacency “Know-it-all”-ism Perspective Foolishness Shallowness Ivory tower Strength Opposite Absence Excess Courage Bravery Cowardice Fright Foolhardiness Persistence Helplessness Laziness Obsessiveness Authenticity Deceit Phoniness Righteousness Vitality Lifelessness Restraint Hyperactivity Strength Opposite Absence Excess Love Intimacy Loneliness Isolation/autism Emotional promiscuity Kindness Cruelty Indifference Intrusiveness Social Intelligence Self-deception Obtuseness Psychobabbling Strength Opposite Absence Excess Justice Citizenship Narcissism Selfishness Chauvinism Fairness Prejudice Partisanship Detachment Leadership Sabotage Compliance Despotism Strength Opposite Absence Excess Temperance Forgiveness Vengefulness Mercilessness Permissiveness Humility Arrogance Footless self-esteem Self-deprecation Prudence Recklessness Sensation-seeking Prudishness Self-regulation Impulsivity Self-indulgence Inhibition Strength Opposite Absence Excess Transcendence Awe Criticism Oblivion Snobbery Gratitude Entitlement Rudeness Ingratiation Hope Despair Present orientation Pollyannaism Humor Dourness Humorlessness Buffoonery Spirituality Alienation Anomie Fanaticism In this growth challenge, you will take the VIA Survey of Character Strengths21 to become aware of your strengths, then explore your strengths, and finally to apply your strengths in new ways.
Steven, 22 right to shine, 71 “rising tide,” high-quality connections, 43 Robbers Cave study, 39 Rogers, Carl, xviii, xxiv, 42, 59, 78, 107, 165, 185 “role abandonment”/role engulfment, 139 romantic love, 138, 139, 141, 142, 194, 228 romantic passion, 145, 146–47 Roosevelt, Eleanor, 88, 168, 169, 180 Rowan, John, xxviii “rumble of panic,” 234, 235, 236 rumination, 10, 104–5, 106, 176, 214 Russian nesting dolls analogy, xxviii Ryan, Richard, 59 Sacks, Oliver, 85 sacredness in all things, xxiii, 222, 223 safety, xiii, xiv, xxviii, xxx, xxxi, xxxii, xxxiii, xxxiv, xxxv, 1, 6, 7–34, 37, 39, 48, 71, 81, 86, 91, 92, 98, 119, 136, 148, 167, 221, 231, 245 sailboat, xxxi–xxxix, xxxii, xxxv, 1, 34, 53, 80, 81, 129, 136, 183, 187 salience network, 116 Salzberg, Sharon, 120, 142 samadhi, 194 Sam’s story, 37 Sandelands, Lance, 42 Sane Society, The (Fromm), xxxvi Saroglou, Vassilis, 213 Schachtel, Rabbi Hyman, 50 Schnell, Tatjana, 238–39 scientific/intuitive, 240 scientific investigation and Theory Z, 228, 228n Seale, Colin, 33–34 Search for Authenticity, The (Bugental), 155 “second naivete,” 225 “second tier” spiral dynamic, 226 “sectarians,” 168 secure attachment, 17, 18, 42, 140–41, 144 security, xiv, xviii, xxix, xxx, xxxi, xxxii, xxxiii, xxxiv, xxxv, 1, 1–80, 84, 86, 93, 98, 100, 119, 141, 146, 147, 167, 225, 227, 231, 233, 238 See also insecurity seismic earthquake metaphor for trauma, 103–4 self-acceptance, xxv, 68, 90, 174, 238 See also acceptance self-actualization, xiii–xv, xiv, xxi, xxiii, xxix, xxx, xxxi, xxxiii–xxxiv, xxxvi, 83–90 peak experiences, 193, 195, 196, 197, 205, 215 security, 7, 70, 79, 80 Theory Z, xiii, 217–44 See also exploration; Kaufman, Scott Barry; love; Maslow, Abraham; purpose; transcendence “Self-Actualization: A Study of Psychological Health” (Maslow), 88 selfactualizationtests.com, xxi, 89, 123, 131, 208 self-awareness, xxv, xxxvi, 17, 26, 117, 133–34, 136, 141, 236 self-compassion, 132–33, 238 self-concordant goals, 166 self-control, 100, 133 self-determination, 164–65, 170, 180 Self-Diminishment (Awe Experience Scale), 208 self-esteem, xiii, xiv, xxviii, xxx, xxxiii, xxxv, xxxvi, 245 growth, 81, 84, 86, 98, 132, 134, 135, 136, 143, 148, 152, 160, 167 healthy transcendence, 219, 236, 238 security, 1, 5, 6, 19, 35, 43, 53, 54–80 self-expansion theory of love, 138–39, 142 self-honesty, 136–37 “Selfishness and Self-Love” (Fromm), 130 selfish/unselfish dichotomy, 153 self-loss, 203–6 self-love, 130–33, 139, 147, 174 pathological, 132 self-presentation strategy, 68, 69, 78 self-preservation, 6, 39, 54, 86 self-regulation, 25, 59, 105, 161 self-respect, xv, 23, 57, 84, 131, 139 self-transcendence, xxiv, 126–27, 181, 200, 201, 227 Seligman, Martin, xxv, 27–28, 115, 200, 201 sensation seeking, 99, 101 sense of self (self-worth), xv, xxv, xxviii, 52, 59, 60–61, 62, 65, 66, 68, 69, 74, 75, 110, 135, 139, 140, 205, 208, 226 Seppälä, Emma, 47–48, 51, 52 sex, 6, 28, 36, 37, 77, 84, 94, 100, 122, 137, 138, 142, 143n, 143–47, 193, 194, 225, 228, 230 sex and dominance research, 54, 55–56, 83 sexploration, 144–46 sexual assault, 102, 214 Sheldon, Kennon, 160, 163–64, 165, 166, 170 Shonkoff, Jack, 24, 27 “sickness-fostering” victory, 215 signature strengths, 166, 171, 176–77 silent vs. quiet ego, 135 Simpson, Jeffry, 21–22 60 Minutes (TV show), 97 Skee-Ball, xxxvi Skenazy, Lenore, 92 SMART goals, 171–72 Snyder, Charles, 177, 178 social anxiety, 95, 145, 211 social curiosity, 95–97 social environment, 95, 96, 202 “social evasion,” 39 social exploration, 94–97 social intelligence, 126 “social interest,” xviii, 54, 55, 58, 78 social isolation, 45, 48 social media, 50–51, 52, 163, 166 social protection system, 38, 39, 41, 61, 67, 69–70 social psychology, xx, xxi, 19, 39, 42–43, 45, 60, 77, 133, 144, 152 social value, 60–61, 62, 64, 66, 67, 73 society and human nature, 216 society and Theory Z, 232–33 Society for Personality and Social Psychology, 195 Some Do Care (Colby and Damon), 167 specific (quality of SMART goals), 171 Spiritual Evolution (Vaillant), 119 “splitting,” 26 “staleness of experience,” 111 states of mind and hierarchy of needs, xxvii–xxviii status-driven life motivations, 79, 80 Steger, Michael, 8–9 Sternberg, Robert, 30 “strange situation procedure,” 16 stress, 9–10, 11, 15, 15, 18–19, 21–22, 24, 25, 26, 38, 43, 45, 49, 69, 91, 101, 102, 106, 113, 132, 143, 174, 182, 208, 230 stress-adapted children, 30, 31–32 stress tolerance, 93, 98–99 striving for power, 55, 58, 78 striving wisely, 159–66, 161, 162, 163, 164, 165, 170, 173, 175 sublimation, 130, 154 suicide, 39, 46–47, 237 “Summer Notes on Social Psychology of Industry and Management” (Maslow), 152 Sumner, William Graham, 3–4, 5 supportive environment, 171, 178–83 suppression, xxvii, 5, 69, 70, 78, 101, 112, 129, 130, 140 Swann, William B., Jr., 61 synergy, xxxiv, 152–53, 169, 222, 225, 233 Tafarodi, Romin, 61, 62 Tedeschi, Richard, 102–3 Teicher, Martin, 25, 26 temporo-parietal junction, 202 Terror Management Theory (TMT), 236 “Theory of Human Motivation” (Maslow), 59, 86 “theory-of-mind” ability, 127–28 Theory of Successful Intelligence, 30 Theory X, 151 Theory Y, 151, 153, 220 Theory Z, xiii, 217–44 thinkLaw, 33 Third Force psychologists, xxiv Thorndike, Edward, 56, 83 Time (Awe Experience Scale), 208 “timelessness,” 194 time-saving vs. material purchases, 49 time-specific (quality of SMART goals), 171, 172 Torrance, E.
The Big Ratchet: How Humanity Thrives in the Face of Natural Crisis by Ruth Defries
agricultural Revolution, Columbian Exchange, demographic transition, double helix, European colonialism, food miles, Francisco Pizarro, Haber-Bosch Process, Intergovernmental Panel on Climate Change (IPCC), Internet Archive, John Snow's cholera map, out of africa, planetary scale, premature optimization, profit motive, Ralph Waldo Emerson, social intelligence, Thomas Malthus, trade route, transatlantic slave trade
: Richerson and Boyd 2005, 7. 40Beak size they’d inherited from their parents: This fascinating response of finch beak size to climatic variability is documented through the long-term work of Rosemary and Peter Grant (1993) on the Galapagos Islands as well as many other publications. 40Pulled a rope: Plotnik et al. 2011. 40With a harsh “kaw”: Cornell et al. 2012. 40Not be worth the investment: Potts (2011) reports that the brain consumes approximately 65 percent of a baby’s total energy requirement and 20 to 25 percent of an adult’s, even though brain tissue makes up only 2 percent of an adult’s body mass. 40Life-span of the animal: Mathematical arguments for the evolution of individual learning, social learning, and culture in relation to variability in the environment are made by Boyd and Richerson (2009), Enquist and Ghirlanda (2007), Henrich and McElreath (2003), and Strimling et al. (2009). 41Macaque’s complex social behavior: The history of the study of Japanese macaques is documented in Yamagiwa (2010). 41Fish for their next meal: Other examples of cultural diffusion in nonhuman species include the spread of lobtail feeding on humpback whales (Allen et al. 2013) and the adoption of social foraging norms in vervet monkeys (van de Waal et al. 2013). 42Process information, make it possible: Holloway (2008), and Blazek et al. (2011) describe brain evolution as the increase in brain size and the creation of more complex brain structures in the cerebral cortex. 43Climatically noisy Pleistocene: Potts 2011. 43Interacted at different times: The interplay of factors is put forward in Holloway (2008). Other primate and bird species show relationships between brain size and learning (Reader and Laland 2002; Sol et al. 2005). 43Less energy gets consumed in the process of digestion: Wrangham 2009, 43. 43Digestive tracts and large, learning brains: The argument of the social-intelligence hypothesis is from Aiello and Wheeler (1995), Reader and Laland (2002), Herrman et al. (2007), and Navarrete et al. (2011). 43Few parents would dare: The story of the Kelloggs is described in Henrich and McElreath (2008). 44Monkeys, chimpanzees, and children: Dean et al. (2012) conducted this experiment. 45Ground with a slender stick: This and other examples of cumulative technology in apes are given in Pradhan et al. (2012). 45“. . .
Archaeological data reveal slow rates of evolution during plant domestication. Evolution 65:171–183. Ranere, A., D. Piperno, I. Holst, R. Dickau, and J. Iriarte. 2009. The cultural and chronological context of early Holocene maize and squash domestication in the Central Balsas River Valley, Mexico. Proceedings of the National Academy of Sciences 106:5014–5018. Reader, S., and K. Laland. 2002. Social intelligence, innovation, and enhanced brain size in primates. Proceedings of the National Academy of Sciences 99:4436–4441. Richerson, P., and R. Boyd. 2005. Not by Genes Alone: How Culture Transformed Human Evolution. University of Chicago Press, Chicago. ———. 2010. The Darwinian theory of human cultural evolution and gene-culture coevolution. In M. Bell, D. Futuyma, W. Eanes, and J. Levinton, eds., Evolution Since Darwin: The First 150 Years.
The End of Nice: How to Be Human in a World Run by Robots (Kindle Single) by Richard Newton
3D printing, Black Swan, British Empire, Buckminster Fuller, Clayton Christensen, crowdsourcing, deliberate practice, disruptive innovation, fear of failure, Filter Bubble, future of work, Google Glasses, Isaac Newton, James Dyson, Jaron Lanier, Jeff Bezos, job automation, lateral thinking, Lean Startup, low skilled workers, Mark Zuckerberg, move fast and break things, move fast and break things, Paul Erdős, Paul Graham, recommendation engine, rising living standards, Robert Shiller, Robert Shiller, Silicon Valley, Silicon Valley startup, skunkworks, social intelligence, Steve Ballmer, Steve Jobs, Y Combinator
In his study of iconoclastic innovators Berns identifies the following three characteristics as key to being creative and successful: Different perception: Seeing the world differently enables you to imagine new possibilities where others see the same. This of course is a feature of the Anti-Conform mentality and thinking differently. Fear management: As you take risks and buck the convention of “Nice” you must be able to handle the fear of failure, social ostracism, or potential mockery that is highly likely to accompany this different direction. You must, in other words, be comfortable being Anti-Safe. Social intelligence: If you have new ideas, new ways of seeing things and want others to see the value of this – whether it is art or business or something else – then you must be able to persuade people. You have every right to treat your art as something wonderful that will speak for itself, and unless you are lucky or have a famous mum or dad it will probably be ignored. To succeed you must be able to “justify and distribute the value of your innovative ideas”, says Berns.
The American Dream Is Not Dead: (But Populism Could Kill It) by Michael R. Strain
Bernie Sanders, business cycle, centre right, creative destruction, deindustrialization, Donald Trump, feminist movement, full employment, gig economy, Gini coefficient, income inequality, job automation, labor-force participation, market clearing, market fundamentalism, new economy, Robert Gordon, Ronald Reagan, social intelligence, Steven Pinker, The Rise and Fall of American Growth, upwardly mobile, working poor
Over the past half-decade, the fastest-growing jobs in the new middle include sales representatives, truck drivers, managers of personal service workers, heating and air conditioning mechanics and installers, computer support specialists, self-enrichment education teachers, event planners, health technologists and technicians, massage therapists, social workers, marriage and family counselors, audiovisual technicians, paralegals, health-care social workers, chefs and head cooks, and food service managers. These jobs probably require a little more education, skills, and experience than jobs in the old middle. They require more situational adaptability, social intelligence, customer service and interpersonal interaction, low-end managerial skills, and administrative, technical, and communication skills. So, yes, populists on the left and right are correct that traditional middle-class jobs are shrinking as a share of total employment. These middle-class jobs do represent a hollowing out of the middle. But in recent decades, a new middle is emerging. DYNAMISM Changes in the types of jobs represented in the middle of the labor market is a reality of economic dynamism.
Alone Together by Sherry Turkle
Albert Einstein, Columbine, global village, Hacker Ethic, helicopter parent, Howard Rheingold, industrial robot, information retrieval, Jacques de Vaucanson, Jaron Lanier, Joan Didion, John Markoff, Kevin Kelly, lifelogging, Loebner Prize, Marshall McLuhan, meta analysis, meta-analysis, Nicholas Carr, Norbert Wiener, Panopticon Jeremy Bentham, Ralph Waldo Emerson, Rodney Brooks, Skype, social intelligence, stem cell, technoutopianism, The Great Good Place, the medium is the message, theory of mind, Turing test, Vannevar Bush, Wall-E, women in the workforce, Year of Magical Thinking
Some children wonder, if these robots belong with people, then what failings in people require robots? For one thirteen-year-old boy, Cog suggests that “humans aren’t good enough so they need something else.” In our first-encounters study children’s time with the robots is unstructured. We ask questions, but not many. The children are encouraged to say whatever comes to mind. Our goal is to explore some rather open questions: How do children respond to an encounter with a novel form of social intelligence? What are they looking for? To this last, the answer is, most simply, that children want to connect with these machines, to teach them and befriend them. And they want the robots to like, even love, them. Children speak of this directly (“Cog loves me”; “Kismet is like my sister; she loves me”; “He [Cog] is my pal; he wants to do things with me, everything with me. Like a best friend.”).
MacDorman and Hiroshi Ishiguro, “The Uncanny Advantage of Using Androids in Cognitive and Social Science Research,” Interaction Studies 7, no. 3 (2006): 297-337, and Karl F. MacDorman et al., “Too Real for Comfort: Uncanny Responses to Computer Generated Faces,” Computers in Human Behavior 25 (2009): 695-710. Like Ishiguro, roboticist David Hanson aspires to build realistic androids that challenge the notion of the uncanny valley. “We conclude that rendering the social human in all possible detail can help us to better understand social intelligence, both scientifically and artistically.” See David Hanson et al., “Upending the Uncanny Valley,” Association for the Advancement of Artificial Intelligence, May 11, 2005, www.aaai.org/Papers/Workshops/2005/WS-05-11/WS05-11-005.pdf (accessed November 14, 2009). 7 A sympathetic reading of the possibilities of deep human-robot connections is represented in Peter H. Kahn Jr. et al., “What Is Human?
For a discussion that focuses on the work of roboticist Maja Matarić in this area, see Jerome Groopman, “Robots That Care: Advances in Technological Therapy,” The New Yorker, November 2, 2009, www.newyorker.com/reporting/2009/11/02/091102fa_fact_groopman (accessed November 11, 2009). 26 This phrase is drawn from Roger Shattuck’s book on the “Wild Child” of Aveyron. The Forbidden Experiment (New York: Farrar, Strauss, and Giroux, 1980). 27 “Basic trust” is Erik Erikson’s phrase; see Childhood and Society (New York: Norton, 1950) and Identity and the Life Cycle (1952; New York: Norton, 1980). 28 At MIT, the question of risk strikes most of my students as odd. They assume, along with roboticist David Hanson, that eventually robots “will evolve into socially intelligent beings, capable of love and earning a place in the extended human family.” See Groopman, “Robots That Care.” 29 A University of Michigan study found that today’s college students have less empathy than those of the 1980s or 1990s. Today’s generation scored about 40 percent lower in empathy than their counterparts did twenty or thirty years ago. Sara Konrath, a researcher at the University of Michigan’s Institute for Social Research, conducted, with University of Michigan graduate student Edward O’Brien and undergraduate student Courtney Hsing, a meta-analysis that looked at data on empathy, combining the results of seventy-two different studies of American college students conducted between 1979 and 2009.
The Moral Animal: Evolutionary Psychology and Everyday Life by Robert Wright
"Robert Solow", agricultural Revolution, Andrei Shleifer, Asian financial crisis, British Empire, centre right, cognitive dissonance, double entry bookkeeping, double helix, fault tolerance, Francis Fukuyama: the end of history, George Gilder, global village, invention of gunpowder, invention of movable type, invention of the telegraph, invention of writing, invisible hand, John Nash: game theory, John von Neumann, Marshall McLuhan, Norbert Wiener, planetary scale, pre–internet, profit motive, Ralph Waldo Emerson, random walk, Richard Thaler, rising living standards, Silicon Valley, social intelligence, social web, Steven Pinker, talking drums, the medium is the message, The Wealth of Nations by Adam Smith, trade route, your tax dollars at work, zero-sum game
vervet monkey vocabulary: Seyfarth (1987), p. 444. young vervet learning: Nishida (1987), p. 473. ten to forty messages: Wilson (1975). neocortex and large social groups: Dunbar (1992). Vampire bats: Ridley (1996), p. 69. coalition-forming and intelligence: Ridley (1996), p. 160. “feasted in peace”: Pinker (1997), p. 193. “mind blind”: Pinker (1997), pp. 331–33. †our evolved social intelligence: The properties of a specifically social intelligence may have helped hape the nature of science. The tendency of the scientific mind to distinguish between “cause” and “effect” may indeed, as the mystics say, misrepresent the ultimate nature of a seamless reality, attributing independent agency to parts of an interdependent whole. But this tendency has certainly had its practical payoffs. And it may owe much to our instinct for social analysis—thinking about who has caused whom to do what to whom, and why.
But the mental tricks that constitute it become vivid when suddenly they’re missing. Autistic children have trouble putting themselves in other people’s shoes. Normal four-year-olds know that people who haven’t looked inside a box don’t know what’s in it. Autistic children lack this instinct for ascribing mental perspective to people; they are “mind blind.” They may be very smart—capable of superhuman mathematical feats—but they lack key parts of our evolved social intelligence.† So far as getting on the co-evolutionary escalator goes, one key implication of coalitional contention is the emphasis it places on communication. If your team wants to subvert the dominant male, advanced planning is advisable. For that matter, if your team just wants to go hunting, and bring back huge hunks of meat that fill the dominant coalition with envy and females with sudden affection, communication is nice.
The Pentagon's Brain: An Uncensored History of DARPA, America's Top-Secret Military Research Agency by Annie Jacobsen
Albert Einstein, Berlin Wall, colonial rule, crowdsourcing, cuban missile crisis, Dean Kamen, drone strike, Edward Snowden, Fall of the Berlin Wall, game design, John Markoff, John von Neumann, license plate recognition, Livingstone, I presume, low earth orbit, megacity, Menlo Park, meta analysis, meta-analysis, Mikhail Gorbachev, Murray Gell-Mann, mutually assured destruction, Norman Mailer, operation paperclip, place-making, RAND corporation, Ronald Reagan, Ronald Reagan: Tear down this wall, social intelligence, stem cell, Stephen Hawking, zero-sum game
Nowhere in Secretary Rumsfeld’s thirty-nine-page monograph for the president, a summation of Cebrowski’s vision titled “Transformation Planning Guidance,” was human behavior mentioned or even alluded to. While Cebrowski did television interviews addressing congressional concerns, the Office of Force Transformation added four new slides to its “Transforming Defense” PowerPoint presentation. One of the two new slides now addressed “Social Intelligence as a key to winning the peace,” and the other addressed “Social Domain Cultural Awareness” as a way to give warfighters a “cognitive advantage.” On PBS NewsHour, Cebrowski defended network-centric warfare and again reminded the audience that the United States had, he believed, achieved operational dominance in Iraq, completing major combat operations in just twenty-one days. “That speed of advance was absolutely unheard of,” Cebrowski said.
In 2004, amid the ever-growing IED crisis, Scales proposed to Cebrowski that the Pentagon needed a social science program to get inside how the enemy thought. The United States needed to know what made the enemy tick. Cebrowski agreed. “Knowledge of one’s enemy and his culture and society may be more important than knowledge of his order of battle,” Cebrowski wrote in Military Review, a bi-monthly Army journal. The Office of Force Transformation now publicly endorsed “social intelligence” as a new warfighting concept, the idea that in-depth knowledge of local customs in Iraq and elsewhere would allow the Pentagon to better determine who was friend and who was foe in a given war theater. “Combat troops are becoming intelligence operatives to support stabilization and counterinsurgency operations in Iraq,” Cebrowski’s office told Defense News in April 2004. It was hearts and minds all over again, reemerging in Iraq.
“It was not a panacea,” he says, “but we needed nation rebuilding. The social science community had tremendous insights into [the] serious problems going on [there], and a sector of DoD was ready to make serious investments into social sciences,” he says of DARPA’s efforts. Arthur Cebrowski died of cancer the following year. The Office of Force Transformation did not last long without him and within a year after his death closed down, but the social intelligence programs forged ahead. Montgomery McFate found a new advocate in General David Petraeus, commander of the Multi-National Security Transition Command, Iraq, who shared her vision about the importance of winning hearts and minds. Petraeus began talking about “stability operations” and using the phrase “culture-centric warfare” when talking to the press. He said that understanding people was likely to become more important in future battles than “shock and awe and network-centric warfare.”
The Technology Trap: Capital, Labor, and Power in the Age of Automation by Carl Benedikt Frey
"Robert Solow", 3D printing, autonomous vehicles, basic income, Bernie Sanders, Branko Milanovic, British Empire, business cycle, business process, call centre, Capital in the Twenty-First Century by Thomas Piketty, Clayton Christensen, collective bargaining, computer age, computer vision, Corn Laws, creative destruction, David Graeber, David Ricardo: comparative advantage, deindustrialization, demographic transition, desegregation, deskilling, Donald Trump, easy for humans, difficult for computers, Edward Glaeser, Elon Musk, Erik Brynjolfsson, everywhere but in the productivity statistics, factory automation, falling living standards, first square of the chessboard / second half of the chessboard, Ford paid five dollars a day, Frank Levy and Richard Murnane: The New Division of Labor, full employment, future of work, game design, Gini coefficient, Hyperloop, income inequality, income per capita, industrial cluster, industrial robot, intangible asset, interchangeable parts, Internet of things, invention of agriculture, invention of movable type, invention of the steam engine, invention of the wheel, Isaac Newton, James Hargreaves, James Watt: steam engine, job automation, job satisfaction, job-hopping, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, Joseph Schumpeter, Kickstarter, knowledge economy, knowledge worker, labor-force participation, labour mobility, Loebner Prize, low skilled workers, Malcom McLean invented shipping containers, manufacturing employment, mass immigration, means of production, Menlo Park, minimum wage unemployment, natural language processing, new economy, New Urbanism, Norbert Wiener, oil shock, On the Economy of Machinery and Manufactures, Pareto efficiency, pattern recognition, pink-collar, Productivity paradox, profit maximization, Renaissance Technologies, rent-seeking, rising living standards, Robert Gordon, robot derives from the Czech word robota Czech, meaning slave, Second Machine Age, secular stagnation, self-driving car, Silicon Valley, Simon Kuznets, social intelligence, speech recognition, spinning jenny, Stephen Hawking, The Future of Employment, The Rise and Fall of American Growth, The Wealth of Nations by Adam Smith, Thomas Malthus, total factor productivity, trade route, Triangle Shirtwaist Factory, Turing test, union organizing, universal basic income, washing machines reduced drudgery, wealth creators, women in the workforce, working poor, zero-sum game
Yet Thomas Savory, Thomas Newcomen, and James Watt, all realized that the steam engine was a GPT, and they conceived many applications for it. As noted above, AI is another GPT, and it is already being used to perform both mental and manual tasks. Because its potential applications are so vast, Michael and I began by looking at tasks that computers still perform poorly and where technological leaps have been limited in recent years. For a glimpse of the state of the art in machine social intelligence, for example, consider the Turing test, which captures the ability of an AI algorithm to communicate in a way that is indistinguishable from an actual human. The Loebner Prize is an annual Turing test competition that awards prizes to chat bots that are considered to be the most humanlike. These competitions are straightforward. A human judge holds computer-based textual interactions with both an algorithm and a human at the same time.
In a paper written in 2013, Michael and I noted: “Sophisticated algorithms have so far failed to convince judges about their human resemblance.”49 Yet a year later the computer program Eugene Goostman managed to convince 33 percent of the judges that it was a person. Some people subsequently argued that we had underestimated the accelerating pace of change. However, such claims exaggerate the capabilities of Eugene Goostman, which simulated a thirteen-year-old boy speaking English as his second language. Even if we assume that algorithms at some point will be able to effectively reproduce human social intelligence in basic texts, many jobs center on personal relationships and complex interpersonal communication. Computer programmers consult with managers or clients to clarify intent, identify problems, and suggest changes. Nurses work with patients, families, or communities to design and implement programs to improve overall health. Fund-raisers identify potential donors and build relationships with them.
See mass production American Telephone and Telegraph Company (AT&T), 315 annus mirabilis of 1769, 97, 148 anti-Amazon law, 290 Antikythera mechanism, 39 Appius Claudius, 37 Archimedes, 30, 39 Aristotle, 1, 39 Arkwright, Richard, 94, 101 artificial intelligence (AI), 5, 36, 301–41, 228, 342; Alexa (Amazon), 306; AlphaGo (Deep Mind), 301, 302; Amara’s Law, 323–25; artificial neural networks, 304; autonomous robots, 307; autonomous vehicles, 308, 310, 340; big data, 303; Chinese companies, 313; Dactyl, 313; data, as the new oil, 304; Deep Blue (IBM), 301, 302; deep learning, 304; -driven unemployment, 356; Google Translate, 304; Gripper, 313; internet traffic, worldwide, 303; JD. com, 313; Kiva Systems, 311; machine social intelligence, 317; Microsoft, 306; misconception, 311; multipurpose robots, 327; Neural Machine Translation, 304; neural networks, 303, 305, 314; pattern recognition, 319; phrase-based machine translation, 304; Siri (Apple), 306; speech recognition technology, 306; Turing test, 317; virtual agents, 306; voice assistant, 306; warehouse automation, 314 artisan craftsmen, 8; in domestic system, 118, 131; emigration of, 83; factory job, transition to, 124; fates of, 17; full-time, 34; middle-income, 11, 16, 24, 135; replacement of, 9, 16, 218 Ashton, T.
The Intelligence Trap: Revolutionise Your Thinking and Make Wiser Decisions by David Robson
active measures, Affordable Care Act / Obamacare, Albert Einstein, Alfred Russel Wallace, Atul Gawande, availability heuristic, cognitive bias, corporate governance, correlation coefficient, cuban missile crisis, Daniel Kahneman / Amos Tversky, dark matter, deliberate practice, dematerialisation, Donald Trump, Flynn Effect, framing effect, fundamental attribution error, illegal immigration, Isaac Newton, job satisfaction, knowledge economy, lone genius, meta analysis, meta-analysis, Nelson Mandela, obamacare, pattern recognition, price anchoring, Richard Feynman, risk tolerance, Silicon Valley, social intelligence, Steve Jobs, the scientific method, theory of mind, traveling salesman, ultimatum game, Y2K, Yom Kippur War
Practical intelligence, meanwhile, concerns a different kind of innovation: the ability to plan and execute an idea, and to overcome life’s messy, ill-defined problems in the most pragmatic way possible. It includes traits like ‘metacognition’ – whether you can judge your strengths and your weaknesses and work out the best ways to overcome them, and the unspoken, tacit knowledge that comes from experience and allows you to solve problems on the fly. It also includes some of the skills that others have called emotional or social intelligence – the ability to read motives and to persuade others to do what you want. Among the Termites, Shelley Smith Mydans’ quick thinking as a war reporter, and her ability to navigate her escape from a Japanese prison camp, may best personify this kind of intelligence. Of the three styles of thinking, practical intelligence may be the hardest to test or teach explicitly, but Sternberg suggests there are ways to cultivate it at school and university.
Woolley told me that these findings have already changed opinions. ‘Some organisations have taken what we have found and just flipped it into hiring more women.’ Whether or not you would deliberately change the gender balance on the basis of these findings, hiring people of both sexes with greater social sensitivity is an obvious way to boost the collective intelligence of an organisation. The very name – soft skills – that we attribute to social intelligence often implies that it is the weaker, secondary counterpart to other forms of intelligence, and the tests we use to explore interpersonal dynamics – such as the Myers-Briggs Type Inventory – are poor predictors of actual behaviour.13 If you are attempting to recruit a smart team, Woolley’s research strongly suggests that these social skills should be a primary concern, and in the same way that we measure cognitive ability using standardised tests, we should begin to use scientifically verified measures to assess this quality.
SUPERHUBS: How the Financial Elite and Their Networks Rule Our World by Sandra Navidi
activist fund / activist shareholder / activist investor, assortative mating, bank run, barriers to entry, Bernie Sanders, Black Swan, Blythe Masters, Bretton Woods, butterfly effect, Capital in the Twenty-First Century by Thomas Piketty, Carmen Reinhart, central bank independence, cognitive bias, collapse of Lehman Brothers, collateralized debt obligation, commoditize, conceptual framework, corporate governance, Credit Default Swap, credit default swaps / collateralized debt obligations, crony capitalism, diversification, East Village, Elon Musk, eurozone crisis, family office, financial repression, Gini coefficient, glass ceiling, Goldman Sachs: Vampire Squid, Google bus, Gordon Gekko, haute cuisine, high net worth, hindsight bias, income inequality, index fund, intangible asset, Jaron Lanier, John Meriwether, Kenneth Arrow, Kenneth Rogoff, knowledge economy, London Whale, Long Term Capital Management, longitudinal study, Mark Zuckerberg, mass immigration, McMansion, mittelstand, money market fund, Myron Scholes, NetJets, Network effects, offshore financial centre, old-boy network, Parag Khanna, Paul Samuelson, peer-to-peer, performance metric, Peter Thiel, plutocrats, Plutocrats, Ponzi scheme, quantitative easing, Renaissance Technologies, rent-seeking, reserve currency, risk tolerance, Robert Gordon, Robert Shiller, Robert Shiller, rolodex, Satyajit Das, shareholder value, Silicon Valley, social intelligence, sovereign wealth fund, Stephen Hawking, Steve Jobs, The Future of Employment, The Predators' Ball, The Rise and Fall of American Growth, too big to fail, women in the workforce, young professional
They combine substance with personality and have the ability to focus on someone with undivided and genuine attention, which makes others feel special. They project a strong presence, draw attention to themselves, and enrapture audiences. With their self-confidence and ability to charm, they manage to persuade and align people, furthering their own objectives. Most people at the top have a great sense of humor—an expression of social intelligence that is supremely helpful in disarming and bonding with people. Their often self-deprecating quick wit bridges differences in culture, status, and interests. George Soros is masterful in firing off unexpectedly dry tidbits. When reminded of something he’d rather avoid, he’d reply, “I do not remember the past; I only remember the future,” and when asked about his work habits, he says, “When I have to, I work furiously because I am furious that I have to work.”
It is unclear what her next career step will be after her IMF term ends, but it is not entirely impossible that she may become the first female French president. I wish I could infer some lessons from Madame Lagarde’s steep ascent other than get the best education, have grit, and stay true to yourself, but many other women have done the same and not achieved her level of success. She is indeed uniquely qualified and possesses a high degree of both social intelligence and resilience, but I also think that in her case all the stars were aligned. Once she found an upward trajectory, she had the ability and good fortune to maintain that positive momentum. Generally, I must say that I am not too optimistic that things will significantly change for the better in the near future. This is a pity, as there is ample proof of the objective business benefits produced by more diversity of gender, backgrounds, experiences, thought, and opinions.
The End of Men: And the Rise of Women by Hanna Rosin
affirmative action, call centre, cognitive dissonance, David Brooks, delayed gratification, edge city, facts on the ground, financial independence, hiring and firing, housing crisis, income inequality, informal economy, job satisfaction, low skilled workers, manufacturing employment, meta analysis, meta-analysis, new economy, New Urbanism, Norman Mailer, Northern Rock, post-work, postindustrial economy, purchasing power parity, Results Only Work Environment, Silicon Valley, social intelligence, Stanford prison experiment, Steven Pinker, union organizing, upwardly mobile, white picket fence, women in the workforce, young professional
Our vast and struggling middle class, where the disparities between men and women are the greatest, is slowly turning into a matriarchy, with men increasingly absent from the workforce and from home, and women making all the decisions. In the past, men derived their advantage largely from size and strength, but the postindustrial economy is indifferent to brawn. A service and information economy rewards precisely the opposite qualities—the ones that can’t be easily replaced by a machine. These attributes—social intelligence, open communication, the ability to sit still and focus—are, at a minimum, not predominantly the province of men. In fact, they seem to come more easily to women. Women in poor parts of India are learning English faster than men, to meet the demands of new global call centers. Women own more than 40 percent of private businesses in China, where a red Ferrari is the new status symbol for female entrepreneurs.
The new model is sometimes called “post-heroic” or “transformational,” in the words of the historian and leadership expert James MacGregor Burns. The aim is to behave like a good coach, and channel your charisma to motivate others to be hardworking and creative. The model is not explicitly defined as feminine, but it echoes literature about male-female differences. A program at Columbia Business School, for example, teaches sensitive leadership and social intelligence, including better reading of facial expressions and body language. “We never explicitly say, ‘Develop your feminine side,’ but it’s clear that’s what we’re advocating,” says Jamie Ladge, a business professor at Northeastern University. Julie Gerberding, an infectious disease specialist who was the head of the Centers for Disease Control and is now the president of Merck Vaccines, calls the new style “meta-leadership” or “horizontal leadership”: Horizontal leadership takes different skills than vertical leadership.
Descartes' Error: Emotion, Reason and the Human Brain by António R. Damásio
Albert Einstein, Benoit Mandelbrot, Daniel Kahneman / Amos Tversky, discovery of DNA, experimental subject, longitudinal study, mandelbrot fractal, placebo effect, Richard Feynman, social intelligence, theory of mind
We all know persons who are exceedingly clever in their social navigation, who have an unerring sense of how to seek advantage for themselves and for their group, but who can be remarkably inept when trusted with a nonpersonal, nonsocial problem. The reverse condition is just as dramatic: We all know creative scientists and artists whose social sense is a disgrace, and who regularly harm themselves and others with their behavior. The absent-minded professor is the benign variety of the latter type. At work, in these different personality styles, are the presence or absence of what Howard Gardner has called “social intelligence,” or the presence or absence of one or the other of his multiple intelligences such as the “mathematical.”3 The personal and immediate social domain is the one closest to our destiny and the one which involves the greatest uncertainty and complexity. Broadly speaking, within that domain, deciding well is selecting a response that will be ultimately advantageous to the organism in terms of its survival, and of the quality of that survival, directly or indirectly.
., 271, 280, 294 Searle, John, 236, 296 Secondary emotions, 134–39 Sejnowski, T. J., 186, 271, 280, 287, 294 Self, 226–27 neural, 236–44 Serotonin, 76-78 Shafir, Eldar, 286 Shallice, Tim, 42, 190, 272, 287 Shatz, C, 281 Shepard, Roger, 280 Silverman, M. S., 279 Singer, W., 277–78 Sizer, Nelson, 16–17, 270 Skin conductance response description of, 207–12 predicting the future and, 219–22 Social intelligence, 169 Somatic-marker hypothesis “As If” symbols, 184 attention and working memory and, 196–98 biases and the creation of order, 198–200 description of, 173–75 emotion and reasoning, 191–96 intuition, 187–89 neural network for somatic markers, 180–83 origin of somatic markers, 177–80 overt and covert somatic markers, 184–85 reasoning outside the personal and social domains, 189-91 Somatic-marker hypothesis, testing of autonomic nervous system responses and, 205–12 gambling experiments, 212-17 myopia for the future, 217–19 predicting the future and skin conductance response, 219–22 Somatosensory, 65 Sox, H.
Conscious Capitalism, With a New Preface by the Authors: Liberating the Heroic Spirit of Business by John Mackey, Rajendra Sisodia, Bill George
Berlin Wall, Buckminster Fuller, business process, carbon footprint, collective bargaining, corporate governance, corporate social responsibility, creative destruction, crony capitalism, cross-subsidies, en.wikipedia.org, Everything should be made as simple as possible, Fall of the Berlin Wall, fear of failure, Flynn Effect, income per capita, invisible hand, Jeff Bezos, job satisfaction, lone genius, Mahatma Gandhi, microcredit, Nelson Mandela, Occupy movement, profit maximization, Ralph Waldo Emerson, shareholder value, six sigma, social intelligence, Social Responsibility of Business Is to Increase Its Profits, Steve Jobs, Steven Pinker, The Fortune at the Bottom of the Pyramid, The Wealth of Nations by Adam Smith, too big to fail, union organizing, wealth creators, women in the workforce, zero-sum game
“Howard Gardner,” last modified June 12, 2012, http://en.wikipedia.org/wiki/Howard_Gardner; see also Howard Gardner, Frames of Mind: The Theory of Multiple Intelligences (New York: Basic Books, 1993). 3. Daniel Goleman, Emotional Intelligence: Why It Can Matter More Than IQ (New York: Bantam, 1995). Goleman also wrote another excellent book Social Intelligence: The New Science of Human Relationships (New York: Bantam, 2006). We have not separated social intelligence from emotional, spiritual, and systems intelligence into its own category, because we believe it is better seen as a characteristic of the other three categories. 4. Danah Zohar and Ian Marshall, Spiritual Capital: Wealth We Can Live By (San Francisco: Berrett-Koehler, 2004), 3. 5. John A. Byrne, World Changers: 25 Entrepreneurs Who Changed Business as We Knew It (New York: Portfolio/Penguin, 2011), 52. 6.
Smart Mobs: The Next Social Revolution by Howard Rheingold
A Pattern Language, augmented reality, barriers to entry, battle of ideas, Brewster Kahle, Burning Man, business climate, citizen journalism, computer vision, conceptual framework, creative destruction, Douglas Engelbart, Douglas Engelbart, experimental economics, experimental subject, Extropian, Hacker Ethic, Hedy Lamarr / George Antheil, Howard Rheingold, invention of the telephone, inventory management, John Markoff, John von Neumann, Joi Ito, Joseph Schumpeter, Kevin Kelly, Metcalfe's law, Metcalfe’s law, more computing power than Apollo, New Urbanism, Norbert Wiener, packet switching, Panopticon Jeremy Bentham, pattern recognition, peer-to-peer, peer-to-peer model, pez dispenser, planetary scale, pre–internet, prisoner's dilemma, RAND corporation, recommendation engine, Renaissance Technologies, RFID, Richard Stallman, Robert Metcalfe, Robert X Cringely, Ronald Coase, Search for Extraterrestrial Intelligence, SETI@home, sharing economy, Silicon Valley, skunkworks, slashdot, social intelligence, spectrum auction, Steven Levy, Stewart Brand, the scientific method, transaction costs, ultimatum game, urban planning, web of trust, Whole Earth Review, zero-sum game
Furthermore, these regularities are quantifiable and can be experimentally tested.66 The interesting statement is the last one. There have been varieties of theories about the Internet as the nervous system of a global brain, but Huberman and colleagues have made clever use of markets and game simulations as computational test beds for experiments with emergent group intelligence. The fall that I visited Huberman, he and his colleagues had used “information markets” to perform experiments in emergent social intelligence and found that group forecasts were more accurate than those of any of the individual participants’ forecasts.67 In information markets, members trade symbolic currency representing predictions of public information. The Hollywood Stock Exchange, for example, uses the market that emerges from the trading of symbolic shares to predict box office revenues and Oscar winners. The HP research team makes the extraordinary claim that they have created a mathematically verifiable methodology for extracting emergent intelligence from a group and using the group’s knowledge to predict the future in a limited but useful realm: “One can take past predictive performance of participants in information markets and create weighting schemes that will predict future events, even if they are not the same event on which the performance was measured.”68 Decades ago, computer scientists thought that someday there would be forms of “artificial intelligence,” but with the exception of a few visionaries, they never thought in terms of computer-equipped humans as a kind of social intelligence.
The HP research team makes the extraordinary claim that they have created a mathematically verifiable methodology for extracting emergent intelligence from a group and using the group’s knowledge to predict the future in a limited but useful realm: “One can take past predictive performance of participants in information markets and create weighting schemes that will predict future events, even if they are not the same event on which the performance was measured.”68 Decades ago, computer scientists thought that someday there would be forms of “artificial intelligence,” but with the exception of a few visionaries, they never thought in terms of computer-equipped humans as a kind of social intelligence. Although everyone who understands the use of statistical techniques to make predictions hastens to add the disclaimer that surprises are inevitable, and one of the fundamental characteristics of complex adaptive systems is their unpredictability, the initial findings that internetworked groups of humans can exhibit emergent prediction capabilities are potentially profound. Another research group that takes emergent group intelligence seriously is the laboratory at Los Alamos, where a group of “artificial life” researchers issued a report in 1998, “Symbiotic Intelligence: Self-Organizing Knowledge on Distributed Networks, Driven by Human Interaction.”69 The premise of this interdisciplinary team is based on the view proposed by some in recent years that human society is an adaptive collective organism and that social evolution parallels and unfolds according to the same dynamics as biological evolution. 70 According to this theory, which I will revisit in the next chapter, new knowledge and new technologies have made possible the evolution of the maximum size of the functioning social group from tribes to nations to global coalitions.
A World Without Work: Technology, Automation, and How We Should Respond by Daniel Susskind
3D printing, agricultural Revolution, AI winter, Airbnb, Albert Einstein, algorithmic trading, artificial general intelligence, autonomous vehicles, basic income, Bertrand Russell: In Praise of Idleness, blue-collar work, British Empire, Capital in the Twenty-First Century by Thomas Piketty, cloud computing, computer age, computer vision, computerized trading, creative destruction, David Graeber, David Ricardo: comparative advantage, demographic transition, deskilling, disruptive innovation, Donald Trump, Douglas Hofstadter, drone strike, Edward Glaeser, Elon Musk, en.wikipedia.org, Erik Brynjolfsson, financial innovation, future of work, gig economy, Gini coefficient, Google Glasses, Gödel, Escher, Bach, income inequality, income per capita, industrial robot, interchangeable parts, invisible hand, Isaac Newton, Jacques de Vaucanson, James Hargreaves, job automation, John Markoff, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, John von Neumann, Joi Ito, Joseph Schumpeter, Kenneth Arrow, Khan Academy, Kickstarter, low skilled workers, lump of labour, Marc Andreessen, Mark Zuckerberg, means of production, Metcalfe’s law, natural language processing, Network effects, Occupy movement, offshore financial centre, Paul Samuelson, Peter Thiel, pink-collar, precariat, purchasing power parity, Ray Kurzweil, ride hailing / ride sharing, road to serfdom, Robert Gordon, Sam Altman, Second Machine Age, self-driving car, shareholder value, sharing economy, Silicon Valley, Snapchat, social intelligence, software is eating the world, sovereign wealth fund, spinning jenny, Stephen Hawking, Steve Jobs, strong AI, telemarketer, The Future of Employment, The Rise and Fall of American Growth, the scientific method, The Wealth of Nations by Adam Smith, Thorstein Veblen, Travis Kalanick, Turing test, Tyler Cowen: Great Stagnation, universal basic income, upwardly mobile, Watson beat the top human players on Jeopardy!, We are the 99%, wealth creators, working poor, working-age population, Y Combinator
The trouble, though, is that these boundaries are unclear and continuously changing. Scores of recent books, articles, reviews, and reports have sought to work out the new limits of machine capabilities, using a variety of different approaches. One is to try to identify which particular human faculties are hard to automate. A popular finding, for instance, is that new technologies struggle to perform tasks that require social intelligence: activities that require face-to-face interaction or empathetic support. From 1980 to 2012, jobs that require a high level of human interaction grew by 12 percent as a share of the US workforce.1 A 2014 Pew Research Center survey found that many experts still believed—despite all the advances of the pragmatist revolution—that there are certain “uniquely human characteristics such as empathy, creativity, judgement, or critical thinking” that will “never” be automated.2 A different tack, rather than looking at human faculties and asking whether they can be replicated by a machine, is to consider the tasks themselves and ask whether they have features that make them easier or harder for a machine to handle.
See also Soviet Union Saez, Emmanuel Sam100 (bricklaying robot) Sandel, Michael sat-nav systems Schloss, David Schmidt, Eric Schumpeter, Joseph Searle, John secondary education security Sedol, Lee self-regulation self-service culture service sector sexuality Shannon, Claude signaling Silicon Valley Simon, Herbert singularity Siri skepticism skill skill-biased work story skill premium skills mismatch skin cancer detection Smith, Adam SNAP. See Supplemental Nutrition Assistance Program social credit system Social Insurance and Allied Services (Beveridge) social intelligence socialist states social justice social media. See also specific companies social robotics social safety nets Socratic software South Korea sovereign wealth funds Soviet Union. See also Russia Sparta Spence, Michael spinning jenny Spotify Standard Oil Company state. See Big State; government state bonus status steam engine Stiglitz, Joseph stock plans structural technological unemployment complementing force weakening and lump of labor fallacy and overview of remaining tasks and superiority assumption and timing of world with less work and substituting force ALM hypothesis and complementing force and defined education and frictional technological unemployment and misplaced anxiety and strengthening of task encroachment and Summers, Larry superintelligence superiority assumption supermanagers superstar firms Supplemental Nutrition Assistance Program (SNAP) supply, price and Supreme Court decision prediction Susskind, Jamie Susskind, Richard Suzman, James synthetic media tacit knowledge Tantalus task complexity task encroachment affective capabilities and cognitive capabilities and manual capabilities and overview of regional differences in skepticism and weakening complementing force and tasks, jobs vs.
Robot Futures by Illah Reza Nourbakhsh
3D printing, autonomous vehicles, Burning Man, commoditize, computer vision, Mars Rover, Menlo Park, phenotype, Skype, social intelligence, software as a service, stealth mode startup, strong AI, telepresence, telepresence robot, Therac-25, Turing test, Vernor Vinge
The fans know an extraordinary amount about the star, but the star knows essentially nothing about each fan. There is no sense of parity or reciprocity in the relationship; 44 Chapter 2 rather, there is a strangely one-sided conversation that does not feel mutually satisfying. The final word on connectivity is that robots, even social ones, will be unlike people. To think, therefore, that we will interact with socially intelligent robots the way we do with people is utterly naïve. There is no real precedent for how this will work, and the only prediction I can make with confidence is that the robots you meet on the street in 2035 will know much more about you than you will know about them. If you are an unyielding optimist, you could interpret this to mean that robots will treat you as if you are a movie star. Primer 6: Control The stereotypical view of robot control is that there are two distinct modes: robots controlled by people, often called teleoperated robots, and robots that are under their own control using local sensors to decide how to move and behave, autonomous robots.
Why We Drive: Toward a Philosophy of the Open Road by Matthew B. Crawford
1960s counterculture, Airbus A320, airport security, augmented reality, autonomous vehicles, Bernie Sanders, Boeing 737 MAX, British Empire, Burning Man, call centre, collective bargaining, crony capitalism, deskilling, digital map, don't be evil, Donald Trump, Elon Musk, en.wikipedia.org, Fellow of the Royal Society, gig economy, Google Earth, hive mind, income inequality, informal economy, Internet of things, Jane Jacobs, labour mobility, Lyft, Network effects, New Journalism, New Urbanism, Nicholas Carr, Ponzi scheme, Ralph Nader, ride hailing / ride sharing, Ronald Reagan, Sam Peltzman, security theater, self-driving car, sharing economy, Shoshana Zuboff, Silicon Valley, smart cities, social graph, social intelligence, Stephen Hawking, technoutopianism, the built environment, The Death and Life of Great American Cities, the High Line, too big to fail, traffic fines, Travis Kalanick, Uber and Lyft, Uber for X, uber lyft, Unsafe at Any Speed, urban planning, Wall-E, Works Progress Administration
But the built environment of technology and cultural practices can likewise be rich enough that it demands the use of our full repertoire of intelligence. Flourishing—that of rats and humans alike—seems to require an environment with “open problem spaces” that elicit the kinds of bodily and mental engagement bequeathed us by evolution and cultural development. These exquisitely honed human capacities include the glorious, century-long development of the automobile, that astonishing tool, and the social intelligence that we have brought to bear on the problem of sharing the road together. If instead we put ourselves in a Plexiglas enclosure in which all our most basic needs are met, we will have nobody but ourselves to blame if we begin to feel like standard lab rats in a massive laboratory of social engineering. We would be safer that way, no doubt. But remember, all rats die. Not every rat lives. Old Cars A Thorn in the Side of the Future Once, in the grassy parking area of Virginia International Raceway, I spotted what appeared to be an AC Cobra from the mid-1960s.
Of course, what human drivers do is make eye contact in such a situation, or read other cues of social interaction, allowing them to negotiate ambiguous cases of right-of-way and work things out on the fly. Some drivers are more assertive, others more defensive. It is not a stretch to say that there is a kind of body language of driving. This improvisation works just fine, for the most part. But social intelligence is hard to reproduce with machine-executable logic. Therefore, it is concluded, human beings must become more like machines, in order to make the road more hospitable to robots. According to the same Times article, “Dmitri Dolgov, head of software for Google’s Self-Driving Car Project, said that one thing he had learned from the project was that human drivers needed to be ‘less idiotic.’” Such an inference comes easily when you conceive reason as a computer scientist does; as asocial and fundamentally rule-like.
What to Think About Machines That Think: Today's Leading Thinkers on the Age of Machine Intelligence by John Brockman
agricultural Revolution, AI winter, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, algorithmic trading, artificial general intelligence, augmented reality, autonomous vehicles, basic income, bitcoin, blockchain, clean water, cognitive dissonance, Colonization of Mars, complexity theory, computer age, computer vision, constrained optimization, corporate personhood, cosmological principle, cryptocurrency, cuban missile crisis, Danny Hillis, dark matter, discrete time, Douglas Engelbart, Elon Musk, Emanuel Derman, endowment effect, epigenetics, Ernest Rutherford, experimental economics, Flash crash, friendly AI, functional fixedness, global pandemic, Google Glasses, hive mind, income inequality, information trail, Internet of things, invention of writing, iterative process, Jaron Lanier, job automation, Johannes Kepler, John Markoff, John von Neumann, Kevin Kelly, knowledge worker, loose coupling, microbiome, Moneyball by Michael Lewis explains big data, natural language processing, Network effects, Norbert Wiener, pattern recognition, Peter Singer: altruism, phenotype, planetary scale, Ray Kurzweil, recommendation engine, Republic of Letters, RFID, Richard Thaler, Rory Sutherland, Satyajit Das, Search for Extraterrestrial Intelligence, self-driving car, sharing economy, Silicon Valley, Skype, smart contracts, social intelligence, speech recognition, statistical model, stem cell, Stephen Hawking, Steve Jobs, Steven Pinker, Stewart Brand, strong AI, Stuxnet, superintelligent machines, supervolcano, the scientific method, The Wisdom of Crowds, theory of mind, Thorstein Veblen, too big to fail, Turing machine, Turing test, Von Neumann architecture, Watson beat the top human players on Jeopardy!, Y2K
In the same way, a real Turing Test is a broad set of questions probing the main aspects of human thinking. For this reason, my colleagues and I are developing the framework around an open-ended set of Turing+ questions in order to measure scientific progress in the field. The plural “questions” emphasizes the many different intelligent abilities to be characterized and possibly replicated in a machine—basic visual recognition of objects, the identification of faces, the gauging of emotions, social intelligence, language, and much more. The “Turing+” emphasizes that a quantitative model must match human behavior and human physiology—the mind and the brain. The requirements are thus well beyond the original Turing Test; an entire scientific field is needed to make progress on understanding them and developing the related technologies of intelligence. Should we be afraid of machines that think? Since intelligence is a whole set of solutions to independent problems, there’s little reason to fear the sudden appearance of a superhuman machine that thinks, though it’s always better to err on the side of caution.
Observing, for example, how beliefs and desires generate wishes that lead to actions, you begin to gain insight into why you think and act the way you do. So you can explain yourself to yourself and to other people too. But equally important, it means you have a model for explaining other people to yourself. Introspective consciousness has laid the ground for what psychologists call Theory of Mind. With humans, for whom social intelligence is the key to biological survival, the advantages have been huge. With machines, for whom success in social life has not yet become an issue, there has been little if any reason to go that way. However, there’s no question that the time is coming when machines will indeed need to understand other machines’ psychology, so as to be able to work alongside them. What’s more, if they’re to collaborate effectively with humans, they’ll need to understand human psychology too.
The Science of Fear: How the Culture of Fear Manipulates Your Brain by Daniel Gardner
Atul Gawande, availability heuristic, Black Swan, Cass Sunstein, citizen journalism, cognitive bias, cognitive dissonance, Columbine, correlation does not imply causation, Daniel Kahneman / Amos Tversky, David Brooks, Doomsday Clock, feminist movement, haute couture, hindsight bias, illegal immigration, Intergovernmental Panel on Climate Change (IPCC), lateral thinking, mandatory minimum, medical residency, Mikhail Gorbachev, millennium bug, moral panic, mutually assured destruction, nuclear winter, placebo effect, Ralph Nader, RAND corporation, Ronald Reagan, social intelligence, Stephen Hawking, Steven Levy, Steven Pinker, the scientific method, Tunguska event, uranium enrichment, Y2K, young professional
In every case, the students said the average student is quite susceptible, but they are much less so. The researchers got the same results when they ran a version of the test in the San Francisco International airport. In more elaborate experiments, Pronin, Lin, and Ross sat people down in pairs and had them take what they said was a “social intelligence” test. The test was bogus. One of the two test-takers—chosen randomly—was given a high score. The other was given a low score. Then they were asked whether they thought the test was an accurate measure of social intelligence. In most cases, the person who got the high score said it was, while the poor guy who got the low score insisted it was not. That’s a standard bias at work—psychologists call it the “self-serving bias.” But then things got interesting. The researchers explained what the “self-serving bias” is and then they asked whether that bias might have had any influence on their judgment.
The Righteous Mind: Why Good People Are Divided by Politics and Religion by Jonathan Haidt
affirmative action, Black Swan, cognitive bias, illegal immigration, impulse control, income inequality, index card, invisible hand, lateral thinking, meta analysis, meta-analysis, Monkeys Reject Unequal Pay, Necker cube, Nelson Mandela, out of africa, Peter Singer: altruism, phenotype, Ralph Waldo Emerson, Richard Thaler, Ronald Reagan, social intelligence, social web, stem cell, Steven Pinker, The Spirit Level, theory of mind, Thomas Malthus, Tony Hsieh, ultimatum game
In the last ten years, however, evolutionary theorists have realized that reciprocal altruism is not so easy to find among nonhuman species.40 The widely reported claim that vampire bats share blood meals with other bats who had previously shared with them turned out to be a case of kin selection (relatives sharing blood), not reciprocal altruism.41 The evidence for reciprocity in chimpanzees and capuchins is better but still ambiguous.42 It seems to take more than just a high level of social intelligence to get reciprocal altruism going. It takes the sort of gossiping, punitive, moralistic community that emerged only when language and weaponry made it possible for early humans to take down bullies and then keep them down with a shared moral matrix.43 Reciprocal altruism also fails to explain why people cooperate in group activities. Reciprocity works great for pairs of people, who can play tit for tat, but in groups it’s usually not in an individual’s self-interest to be the enforcer—the one who punishes slackers.
In factor and cluster analyses of our data at YourMorals.org, we repeatedly find that questions about equality go with questions about care, harm, and compassion (the Care foundation), not with questions about proportionality. 50. See the large body of research in social psychology called “equity theory,” whose central axiom is that the ratio of net gains (outcome minus inputs) to inputs must be equal for all participants (Walster, Walster, and Berscheid 1978). That’s a definition of proportionality. 51. Children generally like equality, until they near puberty, but as their social intelligence matures they stop being rigid egalitarians and start becoming proportionalists; see Almas et al. 2010. 52. Cosmides and Tooby 2005. 53. Our goal with Moral Foundations Theory and YourMorals.org has been to find the best bridges between anthropology and evolutionary psychology, not the complete set of bridges. We think the six we have identified are the most important ones, and we find that we can explain most moral and political controversies using these six.
Autonomia: Post-Political Politics 2007 by Sylvere Lotringer, Christian Marazzi
anti-communist, anti-work, business cycle, collective bargaining, dematerialisation, do-ocracy, feminist movement, full employment, land reform, late capitalism, means of production, social intelligence, wages for housework, women in the workforce
The industry involved in the transmis· sian and elaboration of signs is ranked third in the world on the basis of sales. Consider a hypothesis: the diffusion of the sign as the general equivalent of all things and the transfer of the productive Intelligence to machines may Involve some radlcallnnovatlons In the social forms of language and thought and in the forms of legal and juridical control. Consider this further hypothesis: the creation of a social intelligence which has been rendered useless and polyvalent may have given rise to the SOcial possibility of simulation or, better, to the production of signs beyond the laws governing property and the forms of contra! incarnated In signs. Maurizio Torealta We are convinced that this entire situation is connected with the development of the unforeseen, absurd and paradoxical behavior that Is improperly ca!
"All work for tess [time)" became the watchword for this wave of struggle of young proletarians-a group heterogeneous from the point of view of productivity, but homogeneous from the point of view of culture. "Ali work for less" Is a watchword Which has nothing to do with questions such as "the right to a jab", or the right to a full-time posl.tion. Work Is necessary evll-or at least remains so for a historical period that we wish eventually to surpass and extinguish with collecUve force. What we want is to apply, totally and coherently, the energies and the potentia! that exist for a socialized Intelligence, for a general intellect. We want to make possible a general reduc- tion In working time and we want to transform the organization of work In such a way that an autonomous organization of sectors of productive experimental organization may become possible. These sectors would give rise to experimental forms of production in which the object of worker cooperation would not be profit, but the reduction of necessary work, the intelligent application of technical and scientific knowledge, and Innovation.
Merchants of Truth: The Business of News and the Fight for Facts by Jill Abramson
23andMe, 4chan, Affordable Care Act / Obamacare, Alexander Shulgin, Apple's 1984 Super Bowl advert, barriers to entry, Bernie Madoff, Bernie Sanders, Charles Lindbergh, Chelsea Manning, citizen journalism, cloud computing, commoditize, corporate governance, creative destruction, crowdsourcing, death of newspapers, digital twin, diversified portfolio, Donald Trump, East Village, Edward Snowden, Ferguson, Missouri, Filter Bubble, future of journalism, glass ceiling, Google Glasses, haute couture, hive mind, income inequality, information asymmetry, invisible hand, Jeff Bezos, Joseph Schumpeter, Khyber Pass, late capitalism, Marc Andreessen, Mark Zuckerberg, move fast and break things, move fast and break things, Nate Silver, new economy, obamacare, Occupy movement, performance metric, Peter Thiel, phenotype, pre–internet, race to the bottom, recommendation engine, Robert Mercer, Ronald Reagan, Saturday Night Live, self-driving car, sentiment analysis, Silicon Valley, Silicon Valley ideology, Silicon Valley startup, skunkworks, Snapchat, social intelligence, social web, Steve Jobs, Steven Levy, technoutopianism, telemarketer, the scientific method, The Wisdom of Crowds, Tim Cook: Apple, too big to fail, WikiLeaks
As they cast about frantically for someone fluent in the language of this kind of data, Peretti came knocking to offer them a deal that just might solve their problems. He invited the publishers to join a coalition he was assembling, called the BuzzFeed Partner Network. Joining meant the publishers agreed to let Peretti survey the reader traffic on their sites. In return for these jewels, they would be privy to the coveted Social Intelligence Report that BuzzFeed compiled. This, the publishers figured, would entitle them to the benefits of Peretti’s industry-leading aptitude at virtually no cost. They enthusiastically signed on the dotted line and welcomed the wizard of BuzzFeed to step behind their curtains and observe. Unaware of the precious intelligence they were forking over, or too charmed by Peretti’s acumen to resist, the publishers consented in staggering numbers.
., 22, 287, 289, 306, 378, 387, 389 Trump campaign and, 289, 298 Baquet, Dean, 199, 211, 371, 402, 412, 421 and Abramson’s job offer to Gibson, 220–21 Abramson’s relationship with, 200, 215, 216, 220–21 China princelings story and, 207 Clinton investigation story and, 380–81 as contender for executive editor position, 195, 198, 199–200 in decision to hold off on Trump-Russia story, 383–85 named Times executive editor, 221 native advertising issue and, 215 personality of, 200–201 as Times managing editor, 201, 203 on Times’s mistakes in 2016 coverage, 375–76 use of “lie” in Trump stories approved by, 391 on use of Wikileaks documents, 381–82 White House team increased by, 390 Barbaro, Michael, 370–74, 375 Barboza, David, 205–6, 211 Barboza, Lynn, 206 Barghouty, Phoebe, 362, 363 Baron, Marty, 265, 266, 268, 308, 309, 377, 404, 407, 412 Abramson’s relationship with, 201 as Boston Globe editor, 198, 407 and Catholic pedophiles exposé, 255, 408 as contender for executive editor position, 195, 198, 199, 200 Freedom of the Press Award won by, 421 investigative reporting championed by, 408 named Post executive editor, 255 Post’s Trump investigations pushed by, 407–8 Prakash’s relationship with, 266 Snowden leak and, 260 Barrack, Tom, 316 Barron, Christopher, 345 Barstow, David, 205 Bartosevich, Cat, 332 BBC, Savile scandal at, 214 Becker, Jo, 233, 379 Bee, Samantha, 79 Behar, Joy, 288 Being Digital (Negroponte), 16 Being John Malkovich (film), 50, 51 Bell, Melissa, 241, 248, 249, 266 Post joined by, 237–38 Vox founded by, 239, 248 Bennett, Phil, 229 Bensinger, Ken, 143, 323 Berke, Richard, 201, 372 Berkshire Hathaway, 83 Bernstein, Carl, 225, 408, 409 Bernstein, Joseph, 299 Bethesda Softworks, 166 Bezos, Jeff, 404 building scale as goal of, 412 decline in print circulation seen as inevitable by, 267 as First Amendment defender, 257–58, 420–21 Fox News attacks on, 420 hands-off approach to news coverage adopted by, 418 libertarianism of, 258 national and international coverage expanded by, 263, 264 Post bought by, 1–2, 5, 257–61 Post’s local strategy abandoned by, 406 Post’s technology as focus of, 266, 411–13 and revitalization of news staff, 406, 407 Trump’s attacks on, 418–19, 426 wealth of, 259 Weymouth fired as Post’s editor by, 263 Woodward’s “14 points” memo to, 262–63 Bharat, Krishna, 28 Bianchi, Adam, 333 Biden, Jill, 39 Bieber, Justin, 55 Big Brother, 51 birther movement, 309 Black Lips, 155 Black Lives Matter, 111, 342 Blackpeopleloveus.com, 17, 19 Blaine, Kyle, 314, 315, 317 Blair, Jayson, 3, 67, 78, 79, 184, 385 Blake, Heidi, 345 BlogPOST, 248 blogs, bloggers, 72 growing influence of, 22–23, 94 print reporters’ disdain for, 238 Bloomberg Businessweek, 207, 350 Blue Origin, 258 Boehner, John, 352 “Bored at Work Network,” 18, 32, 37 Boston Globe, 4, 71, 81, 259 Baron as editor of, 198, 407 Catholic pedophilia exposé of, 255, 408 investigative reporting at, 408 Times’s purchase of, 65, 66 Times’s sale of, 219, 259 Boston Marathon bombing, 212 Bourdain, Anthony, 152 Boustany, Nora, 230 Boyd, Gerald, 78, 184, 199 Bradlee, Ben, 82, 84, 228, 262, 265, 268, 408 Bradley, David, 251 Brauchli, Marcus, 238 in exit from Wall Street Journal, 229 fusing of digital and print operations by, 232, 242 Hills’s conflict with, 254–55 increasing isolation of, 251 named Post executive editor, 228–29 Narisetti’s metrics focus defended by, 243 replaced as Post editor, 255 revenue-generating projects pushed by, 250 “Salongate” and, 240–41 Breitbart, Andrew, 21, 22, 290 background of, 283–84 Bannon and, 285, 287 death of, 288 Drudge Report and, 284, 285 Huffington Post cofounded by, 285 mainstream media viewed as enemy by, 285–86 and “making a thing a thing,” 287 on Trump’s entertainment value, 288 Breitbart News, 22, 289–90, 387 Bannon as head of, 289, 306 as epicenter of right-wing media, 290 exponential growth of, 283 fake ACORN videos on, 286–87 as platform for alt-right, 286 psychographics and, 286 in war with BuzzFeed, 306–7 Weinergate story of, 287 Brexit, 279 Brock, Greg, 401 Broder, David, 230, 376 Brown, Campbell, 428 Buchanan, Pat, 50 Buffett, Warren, 83, 88, 97, 257, 430 Bumiller, Elisabeth, 378 Burton, Summer Anne, 119 Bush (GW) administration: deregulation of for-profit schools under, 90–91 in lead-up to Iraq War, 78–79, 92, 95 Business Insider, 182, 312 BuzzBot, 34 BuzzFeed, 8, 16, 37, 47, 56, 142, 197, 219, 224, 242, 243, 265, 273, 280, 300, 329 on Abramson firing, 223 aliases used by staff of, 39 Ben Smith and, see Smith, Ben blue-black/white-gold dress story of, 145–46, 309 blurring of line between news and advertising at, 343 celebrity stories as mainstay of, 35, 39, 111 clickbait on, 139, 267 community-specific Facebook pages of, 337–38 data mining by, 109–10, 112–13, 330 “Dear Kitten” ad of, 122–23 distinction between ads and news stories as irrelevant to, 121–22, 144 early hires at, 36–39 early vulgarity of, 39 emotional charge of stories emphasized by, 111 ethical standards adopted by, 139 Facebook’s importance to, 103, 104, 107–108, 109, 132, 153, 202, 272, 276, 277, 280, 281, 295, 301, 302, 311, 329, 428 financial problems of, 301, 328, 336, 342, 343, 365 fundraising rounds by, 39–40, 103, 120, 129–30, 301, 328 growth of, 123 lawsuits against, 326, 327–28, 427 likability as primary criterion for, 35, 108–9, 121 “list” posts of, 117–18 machine learning and, 34–35, 109, 330–31 and “making a thing a thing,” 120, 287 mass deletions of posts from, 138–39, 164, 310 metrics software of, 113, 116, 144, 330–31 mixing of buzz and news at, 144–45 in move from aggregation to original reporting, 123–25 native advertising program of, 40–41, 120–23, 136–37, 337, 343 new business model of, 160 Nguyen hired by, 113 “No Haters” worldview of, 108–9 nostalgic posts on, 118 Obama native advertising campaign of, 136–37 Peretti’s initial concept for, 33–34 in pivot to video, 332, 336 plagiarized posts at, 138 preservation of informed public as new goal of, 139–40 quality news and, 10 quizzes as mainstay of, 119–20 reaction buttons introduced by, 302–3 “Red, White & Blacklisted” party of, 315–16 relatability as watchword of, 15–16 revenue growth at, 135 shareable content as goal of, 139, 246, 330 Silverman hired by, 311 Social Intelligence Report of, 110–11 Steele dossier published by, 323–24 steep learning curve of, 5 Stopera and, see Stopera, Matt super-sharers and, 111–12 as tastemaker, 120, 125 traditional news media and, 2, 4, 6, 275–76 traffic goals of, 117 Trump’s 2014 interview with, 305–6 2012 convention party hosted by, 135–36 valuation of, 365 verticals of, 123, 132 virality as organizing logic of, 35–36, 111–12, 113–19 Watts and, 35 BuzzFeed Brews, 137–38 BuzzFeed Motion Pictures, 301, 328–29, 334, 335 blurring of line between news and advertising at, 332 Facebook Ops department of, 335 Frank as head of, 331–32, 333–34, 336–37 BuzzFeed News: added to Facebook list of trusted sources, 317 Ben Smith hired as head of, 127–28 Ben Smith’s assembling of team for, 128–29, 130–31 Ben Smith’s expansion of, 141–43 as blindsided by Trump win, 321 Breitbart News war with, 306–7 buzz and, 144–45 Clinton campaign covered by, 318–19 cuts to, 336 expanded staff of, 301 expansion of “hard news” stories of, 140 Facebook “sentiment data” used by, 303–4 gender politics stories featured at, 140 Gibson and, 301 Heat Map of, 144 internet savvy of staff at, 143 investigative reporting by, 141, 301, 302, 345 as loss leader, 317 opinion pieces on, 342–43, 344–45 political reporters at, 305, 313 run-and-gun reporting style of, 133–34 Super Tuesday live stream of, 314–15 Times’s convention coverage collaboration with, 135–36 Trump campaign covered by, 302, 305–6, 313–14, 427 TV-style content added by, 301 Twitter morning show of, 343, 345 2012 election coverage of, 128–29, 131–33 2016 election coverage of, 138, 320 verticals of, 342–43 as wire service for social web, 134 BuzzFeed Partner Network, 110–11 Caliphate, The (podcast), 425 Callimachi, Rukmini, 425 Cambridge Analytica, 279, 298, 307, 400 Cantwell, Christopher, 354 “Capitalism and Schizophrenia” (Peretti), 15 Carleton University, 42, 44 Carr, David, 169–70, 183, 214, 224 Carroll, John S., 71–72, 199 Carroll, Wallace, 71 cats, internet and, 36 CBS News, 3–4, 60 Center for Investigative Reporting, 236 Cernovich, Mike, 283, 299, 324, 338 Chandler family, 225, 226 Charleston Gazette-Mail, 8 Charlottesville, Va., white nationalist rally in, 353–55 “Charlottesville: Race and Terror” (documentary), 354–55 Chartbeat, 243–47, 262, 266 Chasing Hillary (Chozick), 381 Chattanooga Times, 65 Chen, Steve, 53 Chozick, Amy, 318–19, 371, 381 Christmas in Darfur (documentary), 356 Chunn, Nancy, 78 Cillizza, Chris, 239, 266, 411, 4054 citizen journalists, 72 classified advertising: decline of, 26, 67, 89 Post’s reliance on, 26, 83, 89 Clayton, Tracy, 320 clickbait headlines, 280, 413, 414–16 BuzzFeed’s use of, 139, 267 Chartbeat and, 244 Post’s use of, 228, 267–68, 280, 406, 414–16 Times’s avoidance of, 74, 218 Clinton, Bill, Lewinsky scandal and, 239, 284 Clinton, Hillary, 132 Abramson and, 377–78 private email server used by, 178, 379–80 Times mistrusted by, 377–78 Clinton, Hillary, in 2016 election campaign, 287, 290, 299, 300, 315, 318, 322 Election Night and, 371 email investigation and, 377 Times’s coverage of, 378–79 Clinton Cash (Schweizer), 378–79 Clinton Foundation, 378 CNBC, 375 CNN, 54, 55, 60, 385–86, 411 travelogues of, 152 Trump’s attacks on, 325 Vice’s targeting of, 346, 348, 369 cognitive biases, 309–10 Cohen, Michael, 327 Cohn, Nate, 370 Coleman, Greg, 122 Coll, Steve, 86–87, 88, 90 Collectively, 165 Columbia Journalism Review, 290, 381, 389, 394 Columbia Record, 234 Comedy Central, 120 Comey, James, 377, 384, 392 Committee to Protect Journalists, 421 Confessore, Nick, 372, 374 Conrad, Deborah, 178 conspiracy theories: Facebook and, 296 internet and, 283 contagious media, 18, 30, 285 see also virality Contagious Media LLC, 33 Conway, Kellyanne, 339 Cook, Tim, 213 Cooper, Anderson, 315, 428 Cooper, Frank, 336, 337 Coppins, McKay, 130, 132, 305–7, 313 Coppola, Sofia, 51 Costa, Robert, 406, 407 Couric, Katie, 17 Cox, Chris, 32, 277 Craigslist, 26, 68, 86, 89 Cramer, Richard Ben, 130, 318, 322 Cramer, Ruby, 130, 313, 318–21, 322 Creators Project, 162–63 Creighton, Andrew, 364–65 CrowdTangle, 295, 304, 340 Cruz, Ted, 138 Daily (podcast), 373 Daily Beast, 362, 364 Daily Mail, 429 Daily Show, 79 Daily Wire, 429 Dairieh, Medyan, 174–75 data journalism, 290 data mining: as accepted part of online world, 271 BuzzFeed’s reliance on, 109–10, 112–13, 330 by Facebook, 271, 274, 278, 341 David, Laurie, 21 Davis, Charles, 164 Dawkins, Richard, 17 DealBook, 189–90, 375 “Dear Kitten” (Purina ad), 122–23 Death of Cool, The (McInnes), 369 Democratic National Committee, leaked documents of, 381–82 Democratic Party, hacked emails of, 319 Denton, Nick, 246–47 Denver Guardian, 300 Denver Post, 423–24 DeploraBall, 338 DeVigal, Andrew, 197 Devil’s Bargain (Green), 285 digital news media: aggregation sites in, 284 emotional resonance as touchstone of, 273, 275–76, 280 Facebook as platform for, 272–73 fact-checking and, 310 iPhone’s impact on, 32–33 low wages paid by, 175 news cycle and, see news cycle, speeding up of pivot to video of, 328–29, 347 print reporters’ disdain for, 238 pro-Trump wing of, 338–39 “social news” prioritized by, 275 targeting of readers by, 279–80, 281 traditional news media challenged by, 2, 4, 5, 6 vague job titles in, 239, 249 see also BuzzFeed; Vice Media Dillon, Robbie, 47–48 Dish, The (blog), 137 Dog House, 76 Dolnick, Sam, 193, 197, 205, 373, 394–96 Dowd, Maureen, 68, 75, 388, 411 Dow Jones, 67 Downie, Leonard, 7, 84, 89, 93, 98, 228, 229, 262 Drudge, Matt, 21, 30, 73, 239, 284 Drudge Report, 21, 73, 239, 284, 285 Dubuc, Nancy, 369 Duenes, Steve, 204 Duhaime-Ross, Arielle, 351 Dunham, Lena, 224 Dunlap, David, 396–97, 402 “Editing White Female” (Glasser), 223 Elder, Miriam, 141, 143 elections, U.S.: of 2004, 20, 21 of 2008, 98, 99, 126 of 2012, 128–29, 131–33, 135–37 elections, U.S., of 2016, 2 BuzzFeed coverage of, 138, 313–17, 320 divisiveness of, 281 Facebook and, 303 fake news and, 320, 322 Russian interference in, 326, 341–42, 381, 382, 383 see also Clinton, Hillary, in 2016 election campaign; Trump, Donald, in 2016 election campaign Emanuel, Ari, 178 Emergent, 310 Emerson Collective, 343 emotional charge, of news stories, 111 Entous, Adam, 406, 411 Esquire, 268 Eyebeam, 18–19 Facebook, 6, 31–32, 106, 108, 132, 204, 275, 415 accused of liberal bias, 292–93 Audience Optimization Tool of, 282 beginnings of, 95–96 BuzzFeed added to list of trusted sources of, 317 BuzzFeed’s community-specific pages on, 337–38 BuzzFeed’s reliance on, 103, 104, 132, 153, 272, 276, 277, 295, 301, 303–4, 311, 329, 428 Cambridge Analytica and, 279, 298 conspiracy theory stories on, 296 constantly changing algorithms of, 105–6, 271–72, 282, 290–91, 295, 302, 329, 332, 337 criticized for lack of control over content, 154 Custom Audiences tool of, 298 dangerous omnipotence of, 400 Dark Post tool of, 298–99 data mining by, 271, 274, 278, 341 data security issues of, 279, 342, 400 decline of sharing on, 282 demographic of, 106–7 digital advertising dominated by, 7, 27, 254, 367, 397, 404, 428 emotional resonance as touchstone for, 273 expanded reach of publishers’ posts on, 291 explosive growth of, 31, 104 fake news spread by, 277, 289, 295, 296–97, 317, 322, 427–28 growing influence of, 274, 280, 303, 309 human editors controversy at, 291–94, 295–96, 317 Instant Articles on, 267, 280–81, 329–30, 412 Like button of, 107–8, 109 live-video streaming tool of, 314 news content on, 124 in pivot to video, 329, 332 political ads on, 278 political polarization and, 273–74, 279–80, 281, 282–83, 312 Post and, 96–97, 232–33 priority of friends vs. publishers’ posts on, 276, 281–82 psychographics and, 278–79 publishers and, 272–73 ranking of stories on, 275–77 Russian fake news spread by, 289, 341–42, 420 “sentiment data” of, 303–5 “social contagion” experiment of, 303 supposed neutrality of, 274 targeted advertising on, 277–78, 298, 341 Facebook (cont.)
Paul Pioneer Press, 424 Samberg, Andy, 54 Samsung, 393 Sandberg, Sheryl, 213 Sanger, David, 371, 382 Saturday Night Live (TV show), 54 Savile, Jimmy, 214 Scaramucci, Anthony, 385–86 Schafer, Gene, 223 Schmidt, Andrea, 358–59 Schmidt, Eric, 54 Schmidt, Michael, 379–80, 392 Schmitt, Eric, 92 Schoofs, Mark, 141–42, 302, 323, 345 Schreiber, Liev, 268 Schumpeter, Joseph, 153 Schweizer, Peter, 378–79 Scroll, 247 search engine optimization (SEO), 30, 31, 74, 242 Seattle Times, 249 September 11, 2001, terrorist attacks, 27, 49, 172 Sessions, Jeff, 416 Shadid, Anthony, 208–9 Shapiro, Ben, 290 Sheehan, Neil, 402 Shepherd, Jack, 38, 112 Shireman, Robert, 252 Shirky, Clay, 75–76, 193, 196 Shitty Media Men, 361 Shulgin, Alexander, 180–81 Sicardi, Arabelle, 117 Siegal, Al, 152, 189 Silver, Nate, 190, 248, 290, 375 Silverman, Craig: on BuzzFeed dress color story, 309 BuzzFeed joined by, 311 cognitive biases studied by, 309–10 fact-checking business of, 310–11 fake news investigations of, 294–95, 296–98, 299–300, 309, 320, 322, 340–41 as online media watchdog, 310 Simkins, Modjeska, 235 Simpson, Glenn, 323 Slim, Carlos, 5, 9 Times loan of, 188, 430 wealth of, 188, 259 “small world” networks, 15–16 smartphones, impact on digital news of, 32–33, 95 Smith, Ben, 224, 301, 411, 427 background of, 125 and blue-black/white-gold dress story, 146 in BuzzFeed 2016 election night coverage, 320, 321 BuzzFeed news team assembled by, 128–29, 130–31 BuzzFeed opinion pieces and, 345 in debate with Sullivan on native advertising, 137 hired as head of BuzzFeed news department, 127–28 IM interviews conducted by, 135 on impact of Facebook’s “sentiment data,” 304–5 importance of Facebook in 2016 election predicted by, 303, 305 journalism career of, 125–26, 131, 133–34 as master of chasing scoops, 131 NewsFeed podcast of, 342 news team expanded by, 141–43 at Politico, 126, 131, 134 posts critical of BuzzFeed advertisers deleted by, 139 in search for new revenue sources, 344 Steele dossier publication approved by, 323–24, 328 Twitter followers of, 126–27, 130 and use of Facebook “sentiment data,” 304 Smith, Shane, 4, 176 authenticity as prized by, 351 in buyback of Vice, 47 CEO title relinquished by, 369, 426 controversial Liberia documentary of, 169–70 embroidered background story of, 42 and evolution of Vice into serious news brand, 158, 171 extravagant spending by, 175–76 HBO weekly show as priority of, 357 international expansion stressed by, 368 Obama interviewed by, 179, 180 as out of touch with Vice employees’ concerns, 364 overtaking CNN as goal of, 346, 348, 369 sexism of, 59 transformative vision of, 60–61 and Trump’s election, 353 as Vice Media cofounder, 43–44 Vice News as envisioned by, 346, 369 and Vice News Tonight, 353 and Vice’s move into video, 56–57 and Vice’s sexist culture, 363–64 on Vice TV show Emmy nomination, 179 Virtue advertising agency created by, 158 Snapchat, 178, 249, 329, 412 Snowden, Edward, 80 NSA documents leaked by, 80, 215, 259–60, 268, 382 Times mistrusted by, 215 Social Intelligence Report, 110–11 social media, 232 credibility of news services as unimportant on, 294–95 explosion of, 30–32, 103 as news platforms, 294–95 Post content posted by, 412 power of, 5–6 as primary source of news for majority of Americans, 274 Social Network Soiree, 19 Softbank, 103 Sontag, Deborah, 402 Sorkin, Andrew Ross, 375 DealBook and, 189–90 Southern Poverty Law Center, 368 Spayd, Liz, 384, 385 Spencer, Richard, 353 Spicer, Sean, 339 Spotlight (film), 198, 255, 268 Steel, Emily, 362–63 Steele, Christopher, 323, 384 Steele dossier: critiques of BuzzFeed’s publication of, 324–25 lawsuits over, 326, 327–28 unverified claims in, 323 Steiger, Paul, 223, 408 Steiger, Wendy, 223 Steinberg, Jon, 120, 132, 135 Stelter, Brian, 184 “stickiness,” 23, 30, 204 Stopera, Dave, 116 Stopera, Matt, 104, 107, 108, 116, 288 as BuzzFeed early hire, 37–39 and BuzzFeed “List” formula, 117–18 as BuzzFeed’s relatability expert, 115–16 as expert on trend dynamics, 123 gender politics stories emphasized by, 140–41 on importance of adding reporting to BuzzFeed mix, 123–24 and “making a thing a thing,” 287 in move to BuzzFeed newsroom, 128–29 nostalgic posts by, 118 as trend dynamics expert, 123, 144 in 2012 election coverage, 135 Strange Justice (Mayer and Abramson), 196 Sullivan, Andrew, 22, 94, 137 Sullivan, Margaret, 324, 380, 385 Sulzberger, Annie, 65 Sulzberger, Arthur Gregg, 193, 203, 426 Abramson’s relationship with, 395, 396 as candidate for Times publisher position, 65, 394–96 innovation demanded by, 396, 398 named Times editor, 395, 396 reporting career of, 395 “Times Innovation Report” and, 218–20, 394 Times news staff joined by, 197 as Times publisher, 373, 430 on Times’s mistakes in election coverage, 376 Sulzberger, Arthur Ochs, Jr., 1, 5, 9, 407 Abramson fired by, 221–24 Abramson named as executive editor by, 201–2 Abramson’s relationship with, 197–98, 207–8, 216, 402 and blurring of line between news and business departments, 69–70, 189 business-side job cuts by, 191 Chinese princelings story and, 206, 207 Google investment declined by, 97 Keller and, 66, 67–68 lasting achievements of, 427, 429 “last man standing” strategy of, 70–71 liberal views of, 78 news staff cuts and, 70–71, 186, 187, 190–91 premium projects envisioned by, 189 and purchase of Post’s share in International Herald Tribune, 66, 86 retirement party of, 429–30 Robinson fired by, 202–3 shareholder unhappiness with, 63, 74 Times’s future as envisioned by, 62–63 unflattering articles on, 64, 74–75, 79, 183, 187 and Wall Street Journal rivalry, 183 website paywall ordered by, 193–94 Sulzberger, Arthur Ochs, Sr.
Team Human by Douglas Rushkoff
1960s counterculture, autonomous vehicles, basic income, Berlin Wall, big-box store, bitcoin, blockchain, Burning Man, carbon footprint, clean water, clockwork universe, cloud computing, collective bargaining, corporate personhood, disintermediation, Donald Trump, drone strike, European colonialism, Filter Bubble, full employment, future of work, game design, gig economy, Google bus, Gödel, Escher, Bach, Internet of things, invention of the printing press, invention of writing, invisible hand, iterative process, Kevin Kelly, knowledge economy, life extension, lifelogging, Mark Zuckerberg, Marshall McLuhan, means of production, new economy, patient HM, pattern recognition, peer-to-peer, Peter Thiel, Ray Kurzweil, recommendation engine, ride hailing / ride sharing, Ronald Reagan, Ronald Reagan: Tear down this wall, shareholder value, sharing economy, Silicon Valley, social intelligence, sovereign wealth fund, Steve Jobs, Steven Pinker, Stewart Brand, technoutopianism, theory of mind, trade route, Travis Kalanick, Turing test, universal basic income, Vannevar Bush, winner-take-all economy, zero-sum game
Complicated brains make for more complex societies. Think of it this way: a quarterback, point guard, or midfielder, no matter their skills, is only as valuable as their ability to coordinate with the other players; a great athlete is one who can predict the movements of the most players at the same time. Similarly, developing primates were held back less by their size or skills than by their social intelligence. Bigger groups of primates survived better, but required an increase in their ability to remember everyone, manage relationships, and coordinate activities. Developing bigger brains allowed human beings to maintain a whopping 150 stable relationships at a time. The more advanced the primate, the bigger its social groups. That’s the easiest and most accurate way to understand evolution’s trajectory, and the relationship of humans to it.
Physics of the Future: How Science Will Shape Human Destiny and Our Daily Lives by the Year 2100 by Michio Kaku
agricultural Revolution, AI winter, Albert Einstein, Asilomar, 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, Intergovernmental Panel on Climate Change (IPCC), invention of movable type, invention of the telescope, Isaac Newton, John Markoff, John von Neumann, life extension, Louis Pasteur, Mahatma Gandhi, Mars Rover, mass immigration, megacity, Mitch Kapor, Murray Gell-Mann, new economy, oil shale / tar sands, optical character recognition, pattern recognition, planetary scale, postindustrial economy, Ray Kurzweil, refrigerator car, Richard Feynman, Rodney Brooks, Ronald Reagan, Search for Extraterrestrial Intelligence, Silicon Valley, Simon Singh, social intelligence, 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
Rather, these robots are designed from the very beginning to desire to help humans rather than destroy them. They choose to be benevolent. This has given rise to a new field called “social robotics,” which is designed to give robots the qualities that will help them integrate into human society. Scientists at Hanson Robotics, for example, have stated that one mission for their research is to design robots that “will evolve into socially intelligent beings, capable of love and earning a place in the extended human family.” But one problem with all these approaches is that the military is by far the largest funder of AI systems, and these military robots are specifically designed to hunt, track, and kill humans. One can easily imagine future robotic soldiers whose missions are to identify enemy humans and eliminate them with unerring efficiency.
Stanford Conference Ponders a Brave New World with Machines More Powerful Than Their Creators,” San Francisco Chronicle, May 12, 2006, http://articles.sfgate.com/2006–05–12/business/17293318_1_ray-kurzweil-machines-artificial-intelligence. 18 “If you could blow the brain up”: Kurzweil, p. 376. 19 Philosopher David Chalmers has even catalogued: http://consc.net/mindpapers.com. 20 “life may seem pointless if we are fated”: Sheffield, p. 38. 21 “One conversation centered”: Kurzweil, p. 10. 22 “It’s not going to be an invasion”: Abate, San Francisco Chronicle, May 12, 2006. 23 “intelligent design for the IQ 140 people”: Brian O’Keefe, “The Smartest (or the Nuttiest) Futurist on Earth,” Fortune, May 2, 2007, http://money.cnn.com/magazines/fortune/fortune_archive/2007/05/14/100008848/. 24 “It’s as if you took a lot of good food”: Greg Ross, “An Interview with Douglas R. Hofstadter,” American Scientist, January 2007, www.americanscientist.org/bookshelf/pub/douglas-r-hofstadter. 25 “will evolve into socially intelligent beings”: P. W. Singer, “Gaming the Robot Revolution,” Slate, May 21, 2009, www.slate.com/id/2218834/. 26 “When I was a kid”: Rodney A. Brooks, “Making Living Systems,” in John Brockman, ed., Science at the Edge: Conversations with the Leading Scientific Thinkers of Today (New York: Sterling, 2008), p. 250. 27 “My prediction is that by the year 2100”: Rodney A. Brooks, “Flesh and Machines,” in Denning, p. 63. 28 “At Little League games”: Pam Belluck, “Burst of Technology Helps Blind to See,” New York Times, September 27, 2009, p.
From Bacteria to Bach and Back: The Evolution of Minds by Daniel C. Dennett
Ada Lovelace, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, Andrew Wiles, Bayesian statistics, bioinformatics, bitcoin, Build a better mousetrap, Claude Shannon: information theory, computer age, computer vision, double entry bookkeeping, double helix, Douglas Hofstadter, Elon Musk, epigenetics, experimental subject, Fermat's Last Theorem, Gödel, Escher, Bach, information asymmetry, information retrieval, invention of writing, Isaac Newton, iterative process, John von Neumann, Menlo Park, Murray Gell-Mann, Necker cube, Norbert Wiener, pattern recognition, phenotype, Richard Feynman, Rodney Brooks, self-driving car, social intelligence, sorting algorithm, speech recognition, Stephen Hawking, Steven Pinker, strong AI, The Wealth of Nations by Adam Smith, theory of mind, Thomas Bayes, trickle-down economics, Turing machine, Turing test, Watson beat the top human players on Jeopardy!, Y2K
Or perhaps aquatic plants (Wrangham et al. 2009) became a critical “fallback food” during difficult times, promoting wading in ever deeper water, breath holding, and perhaps other physiological revisions. All very controversial and likely to be controversial for some time. In any case, could bipedality and its ensuing suite of enabled competences open the floodgates for language and culture? Another proposed threshold is social intelligence (Jolly 1966; Humphrey 1976): the competence to interpret others as intentional systems whose actions can be anticipated by observing what these others observe and figuring out what they want (food, escape, to predate you, a mating opportunity, to be left alone). This competence is often called TOM (an acronym for theory of mind), which is an ill-chosen term because it invites us to imagine those having this competence as comprehending theoreticians, astute evidence gatherers and hypothesis considerers, instead of flying-by-the-seat-of-their-pants agent anticipators, blessed with an interpretive talent they don’t have to understand at all.
., 108, 113, 130–31 storage of, 108–9 unwanted, 115–16 useful, 117–18, 119–21 “useless,” 118, 126–27 use of term, 107 see also affordances semantic information, extraction of, 3, 74, 85 accumulated knowledge and, 122–23 Bayesian models of, 167–68 brain as organ for, 150–51, 157 evolution and, 118–19 human competences and, 135 see also learning semantic information, transmission of, 106–7, 108–9, 412 beneficiaries in, 117–18 deception in, 127 DNA and, 123–24, 125 language and, 96 light and, 119–20 signal and noise in, 127–28 semantic information, value of: as confirmable but not measurable, 128 legal protection of, 128–34, 136 semantics, children’s acquisition of, 194–95 sense of self: as applied to one’s view of others, 345 in humans, 344 in nonhuman species, 343 see also consciousness serendipity, in software, 47 Seung, Sebastian, 162 sexism, 22, 23–24 sexual selection, 134 Shakespeare, William, 77, 227, 324 Shannon, Claude, 116, 151, 162–63 information theory of, 106, 107–9, 113, 124, 129, 157–58, 411 Shannon information, 5, 108, 109, 111, 117, 129–30, 136, 165 Shazam (app), 185n shell game, 306–7 shibboleth test, 330 Siegel, Lee, 318 signal, information transmission and, 108, 111, 124, 127–28, 136 Simon, Herbert, 153 Sims, Karl, 385 Skinner, B. F., 98 Skinnerian creatures, 98, 99, 100, 151, 331 nuerons as, 165 semantic information acquired by, 119 Skinnerians, 39 “Skinner Skinned” (Dennett), 39 skyhooks, 56, 58, 277, 280, 285n use of term, 54 slime molds, 146–47 Smith, George, 406 Smith, Murray, 249 Smith, Stevie, 117 Snow White and the Seven Dwarfs (film), 381 “Social Gene, The” (Haig), 120n social intelligence, as threshold in cultural evolution, 259–60 social mammals, 251 social norms, 42 reason-giving and, 314, 315 social sciences, memetic theory vs., 242–43 Socrates, 195, 300, 331, 407 software: compiled code for, 66–67 functions vs. mistakes in, 81–82 hierarchical architecture of, 163, 165 legacy code in, 171–72 pseudo-code for, 66, 67 serendipity vs. clobbering in, 47 source code for, 66 Turing’s revolutionary, insight and, 55–56 see also computers, computing software apps, memes compared to, 295, 301–4 “soliloquies,” for animal behavior, 91 Sontag, Susan, 236n Sorceror’s Apprentice, 393 Soul Searching (Humphrey), 369 source code, 66 “spaghetti code,” 83 speciation, 7 species chauvinism, 11, 22 spell-checkers, 403, 405 Sperber, Dan, 220, 225–26, 233, 289, 293n Spiegelman, Sol, 255n spindle cells, 174 Spitsbergen, 44 Sputnik, 217 stages, of words, 187 Sterelny, Kim, 118 stone circles, natural, 44, 45, 46, 46 stotting, 89–90, 289, 292, 295–96, 343, 411 Strawson, Galen, 224 Strawson, Peter F., 288 subjective experience, 349–51 suffering, in nonhuman species, 338, 369 “summer vision project,” 72 supernormal stimuli, 83–84 supply and demand, law of, 307, 310 Sutherland, John, 27–28 sweetness, 355–56 Swiss, Jamy Ian, 319 symbionts, 193n memes as, see memes, as symbionts viruses as, 284–85 symbiosis, 8 symbolists, 384 synanthropy, 122, 197–98, 199 Szilard, Leo, 71 Szostak, Jack, 27–28, 30 talking to oneself, 354 as thinking tool, 296–98, 341, 345–46, 350 see also self-monitoring Talleyrand, Charles-Maurice, 340 technology: growth of, 9 as outgrowth of thinking tools, 3 uncomprehending reliance on, 407–8 technology transfer, 7, 389 teleology: of Aristotle, 33 Cartesian gravity and, 34 Darwin and, 33 Marx on, 33–34 see also reasons termite castles, 51, 59, 340, 409, 410, 411 Test-Operate-Test-Exit (TOTE), 375 texts, transmission errors in, 182 Theaetetus (Plato), 299n theory of mind (TOM), 259, 293 things, words and, 272–74 thinking, “wordless,” 184 thinking tools, 98–99, 152, 171, 302–3, 331, 370, 373, 375, 412 evolution of, 3, 98–99 as human specialty, 3, 54–55, 99, 101, 341 science and technology as outgrowth of, 3 talking to oneself as, 296–98, 341, 345–46, 350 words and, 389 thinkos, 229, 321 third-person point of view, in concept of mind, 366 Thomas, Elizabeth Marshall, 87 Thompson, D’Arcy, 9 Tilghman, Shirley, 43n Tinbergen, Niko, 83 “tip-of-the-tongue” phenomenon, 184–85, 347 TOE (theory of everything), 13 tokens: in culture, 226–27 private vs. public, 185–86, 189–90 spoken vs. silent, 183–86 subpersonal, 347–53 types vs., 182–83, 186–87, 200 Tomasello, Michael, 259–60, 264, 286, 344 Tononi, Giulio, 112n tool making, 258 tools, words as, 292 “toy problems,” 73 trade secrets, 128–29, 136 tradition, artists and, 377 transmission errors, in memes, 234–35 Tree of Life, 323, 379 trees, 336 adaptation in, 121–22 reproduction in, 144–45 semantic information and, 119–20, 121–22 tremes, 237, 392 triggered reproduction, 245–46 trust, 304 cooperation and, 409–10 as cultural phenomenon, 147 Tufts University, 406 Turing, Alan, 70, 72, 77, 116, 151, 152, 162–63, 197, 200, 228, 236, 298, 323, 324, 385 AI and, 56, 72 difference between discoveries of Darwin and, 58–59 inversion of reasoning by, 4, 55–56, 57–58, 68–69, 75, 162, 411 Pilot ACE computer of, 59 Turing-compatibility, 55–56 Turing Test, 365n, 395–96, 403 types, tokens vs., 182–83, 186–87, 200 typos, 321 Uexküll, Jakob von, 78–79 Umwelt, 88, 98–99, 122, 125, 128, 165–66, 194, 336, 356 as things that matter, 366 use of term, 78–79, 80 unconscious processes, 100–101 unconscious selection, 198, 232, 233, 272, 296 understanding, see comprehension universal grammar, 193–94, 275 unlearning, 126 uranium 235, 71 User Illusion, The (Nørretranders), 335n user-illusions, 341, 343 in communication, 344 computer screen as, 202, 346–47 consciousness as, 5, 335n, 346–47, 358, 366, 367, 370, 390–91, 412 utility, natural selection and, 120 variation, in natural selection, 138, 139 Variation of Animals and Plants under Domestication, The, 198 Verstehen (Dilthey), 94 vervet monkey, 265, 289 viruses: deception by, 114–15, 118 memes compared to, 173, 215, 240, 254, 284–85 reproduction of, 254 as symbionts, 284–85 words compared to, 189, 190, 245 vision, neural activity in, 347–53 vitalism, 192 vitamin C, synthesis of, 178 Voltaire, 29 von Economo neurons, 174 Von Neumann, John, 114, 116, 151, 152, 162–63 “von Neumann machines,” 151, 152, 154, 155, 156, 159 Walt Disney Productions, 381 Watson (computer program), 274n, 389–90, 391, 395, 397, 398–99 medical expertise of, 401–2 in TV ads, 393, 395 wealth, 299 Wegner, Daniel, 345, 346 Werner, Brad T., 44, 45, 46, 46 West Side Story (musical), 227–28, 326 Wetware (Bray), 48 “what for” questions, 38–39 evolution of “how come” questions into, 40–41, 48–49, 411 in origins of language, 267–68, 270 What Is Thought?
Catalyst 5.8: The Perl MVC Framework by Antano Solar John, Jonathan Rockway, Solar John Antano
Antano used to run a successful gaming business when gaming as a business was almost unheard of. He has also won the yahoo hack award twice in India consequently, once for developing a Collaborative Browsing Mechanism using lines of code shorter than this biography without any server or proxy and then yet again for developing a Hybrid Search Engine from scratch in 24 hours that uses Machine and Social Intelligence to identify, search, and distill information in contexts you expect! I first like to thank the Catalyst Community without whom this book could have never been possible. I also convey my gratitude to the original author Jonathan, other members of the community like Matt S. Trout, Jess Robinson along with all those who taught me Catalyst! Special appreciation to the reviewer Robert Sedlacek and the Packt team (Leena Purkait , Dhiraj Chandiramani, and Smita Solanki) for continually providing valuable inputs to improve the reading experience.
My Start-Up Life: What A by Ben Casnocha, Marc Benioff
affirmative action, Albert Einstein, barriers to entry, Bonfire of the Vanities, business process, call centre, coherent worldview, creative destruction, David Brooks, don't be evil, fear of failure, hiring and firing, index fund, informal economy, Jeff Bezos, Joan Didion, Lao Tzu, Menlo Park, Paul Graham, place-making, Ralph Waldo Emerson, Sand Hill Road, side project, Silicon Valley, social intelligence, Steve Jobs, Steven Pinker, superconnector, technology bubble, traffic fines, Year of Magical Thinking
Compare these skills to those acquired in a less personal business: remote IT services, manufacturing, or even low-level positions in finance jobs. These kinds of businesses can be successful but may be less rewarding for the entrepreneur in the long term. I have met other young entrepreneurs who are much more successful than I am financially, but unless jealousy is shutting down my mental functions, I don’t think they’ve developed the emotional and social intelligence that will help them in later careers. If you want to start a business, think about judging its worthiness and ultimate success by metrics other than simple financial gain. The experience you gain developing critical life skills should certainly be high on the list. A people-intensive first business can be worth it. financing to acquire other companies. In a fragmented market where several small players are competing for market share, the thinking goes, the winner is the company that can pull off a successful roll-up of all the other companies and become the trusted five-hundred-pound gorilla.
The Emotionally Absent Mother: A Guide to Self-Healing and Getting the Love You Missed by Jasmin Lee Cori Ms, Lpc
Researchers have been studying how the interactions that are the basis of secure attachment affect brain development and functioning.21 The area of the brain most involved in complex social behaviors (so much so that it is sometimes referred to as the social brain) is particularly sensitive to these early interactions. It will sound like an oversimplification, but these caring, attuned interactions actually grow this part of our brains, which is responsible for important social abilities and social intelligence.22 So considering everything from the growth of neurons to one’s sense of self-esteem, the security of our attachment is very important. Some consider this the most critical of all childhood needs. How can I know if I was securely attached to my mother? You won’t know precisely what your relationship with your mother was in your earliest years, but here are some important clues: • moments from your early relationship that were captured in memories • your current feelings about your early relationship with your mother • your patterns in relationships throughout your life and specifically your ability to form strong bonds with others Since this last item is complex, it will take some time to get a clear picture of it.
Working the Phones: Control and Resistance in Call Centres by Jamie Woodcock
always be closing, anti-work, call centre, cognitive dissonance, collective bargaining, David Graeber, invention of the telephone, job satisfaction, late capitalism, means of production, millennium bug, new economy, Panopticon Jeremy Bentham, post-industrial society, post-work, precariat, profit motive, social intelligence, stakhanovite, women in the workforce
These attempts at enthusing workers are ‘novel forms of regulation’ focused ‘on those moments of life that once flourished beyond the remit of the corporation’.25 The challenges of management in the call centre thus feed into the buzz sessions. There is a twofold realisation. First, it is only when ‘workers had checked-out (either literally or mentally) that they begin to feel human again and buzz with life’. Second, ‘that call center work requires high levels of social intelligence, innovation and emotional initiative’. So various attempts emerge that try to ‘find a way of capturing and replicating that buzz of life . . . on the job’.26 This explains examples like this in the call centre: 75 Working the Phones The workers looked at the floor anxiously, feigning smiles but knowing that something pretty awful was about to happen. They were told to form a circle as Carla – the ‘team development leader’ – prepared to deliver a pep-talk, which would have been funny if not for the sadistic glint in her eye.
Architects of Intelligence by Martin Ford
3D printing, agricultural Revolution, AI winter, Apple II, artificial general intelligence, Asilomar, augmented reality, autonomous vehicles, barriers to entry, basic income, Baxter: Rethink Robotics, Bayesian statistics, bitcoin, business intelligence, business process, call centre, cloud computing, cognitive bias, Colonization of Mars, computer vision, correlation does not imply causation, crowdsourcing, DARPA: Urban Challenge, deskilling, disruptive innovation, Donald Trump, Douglas Hofstadter, Elon Musk, Erik Brynjolfsson, Ernest Rutherford, Fellow of the Royal Society, Flash crash, future of work, gig economy, Google X / Alphabet X, Gödel, Escher, Bach, Hans Rosling, ImageNet competition, income inequality, industrial robot, information retrieval, job automation, John von Neumann, Law of Accelerating Returns, life extension, Loebner Prize, Mark Zuckerberg, Mars Rover, means of production, Mitch Kapor, natural language processing, new economy, optical character recognition, pattern recognition, phenotype, Productivity paradox, Ray Kurzweil, recommendation engine, Robert Gordon, Rodney Brooks, Sam Altman, self-driving car, sensor fusion, sentiment analysis, Silicon Valley, smart cities, social intelligence, speech recognition, statistical model, stealth mode startup, stem cell, Stephen Hawking, Steve Jobs, Steve Wozniak, Steven Pinker, strong AI, superintelligent machines, Ted Kaczynski, The Rise and Fall of American Growth, theory of mind, Thomas Bayes, Travis Kalanick, Turing test, universal basic income, Wall-E, Watson beat the top human players on Jeopardy!, women in the workforce, working-age population, zero-sum game, Zipcar
We’re forming these tight relationships with our cars, our phones, and our smart-enabled devices like Amazon’s Alexa or Apple’s Siri. If you think about a lot of people who are building these devices, right now, they’re focused on the cognitive intelligence aspect of these devices, and they’re not paying much attention to the emotional intelligence. But if you look at humans, it’s not just your IQ that matters in how successful you are in your professional and personal life; it’s often really about your emotional and social intelligence. Are you able to understand the mental states of people around you? Are you able to adapt your behavior to take that into consideration and then motivate them to change their behavior, or persuade them to take action? All of these situations, where we are asking people to take action, we all need to be emotionally intelligent to get to that point. I think that this is equally true for technology that is going to be interfacing with you on a day-to-day basis and potentially asking you to do things.
She authored the book Designing Sociable Robots , and she has published over 200 peer-reviewed articles in journals and conferences on the topics of social robotics, human-robot interaction, autonomous robotics, artificial intelligence, and robot learning. She serves on several editorial boards in the areas of autonomous robots, affective computing, entertainment technology and multi-agent systems. She is also an Overseer at the Museum of Science, Boston. Her research focuses on developing the principles, techniques, and technologies for personal robots that are socially intelligent, interact and communicate with people in human-centric terms, work with humans as peers, and learn from people as an apprentice. She has developed some of the world’s most famous robotic creatures, ranging from small hexapod robots, to embedding robotic technologies into familiar everyday artifacts, to creating highly expressive humanoid robots and robot characters. Cynthia is recognized as a prominent global innovator, designer and entrepreneur.
The Life and Death of Ancient Cities: A Natural History by Greg Woolf
agricultural Revolution, capital controls, Columbian Exchange, demographic transition, endogenous growth, Eratosthenes, European colonialism, global village, invention of agriculture, invention of writing, joint-stock company, mass immigration, megacity, New Urbanism, out of africa, Scramble for Africa, social intelligence, social web, trade route, urban planning, urban sprawl
They foraged and fished and hunted, but did not really farm, partly because except in the richest environments they had to keep moving to find food. They cannot have brought with them much more than a few small portable tools. Like all early humans they were knowledgeable about the species they hunted and the plants they ate; they were skilled manipulators of the material world able not just to modify objects into tools but also to construct tools made of several materials combined. Like all humans they had evolved a powerful social intelligence, and had a keen imagination. The first Americans were adaptable too. Their ancestors had survived both the Ice Age that created the land bridge from Asia to Alaska, and the warm periods that followed. As they spread south and east their descendants had had to learn to hunt and fish new species; to survive first in the sub-Arctic, then in the Great Plains; to colonize tropical jungles and the Altiplano of South America; and finally to use and domesticate a range of animals and plants.
In the case of some species the smaller groups are pretty stable; society then becomes a sort of federation of families, or pods. In chimpanzee and human society the smaller groups are not stable in membership. This makes our kind of sociality astonishingly flexible, but it takes a lot more work. Primates spend a lot of time engaged in social grooming: it has even been suggested that human language developed as an extension of that activity. Human social intelligence is far superior to that of even the largest brained of our primate cousins. We can cooperate in large groups to do quite complicated tasks such as planning and organizing a hunt, building a house, or playing football. It is easier enough to teach a chimpanzee to play a game with a ball, but unimaginable that a group of chimpanzees could learn to play team sports. There are other exclusively human dimensions of social life.
The Fix: How Bankers Lied, Cheated and Colluded to Rig the World's Most Important Number (Bloomberg) by Liam Vaughan, Gavin Finch
asset allocation, asset-backed security, bank run, banking crisis, Bernie Sanders, Big bang: deregulation of the City of London, buy low sell high, call centre, central bank independence, collapse of Lehman Brothers, corporate governance, credit crunch, Credit Default Swap, eurozone crisis, fear of failure, financial deregulation, financial innovation, fixed income, interest rate derivative, interest rate swap, Kickstarter, light touch regulation, London Interbank Offered Rate, London Whale, mortgage debt, Northern Rock, performance metric, Ponzi scheme, Ronald Reagan, social intelligence, sovereign wealth fund, urban sprawl
While the heads of the investment bank recognized Hayes’s money-making abilities, Ducrot was making life increasingly uncomfortable for him. The newly promoted manager ordered Hayes to fly to UBS’s headquarters in Zurich to discuss the direction of the business and his future within it. Hayes saw the summons, the first of its kind, as a kick in the teeth and resented having to go. They finally came face to face in a small meeting room away from the trading floor. If Hayes was possessed of more social intelligence he 86 THE FIX may have been able to turn the situation around, but his demeanor was defensive from the start and he begrudged having to explain his worth. Ducrot had been drip-fed reports of Hayes’s antics for years. The meeting was over in minutes; both sides further entrenched in their negative opinions of each other. A few days later, still in Zurich, Hayes was sitting in the seat he’d been allocated with the junior-level rate-setters, when an e-mail from Pieri landed in his inbox.
Rapt: Attention and the Focused Life by Winifred Gallagher
Albert Einstein, Atul Gawande, Build a better mousetrap, Daniel Kahneman / Amos Tversky, David Brooks, delayed gratification, epigenetics, Frank Gehry, fundamental attribution error, Isaac Newton, knowledge worker, longitudinal study, loss aversion, Mahatma Gandhi, McMansion, music of the spheres, Nelson Mandela, Ralph Waldo Emerson, Richard Feynman, Rodney Brooks, Ronald Reagan, Silicon Valley, social intelligence, Walter Mischel, zero-sum game
Brooks, Flesh and Machines: How Robots Will Change Us. New York: Pantheon, 2003. p.82. Intrigued by the “monkey see, monkey do” antics: Marco Iacoboni et al., “Cortical Mechanisms of Human Imitation.” Science 286, 1999; Marco Iacoboni, Mirroring People: The New Science of How We Connect with Others. New York: Farrar, Straus and Giroux, 2008. p.82. Evolution seems to have designed us: Daniel Goleman, Social Intelligence. New York: Bantam, 2007. p.84. Indeed, having social ties is the single best predictor: Ronald Kessler et al., How Healthy Are We? Chicago: University of Chicago Press, 2004. p.85. Research by the Canadian psychologist Joanne Wood shows: J. V. Wood et al., “Downward Comparison in Everyday Life: Reconciling Self-Enhancement Models With the Mood-Cognition Priming Model.” Journal of Personality and Social Psychology 79, 2000.
Dangerous Personalities: An FBI Profiler Shows You How to Identify and Protect Yourself From Harmful People by Joe Navarro, Toni Sciarra Poynter
Goforth, Candace, Erik Ortiz, and Larry McShane. “Kidnap Victims Released from Cleveland Hospital Reunite with Families; 3 Brothers Arrested in Shocking Case.” New York Daily News, May 7, 2013. Accessed November 18, 2013. http://www.nydailynews.com/news/crime/castro-brothers-arrested-connection-missing-cleveland-women-article-1.1337032. Goleman, Daniel. Emotional Intelligence. New York: Bantam Books, 1995. ———. Social Intelligence. New York: Bantam Books, 2006. Graeber, Charles. “The Tainted Kidney.” New York, October 24, 2007. Accessed May 18, 2013. http://nymag.com/news/features/30331/. Greig, Charlotte. Evil Serial Killers: In the Minds of Monsters. New York: Barnes & Noble, 2005. Guinn, Jeff. Manson: The Life and Times of Charles Manson. New York: Simon & Schuster, 2013. Gunderson, John G., and Paul S. Links.
Thinking Machines: The Inside Story of Artificial Intelligence and Our Race to Build the Future by Luke Dormehl
Ada Lovelace, agricultural Revolution, AI winter, Albert Einstein, Alexey Pajitnov wrote Tetris, algorithmic trading, Amazon Mechanical Turk, Apple II, artificial general intelligence, Automated Insights, autonomous vehicles, book scanning, borderless world, call centre, cellular automata, Claude Shannon: information theory, cloud computing, computer vision, correlation does not imply causation, crowdsourcing, drone strike, Elon Musk, Flash crash, friendly AI, game design, global village, Google X / Alphabet X, hive mind, industrial robot, information retrieval, Internet of things, iterative process, Jaron Lanier, John Markoff, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, John von Neumann, Kickstarter, Kodak vs Instagram, Law of Accelerating Returns, life extension, Loebner Prize, Marc Andreessen, Mark Zuckerberg, Menlo Park, natural language processing, Norbert Wiener, out of africa, PageRank, pattern recognition, Ray Kurzweil, recommendation engine, remote working, RFID, self-driving car, Silicon Valley, Skype, smart cities, Smart Cities: Big Data, Civic Hackers, and the Quest for a New Utopia, social intelligence, speech recognition, Stephen Hawking, Steve Jobs, Steve Wozniak, Steven Pinker, strong AI, superintelligent machines, technological singularity, The Coming Technological Singularity, The Future of Employment, Tim Cook: Apple, too big to fail, Turing machine, Turing test, Vernor Vinge, Watson beat the top human players on Jeopardy!
Apple’s expert ‘tastemakers’ include names like popular DJ Zane Lowe, who left his high-paying job at BBC Radio 1 for a starring role in Apple’s new streaming music service. Others include former NWA rapper Dr Dre and pop star Elton John – none of whom are low profile, or (presumably) working for £1 per hour. Depending on how big Apple Music gets, it is astonishing to think that a tech company could wind up being one of the big employers of human DJs on the planet. This new focus on human traits like creativity and social intelligence will only become more important as AI gets smarter. Although Artificial Intelligence is becoming better at communicating in a humanlike way and is proving surprisingly creative in certain applications (as we shall see in the next chapter), these are skills that will remain prized in humans. Observing this transition, Harvard University’s economics professor Lawrence Katz has coined the term ‘artisan economy’.
Empire of Illusion: The End of Literacy and the Triumph of Spectacle by Chris Hedges
Albert Einstein, Ayatollah Khomeini, Cal Newport, clean water, collective bargaining, corporate governance, creative destruction, Credit Default Swap, haute couture, Honoré de Balzac, Howard Zinn, illegal immigration, income inequality, Joseph Schumpeter, Naomi Klein, offshore financial centre, Ralph Nader, Ronald Reagan, single-payer health, social intelligence, statistical model, uranium enrichment
“What we cannot speak about,” Ludwig Wittgenstein warned, “we must pass over in silence.”11 “The existence of multiple forms of intelligence has become a commonplace, but however much elite universities like to sprinkle their incoming classes with a few actors or violinists, they select for and develop one form of intelligence: the analytic,” wrote William Deresiewicz in The American Scholar. Deresiewicz, who taught English at Yale, writes thatwhile this is broadly true of all universities, elite schools, precisely because their students (and faculty, and administrators) possess this one form of intelligence to such a high degree, are more apt to ignore the value of others. One naturally prizes what one most possesses and what most makes for one’s advantages. But social intelligence and emotional intelligence and creative ability, to name just three other forms, are not distributed preferentially among the educational elite.12 Intelligence is morally neutral. It is no more virtuous than athletic prowess. It can be used to further the exploitation of the working class by corporations and the mechanisms of repression and war, or it can be used to fight these forces.
Times Square Red, Times Square Blue by Samuel R. Delany
T H R E E , T W O , O N E , C O N TA C T : T I M E S S Q U A R E R E D What we must recall from our current theory, from our historical practice, is that such institutions and the resultant social contact practices they would develop and contour would no more overturn and rot our society than has alcohol, pop music, the novel, the opera, tobacco, the nightclub, any number of recreational drugs, makeup, men’s clubs, tea-room sex among gay men, universal white male suffrage, lending libraries, comic books, black suffrage, women’s suffrage, Catholicism, legal abortions, Protestantism, public education, Judaism, television, the waltz, coeducation, racial integration, jazz, the pin-up, the pornographic film, body piercing, bundling, taffypulls, tattoos, the fox trot, films, the theater, laws repealing the death penalty, beauty parlors, the university, laws preventing child labor, church marriages for the working classes—or any other social institution that is now, or was once, decried from one podium, pulpit, or another as the End of Civilization as We Know It. Such institutions are always already within the social; indeed they are the social—and are not outside it. That is why they all require social intelligence in their administration. All are always already in tension with other institutions. That is why they all have at one time or another required more or less vigilant protection as a set of freedoms. §10.5. Interclass contact conducted in a mode of good will is the locus of democracy as visible social drama, a drama that must be supported and sustained by political, educational, medical, job, and cultural equality of opportunity if democracy is to mean to most people any more than an annual or quatra-annual visit to a voting booth; if democracy is to animate both infrastructure and superstructure.
Mind Wide Open: Your Brain and the Neuroscience of Everyday Life by Steven Johnson
Columbine, double helix, epigenetics, experimental subject, Gödel, Escher, Bach, James Watt: steam engine, l'esprit de l'escalier, lateral thinking, pattern recognition, phenotype, social intelligence, Steven Pinker, theory of mind, zero-sum game
While autistic people can usually learn and communicate using language, there is something missing in their exchanges with other people, some strange distance in their social demeanor. They seem emotionally remote, disconnected. Many experts now believe that this distance derives from a distinct neurological condition: autistics are mindreading-impaired. The social distance associated with autism is a vivid example of the brain’s modular nature: autistics generally have above-average IQs, and their general logic skills are impeccable. But they lack social intelligence, particularly the ability to make on-the-fly assessments of other people’s inner thoughts. Autistic people do have to go to school to read facial expressions-learning to intuit another person’s mood is at least as challenging for them as learning to read is for the rest of us. When you’re engaged in conversation, you don’t think to yourself, “Aha! His right eyebrow just crinkled up. He must be happy.”
The Happiness Industry: How the Government and Big Business Sold Us Well-Being by William Davies
1960s counterculture, Airbnb, business intelligence, corporate governance, dematerialisation, experimental subject, Exxon Valdez, Frederick Winslow Taylor, Gini coefficient, income inequality, intangible asset, invisible hand, joint-stock company, lifelogging, market bubble, mental accounting, nudge unit, Panopticon Jeremy Bentham, Philip Mirowski, profit maximization, randomized controlled trial, Richard Thaler, road to serfdom, Ronald Coase, Ronald Reagan, science of happiness, selective serotonin reuptake inhibitor (SSRI), sentiment analysis, sharing economy, Slavoj Žižek, smart cities, Smart Cities: Big Data, Civic Hackers, and the Quest for a New Utopia, social intelligence, Social Responsibility of Business Is to Increase Its Profits, Steve Jobs, The Chicago School, The Spirit Level, theory of mind, urban planning, Vilfredo Pareto
Patil, ‘Data Scientist: The Sexiest Job of the 21st Century’, Harvard Business Review, October 2012. 5Viktor Mayer-Schönberger, and Kenneth Cukier, Big Data: A Revolution That Will Transform How We Live, Work and Think, London: John Murray, 2013. 6Anthony Townsend, Smart Cities: Big Data, Civic Hackers, and the Quest for a New Utopia, New York: W. W. Norton & Company, 2013, 297. 7Mark Harrington, ‘How Social Intelligence Is Revolutionizing Market Research’, business2community.com, 20 June 2013. 8‘Carol Matlack, ‘Tesco’s In-Store Ads Watch You – and It Looks Like You Need a Coffee’, businessweek.com, 4 November 2013. 9Mark Bright, ‘Facial Recognition Ads Planned for Manchester Streets’, salfordonline.com, 28 May 2013. 10Rob Matheson, ‘A Market for Emotions’, newsoffice.mit.edu, 31 July 2014. 11James Armstrong, ‘Toronto May Soon Track Residents’ Online Sentiments About City Services’, globalnews.ca, 17 June 2013 ; Sabrina Rodak, ‘Sentiment Analysis: An Emerging Trend That Could Give Hospitals an Edge in Patient Experience’, beckershospitalreview.com, 28 June 2013. 12Dana Liebelson, ‘Meet the Data Brokers Who Help Corporations Sell Your Digital Life’, Mother Jones, November/December 2013. 13Adam Kramer, Jamie Guillory and Jeffrey Hancock, ‘Experimental Evidence of Massive-Scale Emotional Contagion Through Social Networks’, Proceedings of the National Academy of the Sciences 111: 24, 2014. 14Robinson Meyer, ‘Everything We Know About Facebook’s Secret Mood Manipulation Experiment’, theatlantic.com, 28 June 2014. 15Ernesto Ramirez, ‘How to Measure Mood Using Quantified Self Tools’, quantifiedself.com, 17 January 2013. 16Matthew Killingsworth and Daniel Gilbert, ‘A Wandering Mind Is an Unhappy Mind’, Science 330: 6006, 2010. 17Mount Sinai Medical Center, ‘Neuroimaging May Offer New Way to Diagnose Bipolar Disorder’, sciencedaily.com, 5 June, 2013; Lucy McKeon, ‘The Neuroscience of Happiness’, salon.com, 28 January 2012. 18Steve Lohr, ‘Huge New Development Project Becomes a Data Science Lab’, bits.blogs.nytimes.com, 14 April 2014. 19Shiv Malik, ‘Jobseekers Made to Carry Out Bogus Psychometric Tests’, theguardian.com, 30 April 2013. 20Randy Rieland, ‘Think You’re Doing a Good Job?
Devil's Bargain: Steve Bannon, Donald Trump, and the Storming of the Presidency by Joshua Green
4chan, Affordable Care Act / Obamacare, Ayatollah Khomeini, Bernie Sanders, business climate, centre right, Charles Lindbergh, coherent worldview, collateralized debt obligation, conceptual framework, corporate raider, crony capitalism, currency manipulation / currency intervention, Donald Trump, Fractional reserve banking, Goldman Sachs: Vampire Squid, Gordon Gekko, guest worker program, illegal immigration, immigration reform, liberation theology, low skilled workers, Nate Silver, Nelson Mandela, nuclear winter, obamacare, Peace of Westphalia, Peter Thiel, quantitative hedge fund, Renaissance Technologies, Robert Mercer, Ronald Reagan, Silicon Valley, social intelligence, speech recognition, urban planning
Milken, a Jew who wore an ill-fitting toupee, was initially shunned, and later despised, by the old-money firms with their WASP lineage and culture of restraint. But it was Milken who ultimately prevailed by storming their fortresses and upending their businesses. Eventually, they wised up and began doing what Milken had been doing all along: taking big stakes in the companies for themselves. Bannon had the brains and the social intelligence to pass as a Harvard preppy and a Goldman whiz kid, but deep down he identified more with Milken, a swashbuckler and rogue who struck fear in his adversaries. “The strengths that Milken had—the aggressiveness, the creativity, the hard work—those are all traits Steve admires,” said a former Goldman colleague. Whether he recognized it or not, Bannon was better suited to the other side. Later on, when Milken went to prison for insider trading, Bannon did a deal to roll up one of his companies.
Cognitive Gadgets: The Cultural Evolution of Thinking by Cecilia Heyes
Asperger Syndrome, complexity theory, epigenetics, intermodal, longitudinal study, meta analysis, meta-analysis, neurotypical, phenotype, social intelligence, the built environment, theory of mind, twin studies
Second-order conditioning of the pigeon’s keypeck. Learning & Behavior, 5(1), 25–38. Ray, E., and Heyes, C. (2011). Imitation in infancy: The wealth of the stimulus. Developmental Science, 14(1), 92–105. Reader, S. M., Hager, Y., and Laland, K. N. (2011). The evolution of primate general and cultural intelligence. Philosophical Transactions of the Royal Society, Series B, 366, 1017–1027. Reader, S. M., and Laland, K. N. (2002). Social intelligence, innovation, and enhanced brain size in primates. Proceedings of the National Academy of Sciences, 99, 4436–4441. Reeb-Sutherland, B. C., Fifer, W. P., Byrd, D. L., Hammock, E. A., Levitt, P., and Fox, N. A. (2011). One-month-old human infants learn about the social world while they sleep. Developmental Science, 14(5), 1134–1141. Reeb-Sutherland, B. C., Levitt, P., and Fox, N. A. (2012).
Going Dark: The Secret Social Lives of Extremists by Julia Ebner
23andMe, 4chan, Airbnb, anti-communist, anti-globalists, augmented reality, Ayatollah Khomeini, bitcoin, blockchain, Boris Johnson, citizen journalism, cognitive dissonance, crowdsourcing, cryptocurrency, Donald Trump, Elon Musk, feminist movement, game design, glass ceiling, Google Earth, job satisfaction, Mark Zuckerberg, mass immigration, Menlo Park, Mikhail Gorbachev, Network effects, off grid, pattern recognition, pre–internet, QAnon, RAND corporation, ransomware, rising living standards, self-driving car, Silicon Valley, Skype, Snapchat, social intelligence, Steve Jobs, Transnistria, WikiLeaks, zero day
After joining a dozen different extremist groups, I am convinced that any response that focuses purely on technology-led intervention and on regulating the digital sphere will not work. It is true that the way a platform is designed can stimulate, manipulate and escalate our attitudes and behaviour. But compassion and empathy are not predetermined by algorithms. Even if the digital DNA of some platforms carries a dangerous potential to handicap our emotional and social intelligence, we need to move away from the idea that it robs us of our ability to love, hate or fear. If technology is no more than an extension and multiplier of human flaws and qualities, we need to return to a more human-centred approach. Questions around identity, trust and friendship in the online world must be raised if we want to break through the ‘us and them’ thinking that all extremist movements have in common.
Extreme Teams: Why Pixar, Netflix, AirBnB, and Other Cutting-Edge Companies Succeed Where Most Fail by Robert Bruce Shaw, James Foster, Brilliance Audio
Airbnb, augmented reality, call centre, cloud computing, deliberate practice, Elon Musk, future of work, inventory management, Jeff Bezos, job satisfaction, Jony Ive, loose coupling, meta analysis, meta-analysis, nuclear winter, Paul Graham, peer-to-peer, peer-to-peer model, performance metric, Peter Thiel, sharing economy, Silicon Valley, social intelligence, Steve Jobs, Tony Hsieh
We tried to predict which cadets would stay in military training and which would drop out. We went to the National Spelling Bee and tried to predict which children would advance farthest in competition We partnered with private companies, asking, which of these salespeople is going to keep their jobs? And who’s going to earn the most money? In all those very different contexts, one characteristic emerged as a significant predictor of success. And it wasn’t social intelligence. It wasn’t good looks, physical health, and it wasn’t IQ. It was grit.” 41Angela L. Duckworth, Christopher Peterson, Michael D. Matthews, and Dennis R. Kelly, “Grit: Perseverance and Passion for Long-Term Goals,” Journal of Personality and Social Psychology 92 (2007), 1087–101. For a critical view of the grit concept, see David Denby, “The Limits of ‘Grit,’” New Yorker, June 21, 2016. 42Airbnb “Our Commitment to Trust and Safety,” blog.airbnb.com/our-commitment-to-trust-and-safety/. 43Ari Levy, “Airbnb Offers $50,000 Guarantee After User’s Home Is Trashed,” Forbes, August 1, 2011.
The Economics of Belonging: A Radical Plan to Win Back the Left Behind and Achieve Prosperity for All by Martin Sandbu
"Robert Solow", Airbnb, autonomous vehicles, balance sheet recession, bank run, banking crisis, basic income, Berlin Wall, Bernie Sanders, Boris Johnson, Branko Milanovic, Bretton Woods, business cycle, call centre, capital controls, carbon footprint, Carmen Reinhart, centre right, collective bargaining, debt deflation, deindustrialization, deskilling, Diane Coyle, Donald Trump, Edward Glaeser, eurozone crisis, Fall of the Berlin Wall, financial intermediation, full employment, future of work, gig economy, Gini coefficient, hiring and firing, income inequality, income per capita, industrial robot, intangible asset, job automation, John Maynard Keynes: technological unemployment, Kenneth Rogoff, knowledge economy, knowledge worker, labour market flexibility, liquidity trap, longitudinal study, low skilled workers, manufacturing employment, Martin Wolf, meta analysis, meta-analysis, mini-job, mortgage debt, new economy, offshore financial centre, oil shock, open economy, pattern recognition, pink-collar, precariat, quantitative easing, race to the bottom, Richard Florida, Robert Shiller, Robert Shiller, Ronald Reagan, secular stagnation, social intelligence, TaskRabbit, total factor productivity, universal basic income, very high income, winner-take-all economy, working poor
The crumbling foundations of the blue-collar aristocracy are the assembly lines, docks, rigs, and trucks where the men traditionally did most of the work. As such, they are the perfect stage for displays of old-fashioned machismo (Trump’s photo op with an eighteen-wheel truck on the White House lawn comes to mind). That sits less well with the skills that create value in the new service and knowledge economy. Social intelligence, a talent for caring, and similar soft skills are increasingly in demand, as are the jobs that require them: nursing, social care and childcare, teaching, and the like. In the United States, for example, one in four new jobs in the next decade is expected to come in health care, social assistance, and education, and we should expect similar developments elsewhere.19 In many places, however, these jobs come with low status and lower pay.
Thinking in Pictures: And Other Reports From My Life With Autism by Temple Grandin
Albert Einstein, Asperger Syndrome, factory automation, randomized controlled trial, Richard Feynman, selective serotonin reuptake inhibitor (SSRI), social intelligence, source of truth, theory of mind, twin studies
Asperger 1944 Adult Suicide Linked to Popular Antidepressant (Paxil). Nature, 436: 1073. J. Barron, S. Barron 1992 Adult Suicide Linked to Popular Antidepressant (Paxil). Nature, 436: 1073. S. Baron-Cohen, Ring H. A. Bullmore E. T. S. Wheelwright, C. Ashwin, Williams S. C. 2000 The amygdale theory of autism. Neuroscience Biobehavior Review, 24: 355–364. Baron-Cohen, Ring H. A. S. Wheelwright, Bullmore E. T. et al. Brammer M. J. 1999 Social intelligence in the normal and autistic brain: An FMRI study. European Journal of Neuroscience, 11: 1891–1898. S. Baron-Cohen 2004 The cognitive neuroscience of autism. Journal of Neurology, Neurosurgery Psychiatry, 75: 945–948. L. Cesaroni, M. Garber 1991 The cognitive neuroscience of autism. Journal of Neurology, Neurosurgery Psychiatry, 75: 945–948. E. Cutler 2004 A Thorn in My Pocket. Arlington, Texas., Future Horizons U.
Writing on the Wall: Social Media - the First 2,000 Years by Tom Standage
Bill Duvall, British Empire, Edmond Halley, Edward Lloyd's coffeehouse, invention of the printing press, invention of writing, Isaac Newton, knowledge worker, Leonard Kleinrock, Marc Andreessen, Mark Zuckerberg, Menlo Park, Mohammed Bouazizi, New Journalism, packet switching, place-making, Republic of Letters, sexual politics, social intelligence, The Structural Transformation of the Public Sphere, The Wealth of Nations by Adam Smith, theory of mind, yellow journalism
This provides more information on which to base judgments about whether someone is trustworthy or not. And by passing on information selectively it is possible to manipulate one person’s opinion of another. People can also form judgments about someone’s trustworthiness by evaluating the accuracy of the information he or she passes on about others. Gossip is an extraordinarily rich source of social intelligence, both about the person speaking and about whoever is being discussed. And because our brains are wired to process just this kind of information, we find exchanging it extraordinarily compelling. Such chatter benefits both the members of a group and the group as a whole. Individuals can better keep track of shifting alliances within the group, and passing accurate or useful information to others can help establish one’s credibility as an ally or suitability as a mate.
Reskilling America: Learning to Labor in the Twenty-First Century by Katherine S. Newman, Hella Winston
active measures, blue-collar work, business cycle, collective bargaining, Computer Numeric Control, deindustrialization, desegregation, factory automation, interchangeable parts, invisible hand, job-hopping, knowledge economy, longitudinal study, low skilled workers, performance metric, reshoring, Ronald Reagan, Silicon Valley, social intelligence, two tier labour market, union organizing, upwardly mobile, War on Poverty, Wolfgang Streeck, working poor
The fact is, in parts of the United States where young people—high-school students—have had the opportunity to engage in serious, well-designed, and well-implemented training and work, through either youth apprenticeship or high school co-op programs, the benefits can be striking. This is true not just in terms of employment prospects but, as writer, teacher, and education scholar Mike Rose so powerfully demonstrates, of cognitive development, the ability to diagnose, analyze, and solve complex problems, and to operate with social intelligence. But even in places where CTE is embraced, we still need to make sure we are giving both technical and academic teachers in CTE schools the support and the respect they need to do their jobs. We cannot prepare a workforce if the people who do the teaching are at arm’s length from the firms that will employ their students. We should pay teachers to get updated industry experience in the summers, incentivize them to place their students, and provide ongoing support for their connections to the industries they are training people for.
Mindwise: Why We Misunderstand What Others Think, Believe, Feel, and Want by Nicholas Epley
affirmative action, airport security, Amazon Mechanical Turk, Cass Sunstein, crowdsourcing, cuban missile crisis, drone strike, friendly fire, invisible hand, meta analysis, meta-analysis, Milgram experiment, payday loans, Peter Singer: altruism, pirate software, Richard Thaler, school choice, social intelligence, the scientific method, theory of mind
This chapter has detailed how a brain as brilliant and capable as ours can, at times, fail to recognize a mind standing right before our eyes. Our sixth sense, this amazing ability each of us has to understand the mind of another, must be engaged, up close and personal. When distance keeps it disengaged, we may see other human beings as lesser minds and, thereby, as lesser persons. The capacity for mindblindness is not limited to only a select few. Such mistakes can afflict any of us, rendering us less socially intelligent than we could otherwise be. But if failing to engage our ability creates one set of mistakes, then engaging our ability when we should not creates another set, which I’ll describe in the next chapter. In particular, once our sixth sense is engaged, it is all too easy to see other minds almost everywhere we look. Just as we can fail to recognize the mind of a human being standing right before our eyes, we can also recognize a mind where none actually exists. 4 How We Anthropomorphize Give me one minute—just one minute—inside the skin of this creature.
Digital Bank: Strategies for Launching or Becoming a Digital Bank by Chris Skinner
algorithmic trading, AltaVista, Amazon Web Services, Any sufficiently advanced technology is indistinguishable from magic, augmented reality, bank run, Basel III, bitcoin, business cycle, business intelligence, business process, business process outsourcing, buy and hold, call centre, cashless society, clean water, cloud computing, corporate social responsibility, credit crunch, crowdsourcing, cryptocurrency, demand response, disintermediation, don't be evil, en.wikipedia.org, fault tolerance, fiat currency, financial innovation, Google Glasses, high net worth, informal economy, Infrastructure as a Service, Internet of things, Jeff Bezos, Kevin Kelly, Kickstarter, M-Pesa, margin call, mass affluent, MITM: man-in-the-middle, mobile money, Mohammed Bouazizi, new economy, Northern Rock, Occupy movement, Pingit, platform as a service, Ponzi scheme, prediction markets, pre–internet, QR code, quantitative easing, ransomware, reserve currency, RFID, Satoshi Nakamoto, Silicon Valley, smart cities, social intelligence, software as a service, Steve Jobs, strong AI, Stuxnet, trade route, unbanked and underbanked, underbanked, upwardly mobile, We are the 99%, web application, WikiLeaks, Y2K
Many firms believes that having a holding twitter name @MyBank and Facebook page is all you need. Some go as far as to populate their pages with links and news. But you still don’t get it if you think that way as these are platforms, not websites. Facebook and Twitter have hundreds of specialist service providers creating new forms of social engagement from content curation to social marketing management; from social ads to social intelligence; from apps for gaming to apps for sharing to apps for commerce; and more. A good example is Instagram, purchased by Facebook for $1 billion in April 2012. Instagram is a photo sharing social service, and provides an easy way to share such content via Facebook. In other words Facebook, like the internet, is a platform that provides the underpinnings for far more targeted and specialist social connectivity.
The Vanishing Neighbor: The Transformation of American Community by Marc J. Dunkelman
Affordable Care Act / Obamacare, Albert Einstein, assortative mating, Berlin Wall, big-box store, blue-collar work, Bretton Woods, Broken windows theory, business cycle, call centre, clean water, cuban missile crisis, dark matter, David Brooks, delayed gratification, different worldview, double helix, Downton Abbey, Fall of the Berlin Wall, Filter Bubble, Francis Fukuyama: the end of history, George Santayana, Gini coefficient, glass ceiling, global supply chain, global village, helicopter parent, if you build it, they will come, impulse control, income inequality, invention of movable type, Jane Jacobs, Khyber Pass, Louis Pasteur, Marshall McLuhan, McMansion, Nate Silver, obamacare, Occupy movement, Peter Thiel, post-industrial society, Richard Florida, rolodex, Saturday Night Live, Silicon Valley, Skype, social intelligence, Stanford marshmallow experiment, Steve Jobs, telemarketer, The Chicago School, The Death and Life of Great American Cities, the medium is the message, Tyler Cowen: Great Stagnation, urban decay, urban planning, Walter Mischel, War on Poverty, women in the workforce, World Values Survey, zero-sum game
In looking, for example, at which inner-city high-school graduates made it through college and which dropped out, David Levin, one of the founders of the KIPP network of charter schools, noticed: The students who persisted in college were not necessarily the ones who had excelled academically at KIPP; they were the ones with exceptional character strengths, like optimism and persistence and social intelligence. They were the ones who were able to recover from a bad grade and resolve to do better next time; to bounce back from a fight with their parents; to resist the urge to go out to the movies and instead stay home and study instead; to persuade professors to give them extra help after class.20 What Canada, Levin, and other educators have come to focus on is what sort of culture and curriculum can best equip kids with the power of self-discipline.21 What can be done, either at the outset or later in children’s development, to give them the ability to withstand an emotional hijacking?
Mistakes Were Made (But Not by Me): Why We Justify Foolish Beliefs, Bad Decisions, and Hurtful Acts by Carol Tavris, Elliot Aronson
Ayatollah Khomeini, cognitive dissonance, cuban missile crisis, desegregation, Donald Trump, false memory syndrome, fear of failure, Lao Tzu, longitudinal study, medical malpractice, medical residency, meta analysis, meta-analysis, Milgram experiment, moral panic, Nelson Mandela, placebo effect, psychological pricing, Richard Feynman, Ronald Reagan, social intelligence, telemarketer, the scientific method, trade route, transcontinental railway, Watson beat the top human players on Jeopardy!
Psychologist Ervin Staub, himself a Holocaust survivor, has been studying the origins and dynamics of genocide for many years, and most recently has devoted himself to the project of reconciliation between the Tutsi and Hutu in Rwanda. See Ervin Staub and Laurie A. Pearlman (2006), "Advancing Healing and Reconciliation in Rwanda and Other Post-conflict Settings," in L. Barbanel and R. Sternberg (eds.), Psychological Interventions in Times of Crisis, New York: Springer-Verlag; and Daniel Goleman (2006), Social Intelligence, New York: Bantam Books. 25 Broyles told this story in a 1987 PBS documentary, "Faces of the Enemy," based on the book of the same title by Sam Keen. It is still available on VHS and DVD from PBS. CHAPTER 8 Letting Go and Owning Up 1 All quotations are taken from the transcript of Oprah's show, January 26, 2006. 2 "Wayne Hale's Insider's Guide to NASA," by Nell Boyce. NPR Morning Edition, June 30, 2006.
Wired for War: The Robotics Revolution and Conflict in the 21st Century by P. W. Singer
agricultural Revolution, Albert Einstein, Any sufficiently advanced technology is indistinguishable from magic, Atahualpa, barriers to entry, Berlin Wall, Bill Joy: nanobots, blue-collar work, borderless world, Charles Lindbergh, clean water, Craig Reynolds: boids flock, cuban missile crisis, digital map, en.wikipedia.org, Ernest Rutherford, failed state, Fall of the Berlin Wall, Firefox, Francisco Pizarro, Frank Gehry, friendly fire, game design, George Gilder, Google Earth, Grace Hopper, I think there is a world market for maybe five computers, if you build it, they will come, illegal immigration, industrial robot, interchangeable parts, Intergovernmental Panel on Climate Change (IPCC), invention of gunpowder, invention of movable type, invention of the steam engine, Isaac Newton, Jacques de Vaucanson, job automation, Johann Wolfgang von Goethe, Law of Accelerating Returns, Mars Rover, Menlo Park, New Urbanism, pattern recognition, private military company, RAND corporation, Ray Kurzweil, RFID, robot derives from the Czech word robota Czech, meaning slave, Rodney Brooks, Ronald Reagan, Schrödinger's Cat, Silicon Valley, social intelligence, speech recognition, Stephen Hawking, strong AI, technological singularity, The Coming Technological Singularity, The Wisdom of Crowds, Turing test, Vernor Vinge, Wall-E, Yogi Berra
The future military doesn’t just include space for the younger gamers; technology may also help keep the old fogies around a little longer. The prospect of leavening out the young video gamers with an older old guard appeals, especially to the senior set. Retired major general Robert Scales, the former head of the Army War College, writes that older soldiers might actually be better soldiers. “Social intelligence and diplomatic skills increase with age. Older soldiers are more stable in crisis situations, are less likely to be killed or wounded and are far more effective in performing the essential tasks that attend to close-in killing. Experience within special operations units also suggests that more mature soldiers are better suited for fighting in complex human environments.” No one yet has a sense of where exactly this trend will end.
., Religious Perspectives on War: Christian, Muslim, and Jewish Attitudes Toward Force, Perspectives Series (Washington, DC: United States Institute of Peace Press, 2002), 22. 367 “erase the pain given and taken” Macgregor, “Imitation of Life,” 19. 368 “When you have a radical idea” As quoted in Jonathon Keats, “The Idea Man,” Popsci.com, 2004 (cited August 18, 2006); available at http://www.popsci.com/popsci/technology/generaltechnology/6b0898b0c9b84010vgnvcm1000004eecbccdrcrd.html. 368 the Pentagon is now the largest day-care provider Christopher Coker, Humane Warfare (London, New York: Routledge, 2001), 98. 369 “Social intelligence and diplomatic skills” Scales, “Clausewitz and World War IV.” 369 “Sixty is the new forty” Ralph Peters, “The Geezer Brigade: Wartime Needs and Military Retirees,” Armed Forces Journal, July 2007, http://www.armedforcesjournal.com/2007/07/2792594. 369 “the Old Farts” John Scalzi, Old Man’s War, 1st ed. (New York: A Tom Doherty Associates Book, 2005). 369 Our image of a soldier For more on this, see Nancy Sherman, Stoic Warriors: The Ancient Philosophy Behind the Military Mind (New York: Oxford University Press, 2005). 369 “inoperable pilonidal cyst” Michael Arkush, Rush!
GCHQ by Richard Aldrich
belly landing, Berlin Wall, British Empire, colonial exploitation, cuban missile crisis, friendly fire, illegal immigration, index card, lateral thinking, Menlo Park, Mikhail Gorbachev, Neil Kinnock, New Journalism, packet switching, private military company, Robert Hanssen: Double agent, Ronald Reagan, social intelligence, South China Sea, undersea cable, University of East Anglia, Yom Kippur War, Zimmermann PGP
One evening Mrs Molotov complained that her best friend’s son was having difficulty getting a place at Moscow University. ‘Could he ring the rector and arrange it? Rather grudgingly, Molotov consented.’33 One wonders if, at this point, Blake ever paused to reflect that the Soviet Communist system that he admired and the British system were really not so very different. SIS gathered plenty of such ‘social intelligence’, since Blake recalls that during the mid-1950s his unit also bugged Polish diplomatic premises in Brussels, the Soviet Embassy in Copenhagen, the Bulgarian Embassy in London and numerous locations in Cairo.34 The Soviets got some of their own back in late February 1959, when Prime Minister Harold Macmillan made an official visit to Moscow. He recorded his main impressions in his diary, noting for example that ‘Mr Khrushchev is the absolute ruler of Russia and completely controls the situation.’
AB Cryptoteknik 213 ‘ABC’ trial (1977–78) 8, 359–61, 423, 459 Abernethy, Barbara 70 Abu Hamza al-Masri 542 Abyssinia (Ethiopia) 19 Adams, Gerry 500 Aden (Yemen) 6, 156, 164, 345 Admiralty Signals Division 137 Admoni, Nahum 471 Adye, John 427, 431, 476, 483, 494, 495, 598, 608 aerial reconnaissance 31, 59 Afghanistan 387, 420, 421, 510, 511, 533–9 Africa 99, 148, 182, 268, 299, 336, 454–5, 479 Aid, Matthew 521 Aiken, John 326, 327, 328, 331 Airborne Rafter programme 267, 538 Aitken, Jonathan 493–5 al-Badr, Imam 163–4 al-Jazeera 513–14 al-Qaeda 9, 509–11, 513–14, 517, 532 Alanbrooke, Field Marshal Lord 45 Aldeburgh (Suffolk) 286 Aldridge, Peter 449 Alexander, A.V. 123–4 Alexander, Hugh 25, 27, 78, 96, 599 Allen, Lew 357 Allied Commission for Austria and London 170 Alp, Saffet 314 Alvear, Soledad 519 American Office of Naval Intelligence 143 American Type-777 satellite 348 Amery, Julian 162–3, 295 Ames, Aldrich 385, 444 Amory, Robert 158 Amsterdam 487 Anaya, Admiral Jorge 389, 393, 395 Anderson, Jack 344 Andrew, Christopher 2, 362 Anglo-American-Commonwealth sigint 64, 82, 152 Anglo-American relations 7–8; and Balkans 472–5; and Berlin tunnel operation 172–6; changing nature of 441–3, 449–50; and cost of cooperation 222–3; and Cuba 341–2; deterioration in 281–95, 333; and Far East 151–2; and global sigint 89–101; gradual improvement in 295–8; impact of politics on 278; and liberating of Axis sigint 47–56; and Nimrod programme 268–70, 273–4; and Project Sandra 322–3; and public disclosure of sigint material on 355–7, 358, 361–2; and sale of cypher machines 209–15; shared problems 333–4; and sigint 7–8, 38–46, 91–2; and sigint satellite and computer revolution 347–54, 437–8; successful Russian intercepts 279–81; and Suez crisis 157–9; and Third World bases 334–9; and trade unions at GCHQ 421–2, 429; in Turkey 302; and Venona Project 72–88; in wartime 38–46 Angola 357, 454–5 Ankara 58, 254, 302, 303, 305, 310–11, 313, 315, 318, 330 Annan, Kofi 523–4 Antalya (Turkey) 326 Anti-Christ Doom Squad 487 Anti-Smuggling Task Force (Hong Kong) 477 AQ Khan network 531 Aquarius (computer) 349 Arab-Israeli War (1973) see Yom Kippur War Arab states 109 Arafat, Yasser 277 Aral Sea 306 Arbuthnot, Mrs 70 Arctic Circle 133, 136–9, 144–6, 147, 265 Argentina 307–8, 388–415 Argentine Air Force 401, 408, 410, 415 Argentine Army 396 Argentine Navy 395, 405, 408 Argus satellite 377 Arlington Hall (US Army code-breaking centre, Washington) 45, 74, 77, 80, 83 arms control 203, 257, 287, 288, 290 Armstrong, Sir Robert 416, 425, 427, 428, 430–1 Army Intelligence Corps 230 Army Security Agency 80 as-Sallal, Abdullah 163–4 Ascension Island 162, 278, 321, 392, 414 Ash, Timothy Garton 465 Athens 324, 330 Atlantic, Battle of (WWII) 42, 60 Atlas (computer) 349–50 Atomic Demolition Munitions (ADMS) 249 Atomic Energy Authority (AEA) 261 Atomic Energy Intelligence 155 atomic and nuclear weapons 2, 5, 36, 45; and Anglo-US arms control 287–9; at Los Alamos 75, 76, 82; British 163, 249; Chinese 155; need for better intelligence on 253, 255, 321–3; Soviet 107–8, 112, 114, 116, 119, 131–2, 148, 157, 173, 301–2; spiralling of arms race 438–9; US 249; US put on alert (1973) 293–4 Atomic Weapons Establishment (Aldermaston, Berkshire) 418–19 Attlee, Clement 73, 86 ATV 432 Aubrey, Crispin 358–9, 360 Auckland (New Zealand) 487 Audiotel 480 Augsburg (Germany) 48 Austin, Harris M. 115 Australia 79, 80, 85–8, 89, 90, 92–4, 98, 154, 164, 165, 167, 168, 213, 467, 477, 487, 533; Australian Security Intelligence Organisation (ASIO) 86–7, 88; Central Bureau 92; Defence Signals Branch (DSB) 151, 153, 213; Defence Signals Department (DSD) 348; Royal Australian Air Force 150; Royal Australian Navy 266; Royal Australian Signals 166 Austria 96, 371, 384 Automatic Data Processing 353 Ayios Nikolaos (Cyprus) 156, 162, 163, 230, 234, 327, 328, 358–9, 360, 383, 384 Azerbaijan 109 Bad Aibling (Germany) 423 Bad Godesberg (Germany) 215 Badger’s Lair (SAS training exercise) 249–50 BAE Systems Ltd 544 Baghdad (Iraq) 161, 468, 469, 471, 524 Baghdad Pact 161 Bahia Paraios (Argentinean ship) 394, 395 Bahrain 347 Baillie, George 122 Bain, Helen 445 Baldwin, Stanley 18, 72, 400 Balgat (Turkey) 303 Bali bombing (2002) 511, 513 Balkanabteilung (German code-breaking HQ) 50 Balkans 51 Baltic 112, 114, 116, 125, 285 Baltic Sea 273 Bamford, James 263, 361–2, 521 Bandaranaike, Solomon 160 Bank of England 241, 487 Banner, Gordon 312–16, 318 Barbieri, Major 52, 53–4 Barents Sea 114, 115 Barker, Nick 391–2 Barkley, Howard 77 Barsby, Mrs 374–5 Basra (Iraq) 466, 525 Battle of Britain 29 Bay of Pigs crisis (1961) 8, 226 BBC 330, 348, 429, 501, 517, 523–4; BBC Scotland 459 Beach, Sir Hugh 380, 381 Bearman, Sid 595 Beasley, Tony 133–9 Beaumanor Hall (Leicestershire) 63 Beijing 476 Belbasi (Turkey) 302 Belfast 261, 500, 501 Belgium 442, 492 Bell, Rod 409, 410 Benitez, Rafael 114, 115 Benjamin, Ralph 216 Benn, Tony 227 Bennett, Ralph 59 Bentinck, Victor Cavendish 67 Bergen (Norway) 450 Bergold, Harry 295 Beria, Lavrentii 107 Berlin 112, 127–8, 130, 196–7, 227, 228, 253, 270, 369, 370, 372, 478; Berlin Blockade (1948) 71, 113; Berlin Cryptographic Centre 50; Berlin tunnel 169, 170, 172–6, 373, 477 Berlusconi, Silvio 532 Berry, John 358–9, 360 Betts, Richard 600 Beulmann, Major 50 Bevin, Ernest 70 BfV (German domestic security service) 452–3 bin Laden, Osama 511, 513, 514, 549 Binalshibh, Ramzi 514 Bingham, Lord 481 Birch, Frank 43 Bitburg (Germany) 131 Black, Jeremy 407, 408 black chambers 4, 14 ‘Black Friday’ (29 October 1948) 81, 108, 119, 169, 280 Black Sea 112, 131–2, 301, 302, 311, 313, 317, 319 Blair, Tony 4, 436, 497–8, 500, 504, 506, 509, 515, 517, 519, 530, 532 Blake, George 173, 174–5, 176, 178, 179, 238, 385 Bleckede 127 Bletchley Park 103, 186, 188, 221, 354, 549; Americans at 39, 43; and breaking ‘Red’ 25–6; closure of 67–71; and cypher security 54–9; expansion and reorganisation 27–8, 62–3; GCHQ as successor to 1, 5; Huts Three and Six 23, 25, 36, 48, 64–5, 119, 121, 356, 362–3, 364, 387; and machine-based espionage 5; military emphasis at 22–3; post-war role 60–1, 63–7; release of records on 355; SIS GC&CS moves to 22–8; takeover of Axis sigint effort 47–54; tight security measures at 69; unmasking of 362–3; wartime value and achievements 59–60, 61–3; wartime work of 1–2, 5, 25–9, 30, 31–46, 109–10 Blix, Hans 520 Block, Lieutenant 145 Bloomer-Reeve, Carlos 394, 412 ‘Blue Book’ 2–3, 395–6 Bluff Cove (Falklands) 400 Blum, Eberhard 450, 452 Blunkett, David 510, 522 Blunt, Anthony 36, 37, 83, 188, 224, 225, 364, 367 Board of Trade 241 Bodsworth, William 69, 80 Boizenburg (Germany) 127 Bolivia 52, 300 Bonnet, Georges 52 Bonsall, Arthur ‘Bill’ 110 Bontoft, Gerry 352 Borehamwood (aka ‘Department B’, London) 181, 182, 190 Borisenko, Alexsandr Ivanovich 236, 237 Borneo 6, 148, 164–8, 250 Bosnia 8, 9, 471–4, 512 BOSS (South African secret service) 357 Bourbon (Soviet radio intercepts) 75 Boyce, Ed 377 Bracknell (Berkshire) 113 Bradley, General Omar 116 Bradshaw, Mike 423 Brauntoltz, George 432 Bremerhaven (Germany) 116 Brezhnev, Leonid 245, 247 Brezhnev Doctrine 244 Bride (UK code-name for Venona) 80 Bridges, Sir Edward 42, 141–2, 181 Brinks Mat bullion robbery (1983) 505 British Army 14–15, 63, 451, 469, 472; 9 Signals Regiment 162, 327, 383–4; 13 Signals Regiment 166, 228, 493; 14 Signals Regiment 524, 525, 534; 40 Commando 525; British Army on the Rhine 248, 412; First Armoured Division 467, 525; Queen’s Dragoon Guards 525; ‘Rhino Force’ 467; Royal Armoured Corps 248; satellites 198, 208–9, 223, 243, 258, 262–3, 340, 342, 344, 345–8, 347–8, 376, 377, 401, 415, 421, 437–8, 441, 442–3, 445–7, 460–1, 478; sigint units 162, 166–7, 218–19, 228, 327, 383–4, 493, 524, 525, 534; Special Air Service (SAS) 164, 165, 168, 248–51, 359, 409, 410, 411, 468, 472, 475, 536, 583; Special Boat Service (SBS) 333, 409, 410, 411, 443, 468; Special Operations Executive (SOE) 36, 51; Special Reconnaissance Squadron 248 British European Airways (BEA) 129 British Indian Ocean Territories (BIOT) 334 ‘British Intelligence and Weapons of Mass Destruction’ (Butler Report) 2 British Leyland 367–8 British Military Mission (Brixmis) 123, 245–6, 247, 252 British Nuclear Fuels Ltd 500 British Psychological Society 433–4 British Tabulating Machine Company 349 British Telecom 545; Medium Wave Tower (Holyhead) 500 Britten, Douglas 230–8, 369, 382 Broadcasting Standards Authority 481 Broadside operation (US Embassy intercepts in Moscow) 280–1 Brockway, Ernst 383 Brook, Sir Norman 142, 219–20 Brooks, Richard 399 Brooks Field (Michigan) 120 Brown, Gordon 498 Brundrett, Sir Frederick 177, 178 Brunei, Sultan of 164, 586 BRUSA agreement (1943) 43, 44, 121, 151 Brussels 179, 253 Brzezinski, Zbigniew 448 Buffham, Benson 381, 424 Bufton, Air Vice Marshal 207 bugging operations 176–82, 193, 196–7, 473–4, 479, 482, 499 Bulganin, Nikolai 140 Bulgaria 518, 519 Bundesnachrichtendienst (BND, German foreign intelligence service) 214–15, 422–3, 438, 447–51, 452–4, 455, 456, 471, 472, 524 Bundy, William ‘Bill’ 50, 356, 363, 364 Bunyan, Tony 361 Burgess, Guy 8, 37, 73, 82, 83, 84–5, 224, 225, 238, 367 Burma 65 Burrough, John 598 Burton, Sir Edmund 527 Burton-Miller, T.R.W. 57, 191, 577 Bush, George H.W. 356–7 Bush, George W. 511, 517, 532 Butler, Lord 2, 428, 482, 529–31, 610 Byers, Stephen 506–7 Byrnes, Jimmy 53 ‘C’ (head of SIS) 16, 24, 67 Cabell, Charles 96 Cabinet Office Intelligence Coordinator 241, 245, 264, 353, 354, 360, 387, 399, 504 Cable, Danielle 505, 506 Cable, James 278 cable vetting 238–41 Cable & Wireless 240, 312, 392 Caccia, Harold 171 Cadogan, Sir Alexander 23–4, 26, 39, 45, 70 Cairncross, John 36–7, 73, 82, 364 Cairo (Egypt) 58, 159, 179, 185 Callaghan, James 324, 325, 330, 333, 361, 391 Calvi, Roberto 407 Calvocoressi, Peter 59, 61 Cameron, Stephen 505 Campaign for Nuclear Disarmament (CND) 368 Campbell, Alastair 517, 523, 530 Campbell, Duncan 8, 358, 360, 361, 362, 423, 458–9 Canada 38, 89, 93, 95, 97–8, 178, 447, 533; Canadian CBNRC 348; Canadian Communications Security Establishment (CSE) 381, 447; Canadian Joint Intelligence Committee 92 Canine, Ralph 101, 174, 336 Canyon satellite 376 Cape Canaveral (Florida) 322, 437, 461 Cape Matapan, Battle of (1941) 60 Capenhurst Tower (Cheshire) 500–1 Caraman, Mihai 253–4 Carey-Foster, William 185, 188, 228 Carlile of Berriew, Lord 543–4 Carpenter, Harry 598 Carrington, Lord 282–3, 284, 294, 389, 394, 396, 423–4 Carsamba (Turkey) 311–12 Carter, Jimmy 390, 448 Carter, Marshall 264, 272, 273–4, 350 Carter, Pat 448 Cartwright, Ian 328 Carver, Michael 334 Casey, Bill 457 Caspian Sea 112, 132, 161, 301, 302 Castle, Barbara 240 Castro, Fidel 226, 341 Catroux, Georges 52 Caucasus 131, 157 Caviar (Soviet encyphered traffic) 49, 69 Cayan, Mahir 309, 310–15, 314 Caygill, David 445 Celebes 167 Cellnet 481 Cemgil, Sinan 306 Central Gunnery School (Leconfield) 126 Central Signals Establishment 113–14 Ceylon 58, 69, 160, 259, 352 Chagos Islands 278, 335 Chamberlain, Neville 3, 18 Charles, Prince 482 Cheadle (Cheshire) 34, 63, 231 Chechnya 494–5 chemical weapons 470–1, 516 Chevaline project (upgrading of Polaris) 438–40, 459 Cheyne, Bill 166 Chicago Islands 278 Chicksands (Bedfordshire) 63, 360, 535 Chifley, Ben 86, 88, 94 Chile 357, 394, 396, 517 China 98, 129, 150–5, 193–5, 256, 273, 277, 282, 285, 376, 475–8; Chinese Communist Party 150; People’s Liberation Army 151 Chinese language teaching 598 Ching Peng 149, 150 Chippewa Falls (Minnesota) 350 Chirac, Jacques 520–1 Chitty, Brigadier 55 Chiverton, Roy 476 Chum Hom Kok (Hong Kong) 475–6 Church, Frank 356, 357 Church Committee 356, 357 Churchill, Winston 84; addiction to ‘Ultra’ intelligence 1; and airborne incidents 128, 129; and bugging operations 177; comments on the Belgians and Dutch 52; and cypher security 56; and diplomatic intelligence 41; and elint airborne operations 124; and Kuznetsov-Marshall affair 187, 189; meets Stalin 47; as recipient of sigint 3, 5, 40; supports work at Bletchley 26–7, 59, 65, 362 CIA (Central Intelligence Agency) 85, 87, 91; and Bay of Pigs 8, 226; and Berlin-Vienna tunnel operations 169–76; and counter-espionage coup 253–4; and Cyprus 324, 326–7; Foreign Broadcast Information Service 155; and invasion of Czechoslovakia 246; and invasion of the Falklands 399; Jewish sympathisers in 97; and Korean War 100; and Libyan terrorism 457; and Middle East 157, 158; and Nixon administration 4, 278; Office of National Estimates 151; revelations concerning 356–8; Russian spies in 444; security measures 101, 381; and shooting of Che Guevara 300; and Soviet weapons 108, 439; Special Activities Division 514–15; and Turkey 472; and U-2 spy planes 142, 226, 292, 296; and use of communication satellites 348; and Venona Project 77, 82; and Zinnia 322 Cianchi, Commander 54 CIB3 (Metropolitan Police anti-corruption squad) 506 City of London 487, 510 Civil Service 381, 421, 427; Civil and Public Servants Association (CPSA) 419–20; Civil Service Medical Officers Group 382; Civil Service Order in Council (1982) 431; Civil Service Union (CSU) 418, 420, 422–3; First Division Association 435; Society of Civil and Public Servants 426 Claret operations (1964–66) 165–8 Clarke, Kenneth 481, 482 Clarke, Liam 608 Clarke, Peter 266–7 Clarke, William F. 66 Cleveland, Paul 444–5 Clifford, Clark 333 Clinton, Bill 492 Clipper Chip (encryption bypass system) 492 Cobra (Cabinet emergency planning committee) 509–10, 527, 532, 610 Cobra Mist (Over the Horizon Radar) 285–7 code-breakers 2, 6, 198; and Anglo-American relationship 38–46; Australian 92; and Berlin tunnel operation 174; collaboration with Baltic states 31; combined operations 15–16; and computers 340, 348–9, 350–1; and decypherment of ‘Fish’ messages 28; diplomatic 27–8, 37, 43–4, 52–3; during WWII 25–9, 30–46, 58–9; Egyptian 164; and ending of WWII 61; expansion of 63–4; Far Eastern 40; Finnish 32, 35, 91; and French intercepts 52, 53, 209; and global sigint 96; importance of Hong Kong to 151; international work 16–17; and internet 493; Italian 52–4; military operations 14–15, 19–20; move from Bletchley to Cheltenham 5; naval 15; and Pelton affair 444; and personal computing and the internet 488; as Post Office department 14; pre-WWII 22–5; and Prime case 380; quadripartite meeting on computer hackers and encryption 489; revival on eve of WWI 14–15; Russian focus 17–19, 33–8, 169; and sale of cypher machines 209–15; and supply of intelligence reports 2–4, 6–7; and telephone tapping 170–1; and use of cypher machines 21–2; value of 60; and Venona Project 72, 74–88; wartime secrecy 354 COINS (Community On-line Intelligence System) 353 Colby, William ‘Bill’ 293, 327, 329, 330 Cold War 47, 377, 420; airborne incidents 125–33; benefits of intelligence in 175–6; Berlin blockade 71; calming of nerves in 257–8; computing in 349; end of 461, 465, 477, 478–9, 493; flashpoints 203; high profile espionage activity in 8; and planning for future war 247–53; seaborne incidents 133–47; secret service operations 484; sigint in 1, 2, 5, 107–24, 125–47, 402; Soviet nuclear weaponry 108; telephone and bugging operations 169–82; thawing of 195–7; and Venona Project 72–88 Cole, David 379, 380 Coleman, Don 131 Coleridge (Soviet teletype system) 78 Colombia 486, 538 Colonial Office 150 Colorob (computer) 349 Colossus (computer) 28, 48, 68, 70, 349 Combined Cypher Machine 98 Comet aircraft 121–2, 268, 273, 295 Cominstum (digest of hot material) 96 comint (communications intelligence) 96, 101, 110, 111, 122, 123, 228, 252–3, 266, 385, 402, 413 Comintern (Communist International) 19, 30, 37–8, 79 Commonwealth 85–8, 89, 92, 95, 97, 148, 266, 352, 447 Communications Branch of the National Research Council (CBNRC) 94 Communications Data Bill (2009) 543 Communications-Electronics Security Department 241–2 Communications Trials Ship (purpose-built sigint ship) 260–2 Communist Party of Great Britain 19, 188, 367–8, 417 Communist Party of India 87 Communist Party of USA 87 Comprehensive Comparative Radar Library 266 computers 198, 219, 220, 222, 340–1, 342–3, 348–54, 458, 486–93, 507, 507–8, 513, 527–8, 546–8 comsec (communications security) 90, 191–3, 195–7, 211, 218, 241–2, 377 Confederation of British Industry (CBI) 241 Conflict (Vienna tunnel code) 171 Congo crisis (1960) 336 Control Orders 543 Cook, Robin 498 Cooney Hill psychiatric hospital (Gloucester) 382 Cooper, Arthur 598 Cooper, Frank 423 Cooper, Josh 20, 34, 213 Coote, John 136, 137, 138, 143 Copenhagen (Denmark) 179 Corona (satellite) 208 Corporal (battlefield missile system) 249 Cosby, Bill 327 Costello, John 364 Cot, Pierre 53 counter-terrorism 456, 516, 528 Cox, Arthur 301 Crabb, Lionel ‘Buster’ 140–3, 207 Cradock, Percy 193–4, 294 Crankshaw, Edward 34, 35–6, 64 Cray super computers 350–1 Crete 157, 265, 292 Croatia 471–4 Croft, John 37–8 Cromer, Rowley 287–8, 294, 297, 337 Croslieve Mountain (Northern Ireland) 501 Crossman, Richard 227 Cruise missiles 511, 513 Crypto AG 212–15, 457 CSE (Communications Security Establishment) Watton 131 Cuba 226, 341–2; Cuban Missile Crisis (1962) 203, 253, 260 Cukr, Baclav 112 Cummings, Mansfield (aka ‘C’) 16 Cunningham, Andrew 91 Current Intelligence Groups 291, 396 Currie, Laughlin 87 Currier, Prescott 39 Curry, John 79 Curzon, George 15, 16, 18 cyber attacks 487–93 cypher machines; capture of 48–9, 264; Chinese capture of 194, 195; commercial origins of 20; development and use of 20–2, 57, 192; military 54; online 28, 210; and proposed Anglo-US collaboration 98–9; radiation or emanation from 215–18; supplying to NATO countries 209–15; see also Enigma Cypher Policy Board 42, 56–7 cypher security 54–9, 98–9, 191 Cyprus 7–8, 154, 155–6, 159, 161, 162–3, 219, 229, 234, 235, 259, 265, 277, 285, 292, 294, 295, 302, 319, 320–34, 337, 338, 345, 348, 356, 359, 369, 372, 382, 383–4, 419, 423, 466, 471, 504; Cyprus Eight 385 Czechoslovakia 203, 244–7, 253, 387; Czech Air Force Association 112 D-Notice affair (1967) 226, 238–41, 242, 362–3 Damascus (Syria) 159, 291, 300 Darwin (Falklands) 410 Data Encryption Standard (DES) 489 data-mining 486, 546–8 Daubney, Claude 103 Davies, Philip 27 de Gaulle, Charles 52, 195 de Grey, Nigel 35, 43 Deaf Aid (elint reception and analysis kit) 123 Dean, Patrick 142 Decabral, Alan 506 Defcon 3 (US nuclear alert) 293–4 Defence Intelligence and Security Centre (Chicksands) 63, 360, 535 Defence Intelligence Staff (DIS) 245, 246, 353, 369, 397, 402, 414, 527–8 Defence Reviews 329 Defence Signals Branch 93, 151, 153, 213, 578 Demos-1 (Hong Kong sigint station) 475–6 Demos-4 (Hong Kong sigint station) 476 Denham, Flight Sergeant 126 Denmark 442, 533 Denmark Hill (Metropolitan Police intercept station, London) 37 Denniston, Alastair 15, 18, 21, 24–5, 27, 28, 31, 34, 38, 40, 43–4, 70, 79 Denton Green, Robert 400, 402, 403, 407 Department of Economic Affairs 241 Department of Trade and Industry (DTI) 487 détente 247 Detica (security company) 544 Dexter, Harry 87 Dhekelia 163, 233, 327 Diana, Princess of Wales 479–83 Dictionary (keywords/predesignated phrases system) 343 Diego Garcia 321, 332, 335–9, 597 Dieppe raid (1942) 55 Diffie, Whitfield 490 Dimbleby, Jonathan 524 Dingli (Malta) 32, 156, 162 diplomatic intelligence 27–8, 37, 43–6, 52–3, 62, 69, 148, 159, 164, 176–82, 349, 355, 377 Diplomatic Protection Squad 506 Diplomatic Wireless Service (DWS) 58–9, 123, 181, 185–90, 192, 262, 417, 418, 585 Director General of Intelligence (DGI) 246 Directorate of Scientific Intelligence 123 Discovery (space shuttle) 437 Diyarbakir (Turkey) 300, 301–2, 306 Dobrynin, Anatoly 454 Domazet, Davor 472 domestic surveillance and intercepts 540–50 Donoughue, Bernard 3, 325 Doran, Frank 126 Doublecross system 229, 255 Douglas-Home, Sir Alec 163, 282, 312–13 Dozier, James 407, 452 Drake, Edward 94 Drew, John 229 drugs 486, 503, 514, 538 Drumheller, Tyler 529–30 Drummond (Argentine frigate) 395 DS.19 (MoD unit) 368 Dubček, Alexander 244 Dublin 501 Dudley-Smith, Russell 49, 55, 261 Duff, Antony 360, 399 Duffton, Nancy 435 Dulles, Allen 157, 158, 174, 176, 203 Dulles, John Foster 157 Dunderdale, ‘Biffy’ 21 Dunlap, Jack 355 Dunnell, Peter 127 Dwyer, Peter 82 East Africa 335–6 East Asia 120 East Germany 123, 131, 195–7, 345, 370, 379, 385, 453, 605 East-West summit (Paris, 1960) 204 Eastcote (London Signals Intelligence Centre) 62, 68–9, 79, 80, 103, 191, 349 Eastern Bloc 123, 175, 244, 245, 247, 256, 267, 282, 447, 465 Eastern Europe 33, 53, 78, 99, 119, 256, 284 Easton, James 82 Eavesdropper revelations (1976) 358, 359 Echelon (Anglo-US communications network) 7 economic intelligence 240–1 Ecuador 52 Eden, Anthony 46, 85, 129, 140, 141, 142–3, 155–6, 160, 178, 189 Eemnes (Netherlands) 415 Eger (Norwegian ship) 117 Egypt 58, 109, 155–9, 259, 263–4, 271, 277, 290–2, 295, 320, 467 Eichmann, Adolf 307–8 Eisenhower, Dwight D. 140, 157, 158, 202, 205, 219 Electrical Trades Union 368 Electronic Warfare Conferences 122, 123, 307–10 elint (electronic intelligence); air-based 111–14, 118–19, 122, 124, 250–2, 267–73; and Anglo-American relations 111–12; and European cooperation 591; in Germany 247, 250–1; and invasion of the Falklands 401, 413; and jamming of Whetstone monitoring station 190; land-based 117–20, 123; naval 114–17; near the Soviet Union 169; postwar expansion 110; rejection of 247; in Turkey 306; wartime use of 110 Elizabeth II, Queen 480, 482 Elkins, Robert 143 Elliott Brothers Ltd 598 Ellis, James 490, 492 Elmers School (GC&CS Diplomatic Sections) 23 email 488, 507, 513–14, 521–3, 541 embassies 151; Anglo-US-Canadian intercepts in Moscow 280–1; attacks and raids on 193–5; as forward listening stations 31; KGB in 82–3, 283–4; and MI5 watcher operations 183–90; security headache 195–7; sifting of waste-baskets in 56; spies in 84; tapping and bugging operations 171, 176–82, 193, 197–8, 281, 477; ultra-secret short-range sigint stations in 244–5; worldwide collection of intercepts from 45, 53, 79, 112, 159, 242–3, 385 Employment Select Committee of the House of Commons 424 Engulf (Egyptian Embassy cypher machine operation) 216 Enigma (German cypher machine) 1, 20–2, 23, 25–6, 27, 35, 38, 39, 42–3, 43, 51, 68, 78, 80, 354, 387 EOKA (Cypriot guerrilla force) 163 Episkopi (Cyprus) 234 Erim, Nihat 306, 312, 315 Eritrean Liberation Front 336 Escobar, Pablo 538, 549 Ethiopia 299, 334, 335–6 European Convention on Human Rights 433, 483 European Economic Community (EEC) 284 European Principals Meeting 450–1 European Union (EU) 540 Evatt, Dr H.V. 85, 86 Evere (NATO-GCHQ cell) 254, 255–7 Exocets (sea-skimming missiles) 390, 406–7, 414, 415 Faisal, King 160–1 Falkland Islands 6, 424, 429, 441, 442, 452, 467; Argentinean ambitions towards 389–92; Argentinean invasion of 392–3, 394–401; British troops on 408–14; comint and elint on 401, 413; diplomatic exchanges with 403–4; effect of war on British sigint 415; French help on 415; improvised communications with GCHQ 402–3; inadequate intelligence on 392–401; leaseback idea 392; naval action 404–8; near-miss air disaster 408; Norwegian help on 401, 442; scrap-metal incident 393–4; surprise attack on 388–9; Task Force sent to 398, 401, 403, 404–8; US denies pre-knowledge 601 Famagusta (Cyprus) 163, 235, 327, 328 Far East 39, 69, 78, 93, 129, 148–51, 164–8 Farrell, Terry 496 Faslane naval base (Scotland) 145, 146 Fatah (Palestinian organisation) 304, 308 FBI (Federal Bureau of Investigation) 76–7, 81 Federation of Malaysia 164–8 Ferranti 349, 598 ‘ferrets’ (flying intelligence stations) 111–14, 203–7 Fetherstone-Haugh, Timothy 383 Fetterlein, Ernst 17–18 Fieldhouse, Admiral 392 Fiji 446 Finland 31, 32, 76, 83, 91, 371, 489 First World War 14, 15, 16–17 Firyubin, Nikolay 279–80 Fischer, David 407 Fish (encyphered teleprinter) 28, 48, 49, 51 Fitz, Harold 127 Fleet Headquarters (Northwood) 400, 401, 402 Fletcher, WPC Yvonne 455–6 Florida 341 Flowers, Tommy 28, 349 Foden, Arthur 242 Foot, Michael 433 Ford, Gerald 297 Foreign and Commonwealth Office 16, 22, 45, 46, 56, 58, 66, 70, 83, 103, 128, 171, 172, 190–1, 192, 220–1, 239, 245, 273, 281, 287, 333, 335, 339, 353, 355, 360, 392–3, 398, 417, 420, 428; South-East European Department 317; Technical Maintenance Service 182 Forest Moor (wireless station near Harrogate) 96 Fort Bridgelands (Kent) 63 Fort Knox (Kentucky) 101 Fort Meade (NSA HQ, Washington) 102, 157, 174, 223, 271, 513, 528 Förvarets Radionstalt (FRA) 91 Foss, Hugh 21, 64 Fox, Katherine 598 FRA (Swedish sigint service) 421, 438, 456, 483–4 France 21, 32, 44, 52, 52–3, 109, 130, 268, 442, 445, 450, 467, 492 Franks, George 382 Free French 28, 52 Freedom of Information Act 482–3 Freeman, John 279 Freeman, Peter 531 French Guyana 415 Friedman, William 39, 44, 95, 213, 214 Friedrich, Lt Colonel 50 Fuchs, Klaus 72, 82, 83, 87, 104, 238 Fyjis-Walker, Richard 316 Fylingdales (Yorkshire) 287 Gaddafi, Muammar 455, 457, 531 Gagarin, Yuri 301 Gaitskell, Hugh 141 Galvin, John 474 Gambier-Parry, Richard 57, 181, 186, 188 Gamma-Guppy (Soviet intelligence intercepts) 244–5 Gardner, Meredith 75, 79, 80 Garner, Joe 249 Gates, Robert 457 GC&CS (Government Code and Cypher School) 361; and Anglo-American collaboration 40–1; civil achievements 28–9; and cypher security 56–7; diplomatic centre at Berkeley Street 27–8, 37, 43–4, 52–3; divided into civil and military sections 27–8; and European collaboration 20–2; military interests 19–20; post-war role 61, 63–7; relocation to Bletchley 22–7; Russian interests 17–19, 30–2; setting up of 16 GCHQ (Government Communications Headquarters) 1, 31, 104; and al Qaeda 511–12; Benhall 350, 360, 497, 526; and Bosnian-Croatian conflict 472–5; Bude (formerly CSO Morwenstow) 342, 343–4; budget figures 587; building of ‘Doughnut’ 9, 497, 526, 527–8; ceases exchanging intelligence with NSA 289–90; and changing nature of global threats 504–5; and closer relationship with MI5 and SIS 503–4; and Cobra Mist/Orford Ness problems 285–7; code-breaking and intelligence-gathering 6–8; combined NATO-GCHQ cell at Evere 254, 255–7; computers in 527–8; cooperation with NSA 222–3, 278, 282–3, 346, 347–54, 438, 448–58, 461; declining position of 422–3, 438, 441; development of new systems 342–54; diplomatic initiatives 108–9; Directors of 551–2; domestic surveillance and interceptions 540–50; DWS operations 186; E Division (Personnel) 425, 427; and economic intelligence 493; Empress Building (Earl’s Court) 382; encryption problems in banking and commerce 487–93; and end of Empire 148–55; expansion of 79, 169; F Division 476; file storage 598; funding of 219–23, 334, 458, 493, 494, 495; Free Trade Union 430; future purpose of 485; and global sigint 92, 94, 95–100; and Gulf War (1991) 466, 469; H Division (mathematicians and cryptographers) 432; and hoax letters prank 469–70; increased intelligence operations 120, 121–4; influence on foreign policy 321; installation of dedicated computer unit 507–8; and internal surveillance 9–10; and internet 100; and invasion of the Falklands 392–403, 405–6, 411; and IRA 498–503; and Iraqi dossiers 516–17, 530; J Division (Special sigint—Russian) 346, 374, 376, 419, 429, 434–5, 438, 495; J-Ops 429, 434–5, 438; K Division (non-Russian sigint) 218, 222, 402, 420–1, 478, 495; and KGB espionage 108, 189, 424–5; and Korean War 101; language problem 512–13, 516; legal identity of 484–5; and Libyan Embassy affair 455, 456; London office (Palmer Street) 192, 497; loss of Hong Kong listening station 475–8; merger with com sec 241–2; and Middle East 155–64; moles in 368–85; move to Cheltenham (1952) 102–3, 120–1, 122, 191; need for 8–9; ‘need to share’ problem 503–4; Nimrod programme 267–70, 271–4; and Noye affair 505–7; Oakley 360, 380, 427, 496, 497, 526; ocean-going activities 6, 136; organisation overviews 563–5; overhaul of operations 493–7; positive vetting at 227–8; post-war organisation and location 67–71; and Princess Diana 482, 483; and problems with ‘special relationship’ 441–3; promotion and career structures 576; purpose-built sigint ship 260–4; R Division (security) 425; reads HVA traffic 605; reinstatement of unions at 497–8; relationship with private companies 240; removal of trade unions at 416–36; and Russian problem 46, 71, 75, 78, 169, 299; S Division 261; secret pact with armed services 5–6, 117–18, 132–3; size of 227; ‘Station X’ 69; as successor to Bletchley Park 1, 5; suicides connected to 382–3; and supply of cypher machines to NATO 209–15; T Division 123; Tempest 216–18; Trade Union Campaign 498; Turkish operations 300–1, 311–19; unmasking of 355–64; use of deaf and dumb civilian personnel 153; use of name ‘GCHQ’ 61, 67; and use of polygraph at 425–6; and Venona Project 77–81; visibility of 1, 2, 8, 341, 436, 484; W Division 261; and War on Terror 533, 539–40; and West German defections 455–6; whistleblower in 521–3; X Division 6, 350, 353; Z Division (use of sigint) 388, 503; Zionist interests 109 GEC-Marconi 433 General Belgrano (Argentine cruiser) 404–6 General Strike (1926) 18 Geneva (Switzerland) 178; Peace Conference (1954) 178 George VI, King 59, 191 Georkadijis, Polycarpos 323–4 Geraldton (DSD site, Australia) 477 Germany 15, 29, 30, 31, 32–3, 44, 47–50, 55, 62, 78, 96, 127–9, 130, 142, 170–1, 219, 229, 247, 256, 270, 492; Army 26, 29, 43, 47; High Command (OKW) 49, 349; Navy 42; see also East Germany; West Germany Gezmiş, Deniz 310, 311 Giant Reach (SR-71 flights from US to Middle East) 292–3 Gibraltar 162, 398, 415 Gibson, Sir Peter 502 Gilbey, James 479–81 Glazebrook, George 92 Glidwell, Mr Justice 430–1 Glover, Sir James 413 Godfrey, Admiral 32 Golan Heights 297 Golden Valley Hotel (Cheltenham) 432–3 Goldsmith, Lord 522–3 Golombek, Harry 25 Goodpaster, Andrew 256 Goonhilly Downs (Cornwall) 342–3, 597 Goose Green (Falklands) 404, 410, 411 Gorbachev, Mikhail 456 Gordievsky, Oleg 385, 478 Gore Booth, Sir Paul 339 Gosport (Hampshire) 134 Gouzenko, Igor 85 Government Communications Staff Federation 428, 429 Government and Overseas Cable and Wireless Operators Association 418 Government Technical Assistance Centre (GTAC) 507, 547 Government Telecommunications Advisory Centre 504 Gow, Ian 482 Gowrie, Lord 428 Grab (Galactic Radiation and Background) satellite 208 Grant (MI5 computer scheme) 528 Grantham, Sir Alexander 152 Granville (Argentine frigate) 395 Grechko, Andrei 245 Gredjeva, Nina Michailovna 189 Greece 163, 259, 319, 320, 324, 334, 450, 472 Green Light (US special atomic demolition munitions programme) 249 Greenhill, Denis 239, 284 Greenock naval base (Scotland) 144 Greenpeace 446 Grey (US diplomatic code) 40 Grindley, Mike 430 Gromyko, Andrei 205, 206 Groupe de Synthèse et Prévision (France) 284 GRU (Soviet Military Intelligence) 88, 173, 230 Guardrail (US airborne tactical sigint systems) 251–2, 272 Guernica bombing (1937) 22 Guevara, (Ernesto) Che 300 Gulf War (1990–91) 452, 465–71, 529 Gulf War (2003) 479, 516–26 Gun, Katharine 521–3 Gurdon, Adam 396 Gurkhas 164–5 Gurney, Sir Henry 149 Habbaniya (Iraq) 20 Hagelin, Boris Jnr 212–13 Hagelin, Boris Snr 212 Hagelin (cypher machine) 56, 78 Haig, Alexander 403–4 Halifax, Lord 24 Hall, Theodore 73 Hallock, Richard 74–5 Hamilton, Alexander 432 Hampshire, Sir Stuart 221–5, 260 Handel, Michael 362 Hankey, Lord 36 Hanley, Michael 361, 587 Hanley, William J. 305, 306 Hanslope Park (Buckinghamshire) 57, 58, 182, 185, 186, 187, 192, 196, 418 Hanssen, Robert 444 Hardy, Tim 166 Harland & Wolff 261 Harman, Harriet 368 Harrier jets 403, 404, 407, 408, 441 Harris, Robert 59 Hart, Herbert 225 Harty, Russell 359 Harvest (computer) 350 Hashmi, Jabron 535 Hastings, Edward 95 Hawaii 92 Hawkes, John 216 Hay, Malcolm 15 Hayden, Michael 508 Hayter, William 97 Healey, Denis 168, 245, 256, 399, 426, 429, 433 Heath, Edward 4, 239, 279, 315, 337, 338, 439 Heliopolis (Egypt) 92, 155, 162 Hellenbroich, Heribert 452–3 Hellman, Martin 490 Helmand province (Afghanistan) 534, 535 Helms, Richard 292, 356 Hemblys-Scales, Roger 86 Henderson, Nicholas 2–3 Hennessy, Peter 90, 577 Herman, Michael 261, 287, 419, 421, 435 Heseltine, Michael 426 Hibberson, Anthony 189 Hill, Jim 86–7 Hill, Major 120 Hillenkoeter, Roscoe 85 Hillgruber, Andreas 59 Hinsley, Harry 59, 64 Hiroshima 2 Hiss, Alger 88 Hitler, Adolf 3, 5, 29, 30, 31, 32–3, 48, 221, 290 Hoad, Norman 132 Hokkaido (Japan) 112 Holden Agreement (1942 & 1944) 43 Hollis, Sir Roger 79, 86, 182, 367 Holmberg, Elena 389–90 Home Office 507, 538, 544 Honest John (battlefield missile system) 249 Honeywell (computers) 458 Hong Kong 19, 30, 32, 96, 100, 151–5, 219, 256, 277, 419, 475–8 Hooper, Joe 191, 222, 223, 228, 273–4, 285–6, 343, 353, 419, 448, 466, 585 Hoover Commission 219 Hosenball, Mark 358 House of Commons Public Accounts Committee 440, 459 House of Commons Select Committee on Employment (1985) 433–4 Howard, Edward Lee 384, 444, 447 Howard, Michael 364 Howarth, Jack 189 Howe, Geoffrey 426, 427–8, 429, 431–2, 436, 460 Howse, Philip 79, 84 Hughes, Chief Inspector 187 Hughes, Robert D. 111 Hungary 46, 158 Hunt, Sir John 329–30, 337–8, 356–7, 361 Hunters Stones Post Office Tower 346 Hurd, Douglas 495 Hurley, Michael 144–6 Hurn, Roger 495, 526 Hussein, King 161, 164, 290 Hussein, Saddam 467, 516, 524, 525 Husum-Milstedt (intercept station, Germany) 50 Hutton, Lord 529 Huxley, Aldous 549 HVA 605 Iacobescu, Ion 253 IBM 350, 352, 489 Igloo White (ground sensors) 252 Imre, Nahit 254 Incirlik (Turkey) 326 India 4, 18, 19, 30, 32, 85, 95, 178, 334 Indonesia 153, 164–8 Information Research Department 156 Ingebrigsten, Jan 450 Ingham, Bernard 428 Inman, Bobby Ray 399, 422, 601 Intelligence Assault Units 47–8 Intelligence and Security Committee 484–5, 529, 539 Intelligence Services Act (1994) 484–5, 488 Intelligence Support Activity 168 Intelsat 342 Intercept Control Centre 250 Intercept Modernisation Programme (IMP) 543–5, 547–8 International Control Commission on Vietnam 178 International Regulations on Sigint (IRSIG) 90 International Security Assistance Force (ISAF) 533 internet 8, 488, 507–8, 541, 544–5 IRA 345, 455, 479, 481–2, 494, 498–503, 593 Iran 109, 112, 155, 268, 295, 299, 302, 421, 467, 472, 605 Iran, Shah of 299 Iraq 155, 156, 160–2, 259, 295, 320, 465–71, 479, 516–17, 528–31; 124 Electronic Warfare Regiment 525 IRSIG (Instructions and Regulations concerning the Security of Signals Intelligence) 503–4 Iscot (wartime Comintern traffic) 37–8 ISI (Pakistani intelligence service) 514 Ismailia (Egypt) 32, 185 Ismay, General Hastings ‘Pug’ 27 Israel 97, 164, 263–4, 277, 290–1, 293, 307–8, 415, 471; Israeli Sea Corps 264–5 Istanbul 307, 309, 310, 316, 318 Italy 19, 44, 52, 96, 345, 452; Italian Cryptographic Bureau 54–5 ITT (telecoms company) 341, 342 Ivy Bells (undersea cable-tapping) 384 Jakarta (Indonesia) 167, 168 Japan 17, 29, 39, 40, 44, 65, 100, 110, 152, 445, 446 Jebb, Gladwyn 64 Jenkins, Roy 51 Johnson, Lyndon B. 50, 238, 353 Johnson, Robert 346 Johnstone, Sir Charles 164 Johnstone, Colonel Hugh 327–8, 359, 360 Joint Intelligence Committee (JIC) 67; and Arab states 109; Chevaline project 440; circulation of BJs 70; collection of elint on Soviet air-defence capabilities 132; considers Soviet threats a bluff 204; Crabb incident 141–2; D-Notice affair 239; deployment of equipment in Eastern Bloc 123; failures and inaccuracies of 108, 245–6, 387–8; focus on economic, technological and scientific subjects 241; French cooperation 284–5; intelligence failures 387–8; and invasion of the Falklands 391, 395–7; and Iraq 466; Joint Intelligence Committee Far East 167; and new technology 353; and Palestine 97; and possible Soviet move inside Eastern Europe 256; rethinking of European targets 345; review of aerial and submarine surveillance 207; review of GCHQ spending 221; and Soviet invasion of Czechoslovakia 245–6; and Soviet Union 46; and surprise Soviet nuclear attacks 321; and Turkish invasion of Cyprus 319, 325; and Vienna tunnel 171; and Yemen Civil War 164 Joint Technical Services Language School (Tangmere, Surrey) 370 Jones, Eric 46, 121, 132, 142, 159, 188, 191, 197, 418, 585 Jones, Colonel H. 411 Jones, R.V. 102–3, 110, 111, 579 Jordan 157, 164, 308 Joseph, Keith 286 Jowell, Tessa 498 July Bomb Plot (1944) 221 Kabul (Afghanistan) 533 Kagnew (Ethiopia) 335–6 Kaiser, Michael 240–1 Kapustin Yar (Soviet Union) 112, 131, 301 Karadſić, Radovan 473 Karamursel (Turkey) 301 Karlshorst (Germany) 371 Katanga (Congo) 336 Kazakhstan 107 Keepnet (recording equipment) 458 Keith, Bruce 69, 93, 94 Kelly, Gerry 500 Kennan, George 177 Kennedy, Jacqueline 180 Kennedy, Paul 59 Kenya 125, 334, 370, 511 Ker, Leonard Douglas 189 Kern, Dick 449–50 Kerr, Sir Archibald Clark 84 Key Recovery (or Key Escrow) 492, 506–7 KGB (Russian secret service) 137, 230, 285, 419, 538; agents working for 36–7, 185–90, 224–5, 231–7, 354–5, 369–85; and Airborne Rafter programme 267; defections from 478–9; Eight Directorate 377; expulsion from London embassy 283–4; intercepts on 53, 96; microwave intercepts 281; and miners’ strike (1982) 368; and release of material on GCHQ 355; Sixteenth Directorate 377; surveillance operations 4, 183–5, 190–1; tapping and bugging operations 170, 173, 175–82, 193; and Tempest 216–17; and Venona Project 72–88, 98, 104 Khalid Sheikh Mohammed 514, 515 Khrushchev, Nikita 4, 140, 142, 173, 179, 180, 202, 204 kidnapping and hostage-taking 452, 513–14; in Turkey 302–19; see also terrorists, terrorism Kiev (Soviet Union) 126 Killian, James R. 219 King, Tom 426, 427 Kingsdown (Kent) 34 Kinnock, Neil 433 Kipling, Rudyard 13–14 Kirknewton airbase (Scotland) 118 Kirkpatrick, Sir Ivone 130 Kissinger, Henry 277–81, 283–4, 287–90, 292, 293, 294–7, 319, 324, 326, 329, 330, 331, 337–8, 403, 441, 444 Kizildere (Turkey) 312–19 Klemme, General 50 Klugman, James 36, 188 Knockholt (Kent) 120 Knox, Dilly 21 Kohl, Helmut 453 Kola Peninsula (Soviet Union) 118, 136 Komer, Robert 303 Korea 6 Korean War (1950–53) 99–101, 116, 118–19, 120, 129, 152, 178 Kosovo 8, 512 Kosygin, Alexei 280 Koza, Frank 517–18, 521 Kuala Lumpur (Malaysia) 150–1 Kubat, Ferit 313, 314 Kuching (Malaysia) 166 Kurchatov, Igor 107 Kurku, Ertugrul 313–14, 315 Kursk (Soviet Union) 36–7 Kuwait 465–70, 524 Kuznetsov, Pavel 183–8 La Belle discothèque (West Berlin) 457 Labuan (Malaysia) 166 Lagos, Ricardo 519 Lamphere, Robert 76–7 Lander, Stephen 494 Lange, David 444–5 Langley (Virginia) 292, 441 Laos 446 Larnaca (Cyprus) 384 Latakia (Syria) 331 Law, John 312–16, 318 Lawson, Nigel 460 Le Bailly, Louis 246, 286–7, 291, 439 Leach, Henry 395 Lebanon 161, 308 Lee, Raymond 39, 40–1 Libya 109, 295, 334, 455–8, 531; Libyan People’s Bureau (London) 455–6 Liddell, Guy 367 Light Electronic Warfare Teams (LEWTs) 534–5 Limassol (Cyprus) 325 Lindsay, Michael 151 Little, Peter 420–1 Little, Rod 402 Little Sai Wan (Hong Kong) 153, 475 Livebait (comparison of different signals) 458 Llanos, Gonzales 408 Lobban, Ian 542 Lockerbie incident (1988) 457–8, 605 Lockhart, John Bruce 171 Lockheed 476 Loehnis, Clive 31, 197, 210–11, 223, 466 Lohan, Sammy 239 Lombardo, Juan 393, 395 London bombings (2005) 532–6 London Communications Security Agency (LCSA) 103, 191–3, 210, 211, 213, 217, 585 London Communications Security Board 585 London Processing Group (LPG) 372–3 London Signals Intelligence Board 51–2, 109, 142; London Signals Intelligence Centre 69; London Signals Intelligence Committee 267, 268 Longfellow (Soviet cypher system) 78 Lonsdale, Gordon 238 Lord (Vienna tunnel code) 171 Luanda (Angola) 59, 455 Lucas, George 144, 145 Luftwaffe 26, 33–4, 35, 36, 43, 50 Luga airport (Malta) 295 Luneburg Heath (Germany) 127 Lunn, Peter 171, 172, 174 Lyalin, Oleg 283 Lyttelton, Oliver 149 MacArthur, General Douglas 45 McCormack, Alfred 45 Macdonald, Ken 543, 548 McGuinness, Martin 500 Machon, Annie 456 Mackay of Clashfern, Lord 484–5 Mackenzie King, William Lyon 94 Maclean, Donald 8, 37, 72, 73, 76, 82, 84, 87, 104, 238, 367 McManners, Hugh 409, 410 Macmillan, Harold 3–4, 143, 179, 204–7, 226, 364 McNamara, Robert 168 McNeill, Hector 224 Magdeburg (Germany) 50 Magic (Japanese cypher) 29, 39, 41, 44, 69 Maguire, Harold 268, 269 Major, John 398, 484 Makarios, Archbishop Mihail 163, 296, 320, 323–5, 328, 330 Malatya (Turkey) 306 Malaya 6, 30, 38, 125; Malayan Communist Party (MCP) 149, 150; Malayan Emergency 149–51 Malaysia see Federation of Malaysia Malinovsky, Rodion 204 Malta 156, 162, 295 Maltby, Ted 58, 79, 187 Manchester University 349 Manchuria 19 Mandelson, Peter 498 Manhattan Project (Los Alamos atomic bomb project) 75, 76, 82, 219 Manningham-Buller, Dame Eliza 515 Mao Tse-tung 4, 151, 193, 195 Marchetti, Victor 356 Marconi (company) 311 Marconi, Guglielmo 13 Marenches, Alexandre de 442 Marr-Johnson, Patrick 77 Marshall, George 42 Marshall, William 184–90 Martin, William H. 176, 355, 423 Marychurch, Peter 428, 434, 445, 448, 449, 451, 458–60 Mask operation 19 Mason, Roy 332 Mathison, Alan 25 Mauborgne, Joseph 18 Mauritius 334, 335, 338 Mazzini, Giuseppe 14 Medical Research Council 434 Mediterranean 16, 44, 114, 273, 295, 319 Meir, Golda 290–1 Menendez, Mario 412–13 Mentyukov, Igor 201–2 Menwith Hill (Yorkshire) 345–6, 347, 421, 449 Menzies, Sir Stewart 23–4, 26, 27, 28, 38, 39, 42, 45, 51–2, 55, 67, 82, 142 Methods to Improve (MTI) 220 Mexico 15, 517, 519–20 Meyer, Cord 358, 595 Meyer, John C. 271, 272 MI5 see Security Service MI6 see Secret Intelligence Service Middle East 7, 15, 16, 19–20, 32, 34, 41, 51, 97, 148, 155–64, 181, 182, 271, 277, 282, 290–5, 299, 320, 333, 334, 336, 376, 385, 454, 467, 472, 479, 494; Middle East Technical University (Ankara) 303, 304; Middle East War (1973) see Yom Kippur War Middle Six countries 519 Millward, Bill 63, 121, 221–2, 253 Milne, Alasdair 459 Milner, Ian 86 Milner-Barry, Stuart 25, 27, 364, 387 Milošević, Slobodan 473 Ministry of Defence (MoD) 240, 272, 286–7, 291, 312, 368, 423, 456, 495, 510 missiles see rockets and missiles MIT (Turkish National Intelligence Agency) 304, 314 Mitchell, Bernon F. 176, 355, 423 Mitchell, Graham 367 Mitchell, J.R. 118 Mitterrand, François 414–15 Mladić, Ratko 473, 474 mobile phones 492–3, 505, 538, 541, 548 Modin, Yuri 82–3, 84 Moffit, Bill 296–7 Molotov, Vyacheslav 178–9 Monterey (California) 332 Montgomery, Field Marshal Bernard Law 58, 85 Moon-bounce project 262–3 Morgan, Gerry 78 Moriarty, D.M. 587 Morocco 334 Morris, Gareth 433 Morwenstow (Cornwall) 342 Moscow 4, 18, 19, 30, 33, 35, 36, 37, 45, 47, 53, 59, 74, 82, 84, 86, 104, 126, 148, 151, 175, 176–8, 179, 185, 186, 189, 201, 203, 205, 284, 465; Moscow Peace Treaty (1942) 32 Mossad (Israeli secret service) 291, 299–300, 307–8, 444, 472 Mottram, Richard 577 Mount Tumbledown (Falklands) 413 Mountbatten, Lord Louis 110, 143, 192 Mowlam, Mo 500 Mubarak, Hosni 467 Mullah Dadullah 535 Muller, Wilma 127 Mullet Creek (Falklands) 397 Munich Crisis (1938) 3, 22 Murmansk (Soviet Union) 133, 143 Murray, Len 416–17, 426, 427, 428 Muslims 472, 473, 474, 537, 538, 542 Mustard (Enigma key) 35 Mutual Balanced Force Reduction programme 287–9, 319 Mutual Weapons Development Programme 211 Nagasaki (Japan) 2 Nan-Szu-Pu (Taiwan) 152 Narvik raid (1940) 55 Narwal (Argentine trawler) 407–8 Nasser, Gamal Abdel 155–6, 161, 164 National Central Electronic Reconnaissance Agency (NSEI, Croatia) 473 National Council for Civil Liberties 361 National Criminal Intelligence Service 504 National Infrastructure Security Coordination Centre 609 National Security Agency (NSA) 7; and al Qaeda 510–12; and Berlin tunnel operation 174; and BND 422–3, 438, 447–51, 452–4, 455; and Bosnian-Croatian conflict 472–5; ceases intelligence exchange with GCHQ 289–90; and commercial encryption 488, 489; cooperation with GCHQ 222–3, 278, 282–3, 346, 347–54, 438, 441–3, 448–58, 461; creation of 101–2; data silo in Utah 546; development of new systems 345–6; development of Technical Research Ships 260; and documents on Princess Diana 483; and downing of Powers’ U-2 202–3; elint and comint responsibilities 122–3; funding of 334, 346; influence on foreign policy 321; and internet 8, 508; and invasion of the Falklands 398, 399, 415; and North Korea 100; and polygraph 434; and Prime case 376; public mention of 242–3, 355, 358, 361–2; relationship with US armed services 271–2; and Russian nuclear forces 119; Russian spies in 384–5, 444; and sale of cypher machines 209–15; and strategic elint 267; and Suez crisis 157, 158; and Tempest 216–18; and trade unions at GCHQ 421–2, 424, 429; Turkish operations 300–19; use of security measures 381; visibility of 341; and Yom Kippur War 291–2 National Service 117, 153, 219, 229, 369 NATO 126, 130, 209–15, 217–18, 242, 247, 248, 253–7, 268–9, 270, 272, 283, 300, 319, 328, 345, 429, 448, 452, 456, 467, 533, 534; Military Committee 256; Nuclear Planning Group 332; Special Committee 257 Nauticus Corporation 265 Naval Intelligence 32, 116, 143 Naval Mechanics School (Buenos Aires) 389 Nave, Eric 19 Nazi-Soviet Pact (1939) 31 Neff, Paul 50, 76 Netherlands 442, 443 ‘Never Again’ agreement (1982) 440–1 New People’s Army (Philippines) 452 New Zealand 89, 90, 92, 93, 98, 164, 165, 438, 442, 444–7, 448, 487; Government Communications Security Bureau (GCSB) 445–6 Newman, Dr 145 Newman, Max 28, 70 Nicoll, Douglas 387–8, 396, 421, 529 Nicoll Report (1981) 388 Nicosia (Cyprus) 326 Nimrods 268–70, 271–4, 326, 414, 415, 442, 474, 515, 536, 537 9/11 9, 509–14, 531 Nixon, Richard M. 4, 277–8, 279, 281, 283–4, 288, 290, 293, 297–8, 304–5, 325–6, 337, 338, 434 Noakes, John 348 Noise-Induced Hearing Loss 608 Noise Investigation Bureau 110 Nokia (telecoms company) 489 Norland, Selmer 48, 78 North Atlantic Council 254 North Cape, Battle of (1943) 60 North Korea 100, 120, 129, 175, 264 Northern Ireland 329, 498–503; Peace Process 501 Northwood Hills (communications security establishment) 192, 400, 401, 402, 469 Norway 55, 99, 116–17, 134, 139, 269 Nott, John 395, 396, 397–8, 414–15, 429, 601 Noye, Kenneth 505–6 Nuclear Planning Group 255 Oakleigh Park North (Soviet-radio monitoring station, Whetstone) 190–1 O’Connor, Morris J. 144, 145 Odette (Army intercept equipment) 474, 525, 534, 536–7 Odom, William ‘Bill’ 214, 385, 413, 434, 442–4, 446–52, 454–5, 457, 458, 471, 476 Oedipus (computer) 349 Oeljeschaeger, Major 50 Office of Strategic Services 87, 91 Official Secrets Act 8, 359, 360, 363, 383, 522 oil 298, 336, 356 Okinawa (Japan) 152 OKK-5 (Soviet codebook) 35 Oldfield, Maurice 82, 358 Omagh (Northern Ireland) 501–3 Oman 271, 345 Omand, Sir David 9, 272, 398, 495–7, 498 one-time pads (encryption system) 18–19, 20, 56, 74, 81, 83, 108 Operation Citadel (1943) 36 Operation Claret (1956) 140–2 Operation Damage (Comet sorties in the Mediterranean) 273 Operation Debenture (1954) 152–3 Operation Defiant (1955) 137 Operation Desert Storm (1991) 467–9 Operation Duster (sigint flight operations during Yom Kippur War) 295 Operation Gold (1948) 97 Operation Halfmoon (1948) 96 Operation Hem (sigint flight operations during Yom Kippur War) 295 Operation Musketeer (1956) 156–9 Operation Nigeria (against journalists and their sources) 506 Operation Overlord (1944) 59 Operation Pat (Comet sorties over the Baltic) 273 Operation Sanjak (1955) 137–9 Operation Storm (1995) 472–3 Operation Tartan (1955) 136–7 Operation Trail Hammer 536 Orford Ness (Suffolk) 285–7, 322 Organ, Helena see Prime, Helena Orion (sigint satellite) 437 Ormsby Gore, David 206 Orwell, George 549 Oshima, Baron 29 Ottawa (Canada) 57, 85, 92, 94, 97 Over the Horizon Radar 285–7, 322 Owen, Dr David 299–300, 332–3, 360, 391 Padeborn (Germany) 248 Pakistan 323, 334, 384, 513–14, 519, 537 Palestine 97, 109, 155, 156, 320 Paris 21, 25, 52, 53, 158, 194–5, 243, 284–5, 510 Parker-Bowles, Camilla 480, 482 Parliamentary Select Committee on Foreign Affairs 529 Patagonia 393 Patchett, Brian 228–30, 369 Paterson, Brian 507 Pearl, Daniel 514 Pearl Harbor attack (7 December 1941) 29, 290 Peking 150, 151, 194 Pelton, Ronald 384–5, 443–4, 447 Penkovsky, Oleg 322–3 Penney, William 192 Pepper, David 526, 527, 528, 532, 539 Perkar (Ceylon) 160 Perkins, Alice 495 Permanent Secretaries Committee on the Intelligence Services (PSIS) 219–20, 241, 260, 423 Perrin, Ken 267, 270, 363 Peshawar (Pakistan) 384 Petersfield (Hampshire) 133 PGP (Pretty Good Privacy, code-making programme) 490–1 Philby, Kim 37, 82–3, 84–5, 225, 226, 238, 242, 354–5, 367, 385 Philco (telecoms company) 350 Philippines 445 Phillips, Cecil 75, 79 Pilsey Island (Sussex) 140 Pincher, Chapman 17, 226, 238, 239, 240, 242, 386 Pine Gap (Australia) 345 Pinner (Middlesex) 68, 69 Pinochet, Augusto 519 Pirinclik Air Base (Turkey) 301–2, 306 Pither, Judith 383 Plessey (telecoms company) 212, 267–8, 311, 433 PLO (Palestine Liberation Organisation) 277 Poets Systems (Soviet cypher machines) 78, 81 Poland 21–2, 31, 46, 178, 387, 421, 515 Polaris missile system 266, 322, 335, 337, 438–40 Pollard, Jonathan 444 Polyarnoe (Soviet Union) 34, 36 polygraphs 381, 383, 424–6, 433–4, 444 Port Said (Egypt) 156 Port Stanley (Falklands) 390, 397, 413 Portsmouth (Hampshire) 134 Portugal 44 Poseidon (missile system) 439 positive vetting 88, 227–8, 229, 229–30 Posner, Gerald 483 Post Hostilities Planning (PHP) Committee 46, 85 Post Office 241, 286; develops fibre-optic cables 604; Research Department (Dollis Hill) 28, 68, 171, 172, 349; ‘Secret Department’ 14 Potts, Archie 154–5 Poulden, Teddy 93, 94, 352–3, 354 Powell, Jonathan 500 Powers, Gary 8, 201–7, 208, 226 Prague 244; Prague Spring (1968) 387 Prime, Geoffrey 8, 368–86, 423, 424, 425, 444, 447, 600 Prime, Helena 374–5 Prime, Rhona 375, 378–9 Princeton University 350 Prior, James 422 Profumo affair (1963) 8, 226, 228 Project Clipeus (British ADM programme) 249 Project Cobra Shoe (US intelligence station on Cyprus) 323, 348, 356 Project K (NSA HQ) 102 Project Minaret (US illegal monitoring of domestic radicals) 357 Project Sambo (tracking low-frequency submarine radio transmissions) 378 Project Sandra (intelligence facility on Cyprus) 321–3, 348, 356 Public Interest Immunity certificates 505 Public Key Cryptography 489–93, 508, 512 Public Record Office (Kew) 355 Puerto Belgrano (Argentina) 393 Punta Arenas (Chile) 414 Purple (Japanese cypher machine) 29, 38 Purves, Peter 348 Pym, Francis 423 Pyramider satellite 377 Quinlan, Sir Michael 493 Racal (telecoms company) 401, 433, 469, 524, 590 radar 110, 126, 132, 133, 136, 138, 145, 154, 202, 266, 285–7, 301–2, 306, 406, 408, 466 Radcliffe, Lord 239–40 Radcliffe Inquiry into Security in the Civil Service (1962) 381, 418 Radio Corporation of Cuba 341 Radio Operators (GCHQ) 15, 185, 186, 228, 261, 382, 418, 419, 420, 422, 432, 435, 458 Radio Reconnaissance Teams (Afghanistan) 535 Radio Security Service 37, 58, 79, 221 Radio Warfare Special Branch 133, 134 Rainbow Warrior (Greenpeace ship) 446 Rangoon (Burma) 110 Rattan (Soviet radio intercepts) 75 RC-135 ‘Looking Glass’ aircraft 273 Reagan, Ronald 398, 403, 457 ‘Real IRA’ 501, 502 Reenan, Cyril 479, 480 Rees-Mogg, Lord William 481 Reeve, James 196, 197 Regulation of Investigatory Powers Act (RIPA) (2000) 547 Reid, John 516 Reijn, Joop van der 308 Reilly, Patrick 205, 206 rendition programmes 539–40 Rendle, John 578 Rennie, John 156 Res (reserved cypher material) 44–5 Review of Intelligence Requirements and Resources (1994) 493 Review of Intercept as Evidence (2004) 541 Rhodes, Miriam 378 Rhodesia 3, 209 Ribbentrop, Joachim von 31 Richards, Brooks 387 Richards, Francis 504, 511, 526 Riddington, Tony 598 Ridley, Nicholas 392 Rimington, Stella 372, 494, 521 Ring of Five 442–3 Ritter, Scott 470–1 Riyadh (Saudi Arabia) 513 Roake, Alfie 147, 265 Robinson (computer) 349 Robinson, Robin 493 rockets and missiles 5, 108, 110, 131, 169, 201–2, 203, 207, 266, 271, 301, 306, 315, 322–3, 335, 337, 376, 390, 439–40, 510, 511, 515, 525 Rockex (UK cypher machines) 57–8, 194 Rolf, Vic 213 Romania 52, 256, 257, 284; foreign intelligence service (DGIE) 253–4 Rome 372 Rommel, Erwin 5 Roosevelt, Franklin D. 39, 41, 47, 73, 84, 87 Rose, Michael 472, 473, 474 Rosenberg, Ethel and Julius 83 Rosenheim (Germany) 48 Roussilhe, François 254–5 Rowe, Vivian 402 Rowlands, Ted 390, 399–400, 401 Rowlett, Frank 44, 174 Rowntree Foundation 361 Royal Air Force (RAF) 369, 537: 192 Squadron (monitoring aircraft unit) 113, 122, 125, 149, 159; 199 Squadron (radio wafare unit) 113, 125, 131; invited onto Blue Peter children’s programme 348; loss of Avro Lincoln (1953) 125–9, 580; and Malayan Emergency 149–50; near-miss incidents 131; negotiations on air corridors 129–30; 100 Countermeasure Group 112; as part of GC&CS 20; RAF Akrotiri 273, 295, 296, 323, 325; RAF Brampton 469; RAF Brawdy 377; RAF Brize Norton 204, 375; RAF Celle 128; RAF Crail 369; RAF Digby 230, 231, 237; RAF Gatow 112, 370, 383; RAF Habbaniya 155, 161–2, 230; RAF Hammersley Hayes 231; RAF Lakenheath 116, 142; RAF Leconfield 126; RAF Mildenhall 257, 273, 284, 297; RAF North Luffenham 153; RAF Northolt 537; RAF Oakhanger 262; RAF Pergamos 162, 323; RAF Scharfoldendorf 128; RAF Sharjah 271; RAF Strike Command 270; RAF Upper Heyford 457; RAF Watton 112–14, 122, 125, 131, 159; RAF Wythall 153; RAF Wyton 273, 295; ‘Rock Apes’ Regiment 154; sigint and elint operations 110–14, 116–18, 121–2, 124, 131–3, 153, 154, 206, 218–19, 269–70, 272–3, 285–7; Signals Units 153, 154, 161; surveillance operations 537–8; and U-2 overflight programme 202; Y stations in Kent and Cheshire 34, 63, 111 Royal Commission on Criminal Justice Procedure 425–6 Royal Electrical and Mechanical Engineers 499 Royal Marines 390, 391, 394, 402, 411, 413, 524, 535; Y Troop 524, 525, 535 Royal Navy 159, 441, 474, 477; and Buster Crabb incident 140–2; HMS Affray 133; HMS Albion 259; HMS Anderson (sigint station in Ceylon) 69, 92, 93, 94, 160; HMS Antrim 409, 410; HMS Ardent 410; HMS Conqueror 404; HMS Coventry 406; HMS Dolphin 265; HMS Endurance 391–2, 394, 396; HMS Glamorgan 410; HMS Glasgow 406; HMS Hermes 402–3, 411; HMS Invincible 407; HMS Maidstone 139; HMS Mariner 134; HMS Mercury (RN Signals School) 133, 134, 139; HMS Pickle 134; HMS Pucklechurch 133, 134; HMS Sheffield 406; HMS Sir Galahad 400; HMS Superb 259; HMS Taciturn 144–6; HMS Totem (later Dakar) 137, 264, 265; HMS Truculent 133; HMS Truelove 134; HMS Truncheon 264, 265; HMS Turpin 135–9, 140, 143, 146–7, 264; influence on GC&CS 16; intercept sites at Scarborough and Winchester 63; Kipling story involving 13; Provost Branch 139; and radio station at Polyarnoe 34; ‘Room 40’ code-breakers 15; sigint and elint operations 6, 114, 133–9, 143–7, 218–19, 264–7 Royal Radar Establishment (Malvern) 501 Royal Ulster Constabulary (RUC) 501, 502–3; RUC Special Branch 499, 502, 503 Rumsfeld, Donald 511 Rushworth, Edward 48, 78 Russian Mafia 504 Ryolite satellites 345, 346, 376, 421 Sabah (Borneo) 165 Sabri, Naji 530 Sadat, Anwar 296 Sadi, Sener 314 Safford, Laurance 39 Samford, General 101 Samsun (Turkey) 301, 311 San Carlos Water (Falklands) 408–11 San Francisco 92 Sangin province (Afghanistan) 535 Santa Fe (Argentine submarine) 397 Sarafand (Palestine) 20, 32, 155, 162 Sarajevo (Bosnia and Herzegovina) 473, 474 Sarawak 165 Sarell, Sir Roderick 308, 312, 313, 315, 319 Saudi Arabia 164, 467, 468 Saunders, Andrew 458 Savimbi, Joseph 454 Scan Odd (airborne radar) 121 Scarborough (Yorkshire) 63 Scargill, Arthur 416 Scarman, Lord 431 Scarus (portable interception kit) 534 Schlesinger, James 294–5, 326, 329, 330, 332 Schmidt, Hans 21 Schröder, Gerhard 520 Schulze, Reinhard and Sonja 455–6 Scott-Farnie, G.R. 34 SCUD missiles 251, 468, 469 SDECE (French secret intelligence service) 442 Second World War 135, 335; end of 47–50, 59–60; events leading up to 22; and improved communications 5; and release of sigint material 355–6; Russian interceptions in 30, 31–2; sigint and code-breaking in 2, 5, 28–9, 32–46, 250 Secret Intelligence Service (SIS; MI6) 1, 57, 82, 91, 97; agents sent into the Eastern Bloc 123; at Bletchley 23, 27; and Automatic Data Processing 353; and Berlin-Vienna tunnel operations 169–76; and bungled surveillance operations 140–2; buys missiles on the open market 407; closer relationship with MI5 and GCHQ 503–4; considered organisational basket-case 24; and Cyprus radio station 156; and end of influence over sigint 142; and Enigma decypherment 21; funding of 494; move to Broadway Buildings 17; move to Century House (1966) 195; move to Vauxhall Cross 496–7; no trade unions in 417; obsession with Russia 17, 31; origins of 14; and Penkovsky 322–3; and post-war re-absorption of GC&CS 67; recruitment to 61; Section V 37; Section VIII 57–9; Section Y (Carlton Gardens) 171, 178, 372; Technical Collection Service 132; and Yemen 164 Secret Service Committee 15 Security Commission 368–9, 381–2, 384 Security Service (MI5) 1, 57, 182, 361; and Automatic Data Processing 353; Britten affair 237; bugging operations 177; closer relationship with SIS and GCHQ 503–4; and CND 368; fears concerning Communists in trade unions 418–19; funding of 494; interception of telegrams and telexes 239; and John Cairncross 37; and Libyan Embassy affair 456; no trade unions in 417; origins of 14–17; and Peter Wright 223, 224; and polygraph 433–4; and possible sub-agents 382; problems with Orford Ness 287; and sigint security 70–1; ‘Squidgygate’ affair 482; and Venona 79, 84, 85, 86; ‘watchers’ operations 183–90; and West German defections 455–6; Whetstone radio monitoring station 190–1 Selby-Bennett, Harry 134, 139 Selwyn Lloyd, John 128, 158, 159 Semipalatinsk (Soviet Union) 107, 302 Services Liaison Department 70 Sexton, Jamie 305 Seychelles 334, 335 Shanghai 19 Sharq el-Adna (radio station) 156 Shayler, David 521 Shedden, Sir Frederick 86, 92 Sheldon, Robert 459 Shergold, Harry ‘Shergy’ 142 Short, Clare 523–4 Sidewinder air-to-air missiles 441 Sigaba (US cypher machine) 98–9 Sigdasys project (improved flow of sigint to front-line units) 451, 456 Sigint Conference (1946) 95 Sigint Electronic Warfare Operation Centre (Afghanistan) 535 sigint satellites 437–8 sigint ships 259–67 Sigint/EW Operations Centre in Regional Command (South) 534 SIGMod 539 signals intelligence (sigint); in Afghanistan 534–9; airborne 121–2, 125–33, 144, 202–7, 223, 251–2, 257, 267–74, 295, 377; and allied cut-offs 444–7; American 39–40, 143–4, 271–2, 273–4; benefits of 401–2; blue jackets (BJs) 17, 70–1; bugging 176–82; cost of 218–23; Croatian success 473–5; and Cuba 341–2; cypher security 57, 191–3; in Cyprus 320–39; D-Notice affair 238–41; defections from 228–9; dependence on SAS-type activities 250–1; and ‘Dodgies’ or Mystery Trips 6; and domestic/ international blurring 344; during Cold War 1, 5, 8, 108–24, 125–47, 257–8; during WWII 2, 5, 32–46, 57–8; expansion in India 30; failures of 253–5; and Far East 148–51, 164–8; GCHQ at heart of 5–10; German 35, 49–50, 62; global alliances 89–101; ground-based 117–20, 252–3; and Gulf War (1991) 468; in Hong Kong 151–5; importance of bases 151–5, 277–8; and Indonesia-Malaya confrontation 164–8; and invasion of Czechoslovakia 245–6; and invasion of Falklands 397–415; and Iraq War (2003) 525–6; and Kipling 13–14; legalities of 344; and making/influencing of foreign policy 321; in medieval times 4; and Middle East 155–64; modern formation of 58; and political leaders 2–4, 7; and private companies 17; problem of language 512–13; public disclosure of 356–64; rethinking of targets 345; relations between Western allies 444–7; release of wartime material on 355; and rescuing of enemy matériel 47–56; risks 203; and Russians 33–8, 280–1; seaborne 114–16, 133–47, 208, 259–67, 377–8; security disasters 228–38; size of 227–8; and speed of communication 4–5; support for front-line units 449; tactical units 250–2; and Third World 169; in Turkey 300–19, 330–1; value and importance of 60, 62–71 Signals Intelligence Centre 93 Signals Intelligence Service (USA) 74 Sillitoe, Sir Percy 86, 190 Silvey, Reg 412 Simakov, Alexander 478–9 Simkin, Anthony 187 Sinclair, Hugh ‘Quex’ 16, 22, 23 Sinclair, Sir John 142 Sinews (Sigint NEW Systems) 496 Singapore 19, 40, 96, 164, 166, 167 Singleton, Valerie 348 Sinkov Mission (1941) 39 Sinn Féin 500 Sinop (Turkey) 301 Six-Day War (1967) 253, 263–4, 271, 284 Skardon, William 87, 188 Skynet (communications satellite) 347–8, 403, 408, 438 Slessor, John 190–1 Slim, Field Marshal William 65 Sly, Ken 153–4, 375 Smallwood, Sir Denis 271 Smith, F.M. 302 Smith, Ian 3 Smith, Jack 151 Smith, Jacqui 543 Smith, Rupert 474–5 Smiths Industries 495 Snow, Leading Seaman ‘Snowy’ 135 social intelligence 178–9 Solidarity (Polish trade union) 432, 465 Somerville, John 121, 317–18, 419, 420, 428 Sony 480–1 Soothsayer (Army intercept equipment) 537 SOSUS (undersea microphones) 377 South Africa 209, 446, 454 South Georgia 390, 391, 393–6, 409 South-East Asia Command 110 Southern Thule 389, 390–1 Soviet Air Force 118, 119, 360; Air Defence Command 201; Strategic Air Command 256; Strategic Rocket Force 256 Soviet Army 175, 371; General Staff 255–6 Soviet Communist Party 19, 368 Soviet Navy 114–16, 133, 256, 301; Naval Intelligence 73; Northern Fleet 136 Soviet Union 33–8, 336, 349; apparent war preparations 255–7; and Berlin-Vienna tunnel operations 169–76; and biological weapons 611; capture of German cryptographic assets 50–1; Cold War espionage 8; elint on invasion of the Falklands 401; end of Cold War 493; enters WWII 28; ‘ferret’ programmes 112; Hitler’s invasion of 29, 32–3, 290; invasion of Czechoslovakia 244–7; Italian code-breaking concerning 52, 54; nuclear weapons 107–8, 112, 114, 116; and post-war confrontation 47; raid on Arcos building 18; Red Army 46, 78, 245–6, 249, 319; release of UK intelligence material 355; secret submarine missions against 6; and ‘strayed’ aircraft 126–33; successful sigint operations against 279–81, 344, 361; Turkish (Anglo-US) operations against 301–2; UK-US obsession with 17–19, 30–2, 45–6, 321–3; and Venona Project 72–88; and Yom Kippur War 291 Spain 44, 505, 533 Special Branch 141, 150, 151, 166, 187, 453, 456, 459, 509 Special Liaison Units 57–8 Special Radio Installation Flight (SRIF) 114 Spedding, David 494 spy planes 257, 267–74, 292–3, 296–7, 538 ‘Squidgygate’ affair (1990) 479–82 SR-71 Blackbird Mach 3 reconnaissance aircraft 284, 292–3, 296–7 Stalin, Joseph 31, 33, 46, 47, 173 Standard Cable & Wireless Ltd 17 Standard Telegraph & Cable Ltd 342 Stankovic, Milos 473 Stanmore (Middlesex) 62, 68 Stannard, Robert ‘Fred’ 210–11, 213, 218, 242 Starmer, Keir 543 State Research Association 361 stay-behind patrols 247–50 Stella Polaris (sale of Russian codebooks) 91 Stephanie operation (Canadian embassy intercepts in Moscow) 280–1 Stephenson, Sir Hugh 207, 221 Stevens, Geoffrey 40, 45, 50, 94 Stewart, Brian 353 Stewart, Michael 228 Stockholm 192 Straw, Jack 505, 519 Stripp, Alan 109 submarines 6, 114–17, 125, 133–9, 142–7, 197, 259, 264–7, 337, 377–8, 384, 397, 404 Suez Crisis (1956) 156–9, 160, 181, 182, 213 Sugar (Vienna tunnel code) 171 Sugar Grove (West Virginia) 262 Suharto, President 168 Sukarno, President 164, 165, 167–8 Sunay, Cevdet 311 Super Antelope programme (modernising/upgrading Polaris submarines) 337 Supreme Allied Commander Europe (SACEUR) 256 surveillance operations 4, 183–90, 197, 201–7, 208–9, 247–53, 292–3, 295, 296–7, 322, 368, 406, 421, 472, 480–1, 500, 506, 537–8, 540–50 SUSLO (Special United States Liaison Officer based in UK) 381 Sutton Common (Cheshire) 500 Sweden 31, 212, 214, 269 Switzerland 52, 212, 214, 215, 457, 492 Sykes, Richard 297, 298, 335, 593 Syria 156, 157, 271, 291, 300, 301–2, 304, 308, 336, 344 Tai Mo Shan (New Territories) 154 Taipei 195 Taiwan 152, 195, 323 Taliban 535, 537 Tanzania 511 Taper (Soviet cypher traffic) 54, 108 Tartus (Syria) 331 TASS News Agency 190 Taylor, Telford 43 Tebbit, Kevin 498, 504 Technical Committee of London Signals Intelligence Committee 267 Technical Radio Interception Committee 131 Tedder, Lord 5 Tel Aviv 157–8, 180 telephone tapping and intercepts 170–6, 180, 244–5, 299, 340, 341–6, 376, 377, 474–5, 479–83, 486, 499, 500–1, 523, 541–5 Tempest (radiation/emanation phenomenon) 209, 215–18 Templer, Sir Gerald 150, 219 terrorists, terrorism 9, 168, 277, 307, 320–1, 452, 531; and 9/11 509–15; domestic 539; and Heathrow plot (2003) 515–16; and IRA 498–503; Libyan 455–8; see also kidnapping and hostage-taking Teufelsberg (Germany) 478 Thatcher, Margaret 8; and Falklands conflict 298, 396, 400, 403–4; and mole-mania 363, 367; 1987 general election 433; obsession with secrecy 492; and polygraph 434; and removal of trade unions from GCHQ 415, 416–17, 423, 425, 426, 427, 428, 429, 430–1, 435; and tightening of the Official Secrets Act 363; and Zircon project 442, 460 Third World 203, 259, 334 Thistlethwaite, Dick 255 Thomas, Richard 544 Thomas, Teddy 234 Thompson, Julian 402, 410–12 Thompson, Ralph 94 Thompson-CSF (arms company) 489 Thomson, Mike 131 Thorneycroft, Peter 163 Thorpe, Peter 535 Tiananmen Square massacre (1989) 476 Tickell, Crispin 290 TICOM (Target Intelligence Committee) teams 48–56, 76, 78 Tiltman, John 19, 31–2, 42, 44, 67, 78, 79, 96, 213 Tirpitz (German battleship) 35 Titchner, Lambert 186 Tito, Josip 4 Tomlinson, Richard 521 Tonkin, Derek 330, 333 Tornado Multi-Role Combat Aircraft 345 Toumlin, George 432 Tovey, Brian 167, 414, 415, 421–2, 423, 424, 428, 433, 442, 448, 461, 490 trade unions 317, 368, 389, 416–36, 497–8 Trades Union Congress (TUC) 416, 417, 419, 426, 427, 509 Travis, Edward 27, 28, 36, 43, 48, 49, 53, 56, 60, 67–9, 69, 92, 94, 101, 121 Trawlerman (DIS computer scheme) 527–8 Trend, Burke 221, 240, 241, 242, 269–70, 288, 322–3, 354, 364 Trevor-Roper, Hugh 221 Tromsø 134 Truman, Harry S. 73, 85, 91, 101, 108, 109, 116 TRW Inc (telecoms company) 377 Tryst operation (British Embassy intercepts in Moscow) 280–1 ‘Tunny’ (German cypher machine) 28, 349 Turing, Alan 2, 25, 27, 349, 492 Turkey 52, 109, 131–2, 157, 268, 269, 299–319, 325–8, 330–1, 334, 338, 357, 423, 472; Air Force 312–13, 313; Army 315; Foreign Ministry 312–13 Turkish People’s Liberation Army (TPLA) 300, 303–19 Turkish People’s Liberation Front (TPLF) 300, 308–10, 312 Turnbull, Andrew 524 Turner, Charles 312–16, 318 TUSLOG (US Logistics Organisation in Turkey) 302 Tuxedo (British nuclear weapons stockpile in Cyprus) 163 25 Mayo (Argentine aircraft carrier) 404 Typex (UK cypher machine) 56, 98 Tyuratam (Soviet Union) 306 U-2 spy planes 142, 226, 292, 296, 332, 471 UK-USA Technical Conference (1946) 95 Ukraine 472, 533 UKUSA (UK-USA signals intelligence agreements) 7, 213, 241, 273, 376, 577; combined comsec/sigint agencies 242; and deterioration of Anglo-US relationship 285; development of 89–95; and elint 111; existence of 1948 aagreement 577; and GCHQ 95–9, 222; and Hong Kong 152; and Israel 471; and Korea 99–101; and satellite collection 437–8; second-party members 444, 447; standardisation of equipment in 424; third-party members 209, 447, 452; and tightening of security 381; value of British Empire to 149 Ultra (WWII decrypts) 1, 24, 26, 32–8, 41, 42, 43, 57, 59, 60, 62, 72–3, 113, 354, 362, 363 Underwater Development Establishment 145 Unit 8200 (Israel sigint agency) 470 United Nations 66, 295, 336, 445–6, 472, 523–4; Monitoring, Inspection and Verification Commission 520; Protection Force 472; Security Council 517, 522; Security Council Resolution 1373 511–12; Special Commission (UNSCOM) 470–1 United States; and Cold War espionage 8; Communications Intelligence Board 97, 152; cyphers worked on by GC&CS 17, 29; Department of Defense 295; Division of Scientific Intelligence 322; Europe Command 180; Foreign Intelligence Advisory Board 263; Information Service 305; National Photographic Intelligence Center 296; National Reconnaissance Office 449, 458; National Security Council 334; and proposed German-Mexican alliance 15; and UKUSA intelligence treaty 89 University of Pennsylvania 426 Unye (Turkey) 313, 316 US Air Force 96, 101, 129, 152; 47th Radio Squadron 118; Griffiss Air Force Base (New York) 292; Johnson Air Force Base (North Carolina) 293; Security Service 118, 120, 301; Strategic Air Command 272 US Army 39, 40, 42, 43, 44, 52, 74–5, 77, 91, 94, 99, 102, 336, 413, 474; Intelligence Support Activity 452; Marines 525; Security Agency 99, 152, 302, 345–6; Seventh Army Corps 467; Special Forces 249; US Army Air Force 110–11 US Navy 39, 40, 42, 43, 75, 91, 97, 99, 143, 207; US Naval Intelligence 157; Radio Research Station Program 262; Security Group 115, 301; Sixth Fleet 323–4; USS Belmont 260; USS Cochino 112–17, 135; USS Georgetown 260; USS Jamestown 260; USS Liberty 260, 263–4; USS Muller 260; USS Oxford 260; USS Pueblo 260, 264; USS Stickleback 143; USS Tusk 114–15; USS Valdez 260, 605; USS Vincennes 408 USM-49 (US sigint base in Turkey) 303 Vampire (UK intercept unit) 474, 534 ‘Vasiley’ (KGB officer) 232–4 Vass, Sir Douglas 423 Vassall, John 226, 238 Vatican 52 Venona project (intercepted Russian messages) 445–6; and Anglo-American collaboration 72, 78–80; and British Commonwealth 85–8; exploitation of reprinted pages 74–5; and exposure of agents 80–8; extreme secrecy of 73, 77–8; first code-breaks 75–6; and global sigint 90, 94, 98; and Manhattan Project 76; size and importance of 72–3; Soviets alerted to work on 73, 80–1 Vernon, Mike 422, 423 Viehoff (Germany) 50 Vienna 169, 170–1, 172, 372, 373, 375, 376 Vienna Summit (1961) 180 Vietnam 153, 167, 168, 178, 203, 376, 446 Vietnam War 123, 243, 252, 269, 271–2, 277, 279–80, 298, 356, 387 Virgin 545 Vladivostok 129 Voice of Egypt (radio station) 156 Wait, Dave 385–6 Wal Bin Chang 153 Waldegrave, William 429 Walker, John 264, 377, 384, 447 Walker, Walter 165, 166 War Office 22 War on Terror 533, 539–40 Warsaw Pact 114, 244, 245, 247, 248, 251, 253, 257–8, 319, 321, 369, 402, 465 Washington 7, 38, 39, 40, 41, 42, 43, 44, 45, 47, 57, 64, 74, 77, 82, 83, 90, 92, 96, 97, 99, 101, 102, 111, 119, 121, 143, 151, 157, 203, 205, 212, 243, 253, 292, 325, 329, 335, 355–6, 381, 413 Watchkeeper 450 drone 536 Watergate House (London) 15–16 Watergate scandal (1973) 4, 279, 288, 290, 293, 297, 298, 325–6, 356 Wavendon Manor (radio station, Buckinghamshire) 49 weapons of mass destruction (WMD) 516, 520, 523, 526, 528–31 Weatherill, Bernard 459 Weinberger, Casper 441 Weisband, William 80–1, 169 Welchman, Gordon 25, 26, 27, 43, 57, 61, 64, 65, 362–3, 364, 387 Wenger, Joseph 42, 53, 79, 95, 243 West Germany 345, 442, 447–9, 455–6 West Irian 167 West, Lord 544 West, Nigel 88 Western Union 240 Whaddon Hall (Buckinghamshire) 23, 57, 181 Wharfe, Ken 483 White, Ray 501 White, Sir Dick 142, 176, 181, 187, 225, 241–2, 243, 245, 246, 264, 285–6, 353, 354, 364, 453 Whitelaw, Willie 404, 426, 427 Wieck, George 214 Wiesbaden (Germany) 158 Wigg, George 227–8, 240 Wilkes, Detective Sergeant 378 Wilkinson, Peter 206 Williams, Sir Anthony 392–3 Wilson, Edmund 42, 54, 57, 68, 576 Wilson, Harold 225; and Anglo-US relations 356–7; antagonism towards the press 239, 242; and Chevaline project 440; and Cyprus problem 325, 329; and Diego Garcia 338; fascinated and terrified by intelligence and espionage 3, 168, 226–7, 357; and Radcliffe Committee 239–40; and Skynet 438; and U-2 flights from Cyprus 295–6; and Vietnam War 277 Wilson, Jim 292 Wilson, Richard 527 Winnifrith, John 418 Winterbotham, Frederick 35, 354 Wolfenden, Jack 383 Woodward, Admiral Sandy 402–3, 407, 408, 410–11 Wormwood Scrubs prison 238, 385–6 Wreford-Brown, Christopher 404–5 Wright, Georgina 317 Wright, Peter 216, 223, 224, 267, 363, 492, 538, 587–8 Wyllie, Sean 490 Y services (armed forces listening units) 26–7, 33–5, 63, 68, 103, 111, 117, 411 Yarallakos (Cyprus) 320, 328 Yardley, Herbert O. 38 Yemen 148, 163–4 Yom Kippur War (1973) 277, 290–5, 320, 337, 387 York, Duchess of 482 Young, Courtney 86 Yugoslavia 256, 257, 284, 471–5, 503, 512, 534 Yunnan (China) 151 ‘Yuri’ (KGB officer) 231–3 ‘Zhora’ (Weisband’s code name) 80–1 Zimmermann, Phil 490–1 Zimmermann Telegram (1917) 15 Zinnia (missile-detection system) 322–3 Zinser, Aguilar 519–20 Zionist movement 97, 109 Zircon project (GCHQ sigint satellite) 415, 438, 442–3, 449–50, 458–61 Acknowledgements On 9 December 1993 the Lord Chancellor, Lord Mackay of Clashfern, introduced the Intelligence Services Act in the House of Lords.
Everything Is Obvious: *Once You Know the Answer by Duncan J. Watts
active measures, affirmative action, Albert Einstein, Amazon Mechanical Turk, Black Swan, business cycle, butterfly effect, Carmen Reinhart, Cass Sunstein, clockwork universe, cognitive dissonance, coherent worldview, collapse of Lehman Brothers, complexity theory, correlation does not imply causation, crowdsourcing, death of newspapers, discovery of DNA, East Village, easy for humans, difficult for computers, edge city, en.wikipedia.org, Erik Brynjolfsson, framing effect, Geoffrey West, Santa Fe Institute, George Santayana, happiness index / gross national happiness, high batting average, hindsight bias, illegal immigration, industrial cluster, interest rate swap, invention of the printing press, invention of the telescope, invisible hand, Isaac Newton, Jane Jacobs, Jeff Bezos, Joseph Schumpeter, Kenneth Rogoff, lake wobegon effect, Laplace demon, Long Term Capital Management, loss aversion, medical malpractice, meta analysis, meta-analysis, Milgram experiment, natural language processing, Netflix Prize, Network effects, oil shock, packet switching, pattern recognition, performance metric, phenotype, Pierre-Simon Laplace, planetary scale, prediction markets, pre–internet, RAND corporation, random walk, RFID, school choice, Silicon Valley, social intelligence, statistical model, Steve Ballmer, Steve Jobs, Steve Wozniak, supply-chain management, The Death and Life of Great American Cities, the scientific method, The Wisdom of Crowds, too big to fail, Toyota Production System, ultimatum game, urban planning, Vincenzo Peruggia: Mona Lisa, Watson beat the top human players on Jeopardy!, X Prize
Common sense is so ordinary that we tend to notice it only when it’s missing, but it is absolutely essential to functioning in everyday life. Common sense is how we know what to wear when we go to work in the morning, how to behave on the street or the subway, and how to maintain harmonious relationships with our friends and coworkers. It tells us when to obey the rules, when to quietly ignore them, and when to stand up and challenge the rules themselves. It is the essence of social intelligence, and is also deeply embedded in our legal system, in political philosophy, and in professional training. For something we refer to so often, however, common sense is surprisingly hard to pin down.3 Roughly speaking, it is the loosely organized set of facts, observations, experiences, insights, and pieces of received wisdom that each of us accumulates over a lifetime, in the course of encountering, dealing with, and learning from, everyday situations.
NurtureShock: New Thinking About Children by Po Bronson, Ashley Merryman
affirmative action, Columbine, delayed gratification, desegregation, hedonic treadmill, impulse control, index card, job satisfaction, lake wobegon effect, longitudinal study, meta analysis, meta-analysis, randomized controlled trial, social intelligence, Steven Pinker, telemarketer, theory of mind
Rather, many acts of aggression require highly attuned social skills to pull off, and even physical aggression is often the mark of a child who is “socially savvy,” not socially deviant. Aggressive kids aren’t just being insensitive. On the contrary, says Cillessen, the relationally aggressive kid needs to be extremely sensitive. He needs to attack in a subtle and strategic way. He has to be socially intelligent, mastering his social network, so that he knows just the right buttons to push to drive his opponent crazy. Aggression comes as “early adolescents are discovering themselves. They’re learning about coolness—how to be attractive to other people.” This completely changes the game for parents. When parents attempt to teach their seven-year-old daughter that it’s wrong to exclude, spread rumors, or hit, they are literally attempting to take away from the child several useful tools of social dominance.
Reinventing Discovery: The New Era of Networked Science by Michael Nielsen
Albert Einstein, augmented reality, barriers to entry, bioinformatics, Cass Sunstein, Climategate, Climatic Research Unit, conceptual framework, dark matter, discovery of DNA, Donald Knuth, double helix, Douglas Engelbart, Douglas Engelbart, en.wikipedia.org, Erik Brynjolfsson, fault tolerance, Fellow of the Royal Society, Firefox, Freestyle chess, Galaxy Zoo, Internet Archive, invisible hand, Jane Jacobs, Jaron Lanier, Johannes Kepler, Kevin Kelly, Magellanic Cloud, means of production, medical residency, Nicholas Carr, P = NP, publish or perish, Richard Feynman, Richard Stallman, selection bias, semantic web, Silicon Valley, Silicon Valley startup, Simon Singh, Skype, slashdot, social intelligence, social web, statistical model, Stephen Hawking, Stewart Brand, Ted Nelson, The Death and Life of Great American Cities, The Nature of the Firm, The Wisdom of Crowds, University of East Anglia, Vannevar Bush, Vernor Vinge
 Tommaso Dorigo. So was the rumor more than just a rumor, or was it a honest rumor? A Quantum Diaries Survivor (blog), July 17, 2010. http://www.science20.com/quantum_diaries_survivor/so_was_rumor_ more_just_rumor_or_was_it_honest_rumor.  Robert Dougans and David Allen Green. Virtual veracity. The Lawyer, July 5, 2010.  K. Eric Drexler. Hypertext publishing and the evolution of knowledge. Social Intelligence, 1:87–120, 1991.  Jason Dyer. A gentle introduction to the Polymath Project. The Number Warrior (blog), March 25, 2009. http://numberwarrior.wordpress.com/2009/03/25/a-gentle-introduction-to-the-polymath-project/.  David Easley and Jon Kleinberg. Networks, Crowds, and Markets. Cambridge: Cambridge University Press, 2010.  Nature editorial. Dreams of flu data. Nature, 440:255–256, March 16, 2006
Groundswell: Winning in a World Transformed by Social Technologies by Charlene Li, Josh Bernoff
business process, call centre, centre right, citizen journalism, crowdsourcing, demand response, Donald Trump, estate planning, Firefox, John Markoff, Kickstarter, knowledge worker, Silicon Valley, skunkworks, social intelligence, Tony Hsieh
Scaling-and-optimizing-stage companies don’t just embrace the idea of social applications, they typically have a formalized process for getting them started, integrating them into the company’s other programs, and measuring their impact. Social applications generate data—a lot of it. Coordinating-stage companies use the data to improve social applications. Scaling-and-optimizing-stage companies collect the data and use it to develop social intelligence—a peek into the zeitgeist around a brand or company. Zach Hofer-Shall, Forrester’s expert on social listening, cites the example of Intel, which monitors online conversations across many social channels to gain customer insights. Intel uses this information to craft marketing and product strategy and to engage more intelligently with its developer community. Even though listening is the easiest objective, gathering masses of social data across applications and turning it into actionable intelligence is challenging.
Forty Signs of Rain by Kim Stanley Robinson
bioinformatics, business intelligence, double helix, experimental subject, Intergovernmental Panel on Climate Change (IPCC), phenotype, prisoner's dilemma, Ronald Reagan, social intelligence, stem cell, the scientific method, zero-sum game
We grew so fast we can hardly fit through the birth canal these days. All that growth from trying to understand other people, the other sex, and look where we are. ANNA WAS pleased to see Frank back in the office, brusque and grouchy though he was. He made things more interesting. A rant against oversized pickup trucks would morph into an explanation of everything in terms of yes or no, or a discussion of the social intelligence of gibbons, or an algebra of the most efficient division of labor in the lab. It was impossible to predict what he would say next. Sentences would start reasonably and then go strange, or vice versa. Anna liked that. He did, however, seem overly impressed by game theory. “What if the numbers don’t correspond to real life?” she asked him. “What if you don’t get five points for defecting when the other person doesn’t, what if all those numbers are off, or even backward?
Only Humans Need Apply: Winners and Losers in the Age of Smart Machines by Thomas H. Davenport, Julia Kirby
AI winter, Andy Kessler, artificial general intelligence, asset allocation, Automated Insights, autonomous vehicles, basic income, Baxter: Rethink Robotics, business intelligence, business process, call centre, carbon-based life, Clayton Christensen, clockwork universe, commoditize, conceptual framework, dark matter, David Brooks, deliberate practice, deskilling, digital map, disruptive innovation, Douglas Engelbart, Edward Lloyd's coffeehouse, Elon Musk, Erik Brynjolfsson, estate planning, fixed income, follow your passion, Frank Levy and Richard Murnane: The New Division of Labor, Freestyle chess, game design, general-purpose programming language, global pandemic, Google Glasses, Hans Lippershey, haute cuisine, income inequality, index fund, industrial robot, information retrieval, intermodal, Internet of things, inventory management, Isaac Newton, job automation, John Markoff, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, Joi Ito, Khan Academy, knowledge worker, labor-force participation, lifelogging, longitudinal study, loss aversion, Mark Zuckerberg, Narrative Science, natural language processing, Norbert Wiener, nuclear winter, pattern recognition, performance metric, Peter Thiel, precariat, quantitative trading / quantitative ﬁnance, Ray Kurzweil, Richard Feynman, risk tolerance, Robert Shiller, Robert Shiller, Rodney Brooks, Second Machine Age, self-driving car, Silicon Valley, six sigma, Skype, social intelligence, speech recognition, spinning jenny, statistical model, Stephen Hawking, Steve Jobs, Steve Wozniak, strong AI, superintelligent machines, supply-chain management, transaction costs, Tyler Cowen: Great Stagnation, Watson beat the top human players on Jeopardy!, Works Progress Administration, Zipcar
Therefore, the question of “what are you paid for” should be reexamined as well. The authors of the Oxford study we referenced earlier—the one that says 47 percent of U.S. jobs are about to go the way of the passenger pigeon—manage to conclude their report with a ray of hope. They predict that “occupations that involve complex perception and manipulation tasks, creative intelligence tasks, and social intelligence tasks are unlikely to be substituted by computer capital over the next decade or two.” Although we could debate the 47 percent conclusion (and how it will translate to actual jobs lost), that sounds right to us, and we’ll amplify it a bit further. Work that involves courage and counterintuitive ideas won’t be taken away from humans. People will still be uniquely able to inspire other people to act, and they will still have a monopoly on empathy, diplomacy, and ambition.
Global Catastrophic Risks by Nick Bostrom, Milan M. Cirkovic
affirmative action, agricultural Revolution, Albert Einstein, American Society of Civil Engineers: Report Card, anthropic principle, artificial general intelligence, Asilomar, availability heuristic, Bill Joy: nanobots, Black Swan, carbon-based life, cognitive bias, complexity theory, computer age, coronavirus, corporate governance, cosmic microwave background, cosmological constant, cosmological principle, cuban missile crisis, dark matter, death of newspapers, demographic transition, Deng Xiaoping, distributed generation, Doomsday Clock, Drosophila, endogenous growth, Ernest Rutherford, failed state, feminist movement, framing effect, friendly AI, Georg Cantor, global pandemic, global village, Gödel, Escher, Bach, hindsight bias, Intergovernmental Panel on Climate Change (IPCC), invention of agriculture, Kevin Kelly, Kuiper Belt, Law of Accelerating Returns, life extension, means of production, meta analysis, meta-analysis, Mikhail Gorbachev, millennium bug, mutually assured destruction, nuclear winter, P = NP, peak oil, phenotype, planetary scale, Ponzi scheme, prediction markets, RAND corporation, Ray Kurzweil, reversible computing, Richard Feynman, Ronald Reagan, scientific worldview, Singularitarianism, social intelligence, South China Sea, strong AI, superintelligent machines, supervolcano, technological singularity, technoutopianism, The Coming Technological Singularity, Tunguska event, twin studies, uranium enrichment, Vernor Vinge, War on Poverty, Westphalian system, Y2K
The heritability of i Q has received a great deal of attention, but a recent meta-analysis estimates broad heritability of IQ to be 0.5 and narrow heritability (the component of heritability that measures selectable phenotypic variation) to be as low as 0.34 (Devlin et al., 1997). But IQ is only one aspect of human intelligence, and other aspects of intelligence need investigation. Daniel Goleman has proposed that social intelligence, the ability to interact with others, is at least as important as I Q (Goleman, 1995 ), and Howard Gardner has explored multiple intelligences ranging from artistic and musical through political to mechanical (Gardner, 1993). All of us have a different mix of such intelligences. To the extent that genes contribute to them, these genes are likely to be polymorphic - that is, to have a number of alleles, each at appreciable frequency, in the human population.
104, 107 small interfering RNA (siRNA) technology 465 smallpox 291, 292, 294, 296 bioterrorism threat 457-8, 467 pandemic 1 520-1527 290 smallpox vaccination, health workers 473 Smart, ) . 80 smart weapons 488 social disruption 1, 19-20, 366-7, 375 after nuclear war 389 as consequence of molecular manufacturing 492 evolutionary consequences 5 5 i n existential disasters 369-72 after volcanic super-eruptions 2 1 3 social growth 364-6 social impact bioterrorism 467-8 nuclear terrorism 430-1 social intelligence 62 socialism, millenialism 74 societies 363-4 disaster policy 372-5 'soft' oversight of biotechnology research 462 solar activity, relationship to global warming 250- 1 , 258 solar evolution 34, 44 solar extinction 245 solar flares 239, 242-3, 258 damage to ozone layer 246 solar forcing of climate 268-9 solar luminosity changes 238-42 global warming 243-4 solar wind 250 sophistication effect 100 South Asia nuclear war risk 390 predicted death toll 388 Soviet nuclear weapons, possible terrorist acquisition 421 Soviet Union, totalitarianism 505, 506, 507 stability 507-8 Soviet Union disintegration, nuclear threat 406 Spaceguard project 14 Spanish flu 16, 290 re-synthesis of virus 450, 459-60 551 sparse information 105 Spearman's g 3 1 3 species metaphors, AI 3 3 0 , 3 3 3 Sprinzak, E. 439 stability, totalitarianism 506-10 stagnation, as result of global governance 494 Stalin 506, 507, 508 START agreements 382 starvation, causal factors 7 'Star Wars' anti-missile system 381 state complicity, nuclear terrorism 423-5 Steinbruner, J. et a!.
Broke: How to Survive the Middle Class Crisis by David Boyle
anti-communist, banking crisis, Berlin Wall, Big bang: deregulation of the City of London, Bonfire of the Vanities, bonus culture, call centre, collateralized debt obligation, corporate raider, Credit Default Swap, credit default swaps / collateralized debt obligations, deindustrialization, delayed gratification, Desert Island Discs, Eugene Fama: efficient market hypothesis, eurozone crisis, Fall of the Berlin Wall, financial deregulation, financial independence, financial innovation, financial intermediation, Francis Fukuyama: the end of history, Frederick Winslow Taylor, housing crisis, income inequality, Jane Jacobs, job satisfaction, Kickstarter, knowledge economy, knowledge worker, market fundamentalism, Martin Wolf, mega-rich, mortgage debt, Neil Kinnock, Nelson Mandela, new economy, Nick Leeson, North Sea oil, Northern Rock, Occupy movement, off grid, offshore financial centre, pension reform, pensions crisis, Plutonomy: Buying Luxury, Explaining Global Imbalances, Ponzi scheme, positional goods, precariat, quantitative easing, school choice, Slavoj Žižek, social intelligence, too big to fail, trickle-down economics, Vanguard fund, Walter Mischel, wealth creators, Winter of Discontent, working poor
In a New York Times column, David Autor and David Dorn looked at the process of replacing careers with technology, even now the jobs of high-income workers, such as professional managers, engineers and consultants. They argued that 47 per cent of 700 occupation types in the USA are now at risk from automation, thanks to the emergence of big data and advanced sensors, which give robots better senses and dexterity, so that they can perform a broader scope of non-routine manual tasks. Algorithms for big data are already taking over tasks which rely on recognising patterns. Autor and Dorn suggest that the way to avoid this fate is to choose to train for careers that require creativity and social intelligence. But then how do you earn enough to get a roof over your head in some parts of the UK? But in the cacophony of figures about our battered economy, we are going to have to look beyond all this to see what is really happening. Because that is hard to discern sometimes, with all the talk of a ‘booming’ southern England and a struggling northern England. The unbalanced economy, which seems to get more unbalanced with every month that passes, has sucked the enterprise out of the north, leaving it with a constrained, shrinking public sector.
The Problem With Work: Feminism, Marxism, Antiwork Politics, and Postwork Imaginaries by Kathi Weeks
basic income, call centre, cognitive dissonance, collective bargaining, conceptual framework, deskilling, feminist movement, financial independence, Ford paid five dollars a day, Francis Fukuyama: the end of history, glass ceiling, late capitalism, low-wage service sector, means of production, moral panic, new economy, New Urbanism, occupational segregation, pink-collar, post-work, postindustrial economy, profit maximization, Shoshana Zuboff, social intelligence, two tier labour market, union organizing, universal basic income, wages for housework, women in the workforce, zero-sum game
Postone describes this as a model of immanent critique—in this case, a critique of the work society from the perspective of the emergent possibility of a social form in which work does not serve as the primary force of social mediation (1996, 49), an antiwork critique grounded in a postwork potential. The refusal of work as both a practical demand and a theoretical perspective presupposes an appreciation of the potentially immense productive power of the accumulated capacities of social labor. “What we want,” explains another autonomist, Franco Berardi (“Bifo”), “is to apply, totally and coherently, the energies and the potential that exist for a socialized intelligence, for a general intellect. We want to make possible a general reduction in working time and we want to transform the organization of work in such a way that an autonomous organization of sectors of productive experimental organization may become possible” (1980, 157–58). This affirmation of the creative powers of social labor notwithstanding, the refusal of work does not simply replicate the productivist glorification of work (even socialist or unalienated work).
50 Psychology Classics by Tom Butler-Bowdon
1960s counterculture, Albert Einstein, cognitive dissonance, conceptual framework, corporate governance, delayed gratification, fear of failure, feminist movement, global village, invention of the printing press, Isaac Newton, lateral thinking, Mikhail Gorbachev, Milgram experiment, Necker cube, Ronald Reagan, social intelligence, Steven Pinker, The Bell Curve by Richard Herrnstein and Charles Murray, Thomas Kuhn: the structure of scientific revolutions
Men are happier in marriage when their wives look good and provide “services,” while women seem happier if their husband was affectionate on the day they answered the questionnaire! Given men’s inclination to “roam,” the success of marriage as an institution, Moir and Jessel suggest, is a triumph of the female brain: “Power, in any state, depends on the possession of information. In the married state, women have more of it.” Marriage works not because women become subservient, but because women’s social intelligence enables the relationship to be well managed. Men and women at work The priority that women give to personal relationships tends to rule out the egocentricity, obsession with success, ruthlessness, and “suspension of personal values” that can characterize a man’s approach to his career. A woman’s brain is programmed to find fulfillment in whatever role she does above and beyond some external perception of status, achievement, or success.
An Optimist's Tour of the Future by Mark Stevenson
23andMe, Albert Einstein, Andy Kessler, augmented reality, bank run, carbon footprint, carbon-based life, clean water, computer age, decarbonisation, double helix, Douglas Hofstadter, Elon Musk, flex fuel, Gödel, Escher, Bach, Hans Rosling, Intergovernmental Panel on Climate Change (IPCC), Internet of things, invention of agriculture, Isaac Newton, Jeff Bezos, Kevin Kelly, Law of Accelerating Returns, Leonard Kleinrock, life extension, Louis Pasteur, low earth orbit, mutually assured destruction, Naomi Klein, off grid, packet switching, peak oil, pre–internet, Ray Kurzweil, Richard Feynman, Rodney Brooks, self-driving car, Silicon Valley, smart cities, social intelligence, stem cell, Stephen Hawking, Steven Pinker, Stewart Brand, strong AI, the scientific method, Wall-E, X Prize
But it’s the next step where Cynthia comes into her own. Make it social. Or to put it another way, make some of its reactions ‘social’ reactions. So, for example, if someone gets too close to the robot, not only does it back away, it might express its annoyance at having its personal space invaded with a grimace or sound of disapproval. In these examples the robot responds directly to something you do. But Cynthia is striving for a robotic social intelligence that takes things into a whole new realm, responding to something you think, where the robot perceives something of your mental state from the way you are acting, perhaps understanding if you are sad, happy or confused – or working out that you believe something different to it. She admits we’re a long way off achieving anything that looks like this in a robot although in certain highly controlled conditions Leo has been able to work out that a researcher believes an object is in one box, even though Leo knows it’s in another, a version of something psychologists call the ‘false belief test.
Priceless: The Myth of Fair Value (And How to Take Advantage of It) by William Poundstone
availability heuristic, Cass Sunstein, collective bargaining, Daniel Kahneman / Amos Tversky, delayed gratification, Donald Trump, East Village, en.wikipedia.org, endowment effect, equal pay for equal work, experimental economics, experimental subject, feminist movement, game design, German hyperinflation, Henri Poincaré, high net worth, index card, invisible hand, John von Neumann, Kenneth Arrow, laissez-faire capitalism, Landlord’s Game, loss aversion, market bubble, mental accounting, meta analysis, meta-analysis, Nash equilibrium, new economy, Paul Samuelson, payday loans, Philip Mirowski, Potemkin village, price anchoring, price discrimination, psychological pricing, Ralph Waldo Emerson, RAND corporation, random walk, RFID, Richard Thaler, risk tolerance, Robert Shiller, Robert Shiller, rolodex, social intelligence, starchitect, Steve Jobs, The Chicago School, The Wealth of Nations by Adam Smith, ultimatum game, working poor
In turn, a reasonable proposer should anticipate that and offer a token amount, in blissful confidence of its being accepted. That didn’t happen. When Richard Thaler tried this game on students at Cornell, he found that a “fair” fifty-fifty split was by far the most common proposer offer. He also found that responders were willing to reject stingy offers. The average responder would accept $3 but reject $2. It’s not hard to understand what was going on. The proposers had enough social intelligence to know they had to give the responders enough to keep them satisfied. One thought that must have occurred to all is that a fifty-fifty split is “fair.” That makes a case for offering an even split, as a plurality of Cornell students did. The thing is, neither life nor the ultimatum game is necessarily fair. The two participants have different choices and different powers. Unless the responder is so upset that he is willing to cut his own throat, the proposer has power and incentive to shave a little off the even split.
The AI Economy: Work, Wealth and Welfare in the Robot Age by Roger Bootle
"Robert Solow", 3D printing, agricultural Revolution, AI winter, Albert Einstein, anti-work, autonomous vehicles, basic income, Ben Bernanke: helicopter money, Bernie Sanders, blockchain, call centre, Capital in the Twenty-First Century by Thomas Piketty, Chris Urmson, computer age, conceptual framework, corporate governance, correlation does not imply causation, creative destruction, David Ricardo: comparative advantage, deindustrialization, deskilling, Elon Musk, en.wikipedia.org, Erik Brynjolfsson, everywhere but in the productivity statistics, facts on the ground, financial intermediation, full employment, future of work, income inequality, income per capita, industrial robot, Internet of things, invention of the wheel, Isaac Newton, James Watt: steam engine, Jeff Bezos, job automation, job satisfaction, John Markoff, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, John von Neumann, Joseph Schumpeter, Kevin Kelly, license plate recognition, Marc Andreessen, Mark Zuckerberg, market bubble, mega-rich, natural language processing, Network effects, new economy, Nicholas Carr, Paul Samuelson, Peter Thiel, positional goods, quantitative easing, RAND corporation, Ray Kurzweil, Richard Florida, ride hailing / ride sharing, rising living standards, road to serfdom, Robert Gordon, Robert Shiller, Robert Shiller, Second Machine Age, secular stagnation, self-driving car, Silicon Valley, Simon Kuznets, Skype, social intelligence, spinning jenny, Stanislav Petrov, Stephen Hawking, Steven Pinker, technological singularity, The Future of Employment, The Wealth of Nations by Adam Smith, Thomas Malthus, trade route, universal basic income, US Airways Flight 1549, Vernor Vinge, Watson beat the top human players on Jeopardy!, We wanted flying cars, instead we got 140 characters, wealth creators, winner-take-all economy, Y2K, Yogi Berra
Manyika, J. and Miremadi, M. (2015) “Four Fundamentals of Workplace Automation,” McKinsey Quarterly (November). 21 Max Tegmark has laid down three criteria for judging whether a job is more or less likely to be challenged, or replaced, by robots any time soon. They amount to essentially the same as McKinsey’s two criteria, with my suggested addition of “common sense.” They are: Does it require interacting with people and using social intelligence? Does it involve creativity and coming up with clever solutions? Does it require working in an unpredictable environment? Tegmark (2017), p. 121. 22 Chace, C. (2016). 23 Ibid., p. 249. 24 Simon, H. (1965) The Shape of Automation for Men and Management, New York: Harper. 25 Minsky, M. (1967) Finite and Infinite Machines, New Jersey: Prentice Hall. 26 Bostrom, N. (2014) Superintelligence: Paths, Dangers, Strategies, Oxford: Oxford University Press, p. 4. 27 According to Chace (2016), p. 14. 28 Reported in The Economist, April 21, 2018. 29 Markoff, J. (2012) How Many Computers to Identify a Cat?
Human Compatible: Artificial Intelligence and the Problem of Control by Stuart Russell
3D printing, Ada Lovelace, AI winter, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, Alfred Russel Wallace, Andrew Wiles, artificial general intelligence, Asilomar, Asilomar Conference on Recombinant DNA, augmented reality, autonomous vehicles, basic income, blockchain, brain emulation, Cass Sunstein, Claude Shannon: information theory, complexity theory, computer vision, connected car, crowdsourcing, Daniel Kahneman / Amos Tversky, delayed gratification, Elon Musk, en.wikipedia.org, Erik Brynjolfsson, Ernest Rutherford, Flash crash, full employment, future of work, Gerolamo Cardano, ImageNet competition, Intergovernmental Panel on Climate Change (IPCC), Internet of things, invention of the wheel, job automation, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, John Nash: game theory, John von Neumann, Kenneth Arrow, Kevin Kelly, Law of Accelerating Returns, Mark Zuckerberg, Nash equilibrium, Norbert Wiener, NP-complete, openstreetmap, P = NP, Pareto efficiency, Paul Samuelson, Pierre-Simon Laplace, positional goods, probability theory / Blaise Pascal / Pierre de Fermat, profit maximization, RAND corporation, random walk, Ray Kurzweil, recommendation engine, RFID, Richard Thaler, ride hailing / ride sharing, Robert Shiller, Robert Shiller, Rodney Brooks, Second Machine Age, self-driving car, Shoshana Zuboff, Silicon Valley, smart cities, smart contracts, social intelligence, speech recognition, Stephen Hawking, Steven Pinker, superintelligent machines, Thales of Miletus, The Future of Employment, Thomas Bayes, Thorstein Veblen, transport as a service, Turing machine, Turing test, universal basic income, uranium enrichment, Von Neumann architecture, Wall-E, Watson beat the top human players on Jeopardy!, web application, zero-sum game
Refutation: if most physicists on Earth were working to make such black holes, wouldn’t we ask them if it was safe? It’s complicated It is a staple of modern psychology that a single IQ number cannot characterize the full richness of human intelligence.3 There are, the theory says, different dimensions of intelligence: spatial, logical, linguistic, social, and so on. Alice, our soccer player from Chapter 2, might have more spatial intelligence than her friend Bob, but less social intelligence. Thus, we cannot line up all humans in strict order of intelligence. This is even more true of machines, because their abilities are much narrower. The Google search engine and AlphaGo have almost nothing in common, besides being products of two subsidiaries of the same parent corporation, and so it makes no sense to say that one is more intelligent than the other. This makes notions of “machine IQ” problematic and suggests that it’s misleading to describe the future as a one-dimensional IQ race between humans and machines.
Rage Inside the Machine: The Prejudice of Algorithms, and How to Stop the Internet Making Bigots of Us All by Robert Elliott Smith
Ada Lovelace, affirmative action, AI winter, Alfred Russel Wallace, Amazon Mechanical Turk, animal electricity, autonomous vehicles, Black Swan, British Empire, cellular automata, citizen journalism, Claude Shannon: information theory, combinatorial explosion, corporate personhood, correlation coefficient, crowdsourcing, Daniel Kahneman / Amos Tversky, desegregation, discovery of DNA, Douglas Hofstadter, Elon Musk, Fellow of the Royal Society, feminist movement, Filter Bubble, Flash crash, Gerolamo Cardano, gig economy, Gödel, Escher, Bach, invention of the wheel, invisible hand, Jacquard loom, Jacques de Vaucanson, John Harrison: Longitude, John von Neumann, Kenneth Arrow, low skilled workers, Mark Zuckerberg, mass immigration, meta analysis, meta-analysis, mutually assured destruction, natural language processing, new economy, On the Economy of Machinery and Manufactures, p-value, pattern recognition, Paul Samuelson, performance metric, Pierre-Simon Laplace, precariat, profit maximization, profit motive, Silicon Valley, social intelligence, statistical model, Stephen Hawking, stochastic process, telemarketer, The Bell Curve by Richard Herrnstein and Charles Murray, The Future of Employment, the scientific method, The Wealth of Nations by Adam Smith, The Wisdom of Crowds, theory of mind, Thomas Bayes, Thomas Malthus, traveling salesman, Turing machine, Turing test, twin studies, Vilfredo Pareto, Von Neumann architecture, women in the workforce
The researchers placed these nine features into three groups. The first group has to do with perception and manipulation, and it included the O*NET metrics for finger dexterity, manual dexterity and cramped work spaces (or awkward positions). The second group has to do with creative intelligence, which includes the O*NET ratings for originality and fine arts. The third group has to do with social intelligence and includes the O*NET numbers for social perceptiveness, negotiation persuasion and assisting and caring for others. Only these nine numerical features are used by the algorithm to determine whether a machine can do a human being’s job. After the GPC algorithm’s Bell Curve is warped around to best fit to the seventy jobs into its tails, that curve (acting very much like a IQ test relative to Spearman’s g factor) naturally provides a ‘probability’ of computerizability for all the other 632 jobs, simply by putting the scores on these nine metrics into the warped Bell Curve (that mis-shaped rugby ball) that the algorithm has ‘learned’.
How the Mind Works by Steven Pinker
affirmative action, agricultural Revolution, Alfred Russel Wallace, Buckminster Fuller, cognitive dissonance, Columbine, combinatorial explosion, complexity theory, computer age, computer vision, Daniel Kahneman / Amos Tversky, delayed gratification, double helix, experimental subject, feminist movement, four colour theorem, Gordon Gekko, greed is good, hedonic treadmill, Henri Poincaré, income per capita, information retrieval, invention of agriculture, invention of the wheel, Johannes Kepler, John von Neumann, lake wobegon effect, lateral thinking, Machine translation of "The spirit is willing, but the flesh is weak." to Russian and back, Mikhail Gorbachev, Murray Gell-Mann, mutually assured destruction, Necker cube, out of africa, pattern recognition, phenotype, plutocrats, Plutocrats, random walk, Richard Feynman, Ronald Reagan, Rubik’s Cube, Saturday Night Live, scientific worldview, Search for Extraterrestrial Intelligence, sexual politics, social intelligence, Steven Pinker, theory of mind, Thorstein Veblen, Turing machine, urban decay, Yogi Berra
My own guess is that a cognitive arms race by itself was not enough to launch human intelligence. Any social species can begin a never-ending escalation of brain power, but none except ours has, probably because without some other change in lifestyle, the costs of intelligence (brain size, extended childhood, and so on) would damp the positive feedback loop. Humans are exceptional in mechanical and biological, not just social, intelligence. In a species that runs on information, each faculty multiplies the value of the others. (Incidentally, the expansion of the human brain is no evolutionary freak crying out for a runaway positive feedback loop. The brain tripled in size in five million years, but that is leisurely by evolutionary timekeeping. There was enough time in hominid evolution for the brain to shoot up to human size, shrink back down, and shoot up again several times over.)
Women did not wait in the kitchen to cook the mastodon that Dad brought home, nor did they forgo the expansion of intelligence enjoyed by evolving men. The ecology of modern foraging peoples suggests that Woman the Gatherer provided a substantial portion of the calories in the form of highly processed plant foods, and that requires mechanical and biological acumen. And, of course, in a group-living species, social intelligence is as important a weapon as spears and clubs. But Tooby and DeVore have argued that hunting was nonetheless a major force in human evolution. The key is to ask not what the mind can do for hunting, but what hunting can do for the mind. Hunting provides sporadic packages of concentrated nutrients. We did not always have tofu, and the best natural material for building animal flesh is animal flesh.
The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World by Pedro Domingos
Albert Einstein, Amazon Mechanical Turk, Arthur Eddington, basic income, Bayesian statistics, Benoit Mandelbrot, bioinformatics, Black Swan, Brownian motion, cellular automata, Claude Shannon: information theory, combinatorial explosion, computer vision, constrained optimization, correlation does not imply causation, creative destruction, crowdsourcing, Danny Hillis, data is the new oil, double helix, Douglas Hofstadter, Erik Brynjolfsson, experimental subject, Filter Bubble, future of work, global village, Google Glasses, Gödel, Escher, Bach, information retrieval, job automation, John Markoff, John Snow's cholera map, John von Neumann, Joseph Schumpeter, Kevin Kelly, lone genius, mandelbrot fractal, Mark Zuckerberg, Moneyball by Michael Lewis explains big data, Narrative Science, Nate Silver, natural language processing, Netflix Prize, Network effects, NP-complete, off grid, P = NP, PageRank, pattern recognition, phenotype, planetary scale, pre–internet, random walk, Ray Kurzweil, recommendation engine, Richard Feynman, scientific worldview, Second Machine Age, self-driving car, Silicon Valley, social intelligence, speech recognition, Stanford marshmallow experiment, statistical model, Stephen Hawking, Steven Levy, Steven Pinker, superintelligent machines, the scientific method, The Signal and the Noise by Nate Silver, theory of mind, Thomas Bayes, transaction costs, Turing machine, Turing test, Vernor Vinge, Watson beat the top human players on Jeopardy!, white flight, zero-sum game
In all of these cases, the best way to understand an entity—whether it’s a person, an animal, a web page, or a molecule—is to understand how it relates to other entities. This requires a new kind of learning that doesn’t treat the data as a random sample of unrelated objects but as a glimpse into a complex network. Nodes in the network interact; what you do to one affects the others and comes back to affect you. Relational learners, as they’re called, may not quite have social intelligence, but they’re the next best thing. In traditional statistical learning, every man is an island, entire of itself. In relational learning, every man is a piece of the continent, a part of the main. Humans are relational learners, wired to connect, and if we want Robby to grow into a perceptive, socially adept robot, we need to wire him to connect, too. The first difficulty we face is that, when the data is all one big network, we no longer seem to have many examples to learn from, just one—and that’s not enough.
Together by Vivek H. Murthy, M.D.
Airbnb, call centre, cognitive bias, coronavirus, COVID-19, Covid-19, crowdsourcing, gig economy, income inequality, index card, longitudinal study, Lyft, Mahatma Gandhi, medical residency, meta analysis, meta-analysis, moral hazard, Nelson Mandela, Ralph Waldo Emerson, randomized controlled trial, rent control, ride hailing / ride sharing, Ronald Reagan, sharing economy, Silicon Valley, Silicon Valley startup, Skype, Snapchat, social intelligence, stem cell, twin studies, Uber and Lyft, uber lyft
She started going to summer camp at five years old, later became a camp counselor, and now serves as a consulting psychologist to summer camps. Like Yalda Uhls, who found that outdoor camp can increase empathy among kids, Steiner-Adair describes camp as an important setting for youth. “There’s no better place that I can think of to learn social emotional intelligence,” she told me when we spoke recently. Not all camps are equal, of course. Nor is camp the only place where kids develop social intelligence. However, the summer-camp model is worth examining because, as Steiner-Adair said, “The canons at a good camp are empathy, authenticity, and social and emotional intelligence.” At camp, kids are released from what Steiner-Adair calls the digital pacifier. “Everybody is present to each other. There’s no digital distraction and everybody has to be included. We are connected through camp—whether you like that girl or not, you are in the same boat.”
The Black Box Society: The Secret Algorithms That Control Money and Information by Frank Pasquale
Affordable Care Act / Obamacare, algorithmic trading, Amazon Mechanical Turk, American Legislative Exchange Council, asset-backed security, Atul Gawande, bank run, barriers to entry, basic income, Berlin Wall, Bernie Madoff, Black Swan, bonus culture, Brian Krebs, business cycle, call centre, Capital in the Twenty-First Century by Thomas Piketty, Chelsea Manning, Chuck Templeton: OpenTable:, cloud computing, collateralized debt obligation, computerized markets, corporate governance, Credit Default Swap, credit default swaps / collateralized debt obligations, crowdsourcing, cryptocurrency, Debian, don't be evil, drone strike, Edward Snowden, en.wikipedia.org, Fall of the Berlin Wall, Filter Bubble, financial innovation, financial thriller, fixed income, Flash crash, full employment, Goldman Sachs: Vampire Squid, Google Earth, Hernando de Soto, High speed trading, hiring and firing, housing crisis, informal economy, information asymmetry, information retrieval, interest rate swap, Internet of things, invisible hand, Jaron Lanier, Jeff Bezos, job automation, Julian Assange, Kevin Kelly, knowledge worker, Kodak vs Instagram, kremlinology, late fees, London Interbank Offered Rate, London Whale, Marc Andreessen, Mark Zuckerberg, mobile money, moral hazard, new economy, Nicholas Carr, offshore financial centre, PageRank, pattern recognition, Philip Mirowski, precariat, profit maximization, profit motive, quantitative easing, race to the bottom, recommendation engine, regulatory arbitrage, risk-adjusted returns, Satyajit Das, search engine result page, shareholder value, Silicon Valley, Snapchat, social intelligence, Spread Networks laid a new fibre optics cable between New York and Chicago, statistical arbitrage, statistical model, Steven Levy, the scientific method, too big to fail, transaction costs, two-sided market, universal basic income, Upton Sinclair, value at risk, WikiLeaks, zero-sum game
Gabriella Coleman, Coding Freedom: The Ethics and Aesthetics of Hacking (Princeton, NJ: Princeton University Press, 2013) (exploring Debian open source community and assessment of community members’ contributions); Stephen Baker, The Numerati (New York: Houghton-Miffl in, 2008), 33. 87. Mat Honan, “I Flunked My Social Media Background Check. Will You?,” Gizmodo (July 7, 2011). Available at http://gizmodo.com /5818774 /this-is -a-social-media-background-check /. (“For each [social media] internet sources, Social Intelligence scored [candidate as] either “pass” or “negative,” and included comments such as “subject admits to use of cocaine as well as LSD,” and “subject references use of Ketamine [another recreational drug].”). NOTES TO PAGES 34–37 235 88. Solove, The Digital Person, 47. 89. Tom Burghardt, “Big Brother a Click Away,” Pacifi c Free Press, October 10, 2010, http://www.pacificfreepress.com /news/1/7119-big-brother-a-click -away.html.
Feral: Rewilding the Land, the Sea, and Human Life by George Monbiot
Chance favours the prepared mind, cognitive dissonance, en.wikipedia.org, Hugh Fearnley-Whittingstall, land reform, Nelson Mandela, nuclear winter, offshore financial centre, oil rush, oil shale / tar sands, place-making, social intelligence, trade route
In reality, wolves are exceedingly afraid of people and in almost all circumstances avoid us. If we take the time to win their trust—as the biologists who have been adopted by wild wolf packs can testify—they can become affectionate companions. But the fairytales are more powerful than the facts. Could it be that we are so afraid of wolves not because they represent an alien threat, but because we recognize in them some of our own traits? They have a similar social intelligence: the ability to interpret and respond to someone else’s behavior and mood. They look at you as if they can read your mind. To some extent they can, which is why we domesticated them. This, perhaps, is why they unnerve us, and why so many stories have been written and filmed in which wolves become humans or disguise themselves as such, or humans become wolves. But perhaps there is something else at work too, a subliminal yearning for the kind of danger that no longer infects our lives.
The Village Effect: How Face-To-Face Contact Can Make Us Healthier, Happier, and Smarter by Susan Pinker
assortative mating, Atul Gawande, Bernie Madoff, call centre, cognitive dissonance, David Brooks, delayed gratification, Edward Glaeser, epigenetics, Erik Brynjolfsson, estate planning, facts on the ground, game design, happiness index / gross national happiness, indoor plumbing, invisible hand, Kickstarter, longitudinal study, Mark Zuckerberg, medical residency, Menlo Park, meta analysis, meta-analysis, neurotypical, Occupy movement, old-boy network, place-making, Ponzi scheme, Ralph Waldo Emerson, randomized controlled trial, Ray Oldenburg, Silicon Valley, Skype, social intelligence, Stanford marshmallow experiment, Steven Pinker, The Great Good Place, The Wisdom of Crowds, theory of mind, Tony Hsieh, urban planning, Yogi Berra
The emotional and psychological investments that a close relationship requires are considerable, and the emotional capital we have available is limited,” Dunbar writes.38 A primatologist by training, Dunbar is a mild-mannered, sixtyish Oxford academic with a graying chinstrap beard, large rimless glasses, and a tendency to sprinkle “as it were” into his speech every few minutes. He should have added “as it were” to that previous statement about the mind: I doubt that he meant our minds were designed per se but rather that they evolved over time to support the size and complexity of our social groups. Called the social intelligence hypothesis, it explains why primates, and humans in particular, developed brains large enough for them to develop the capacities for language and empathy.39 In order for primates to survive in larger groups, they needed supercharged brainpower to keep track of who was sleeping with whom, who was whose momma, who was the Big Cheese at any given moment (and who he had just deposed), who was his right-hand man and who were his allies, and which young whippersnapper was planning to depose him.
The Happiness Hypothesis: Finding Modern Truth in Ancient Wisdom by Jonathan Haidt
coherent worldview, crack epidemic, delayed gratification, feminist movement, hedonic treadmill, Ignaz Semmelweis: hand washing, invisible hand, job satisfaction, Lao Tzu, longitudinal study, meta analysis, meta-analysis, Peter Singer: altruism, PIHKAL and TIHKAL, placebo effect, prisoner's dilemma, Ralph Waldo Emerson, selective serotonin reuptake inhibitor (SSRI), social intelligence, stem cell, telemarketer, the scientific method, twin studies, ultimatum game, Walter Mischel, zero-sum game
T h e lawyer has been given an order: U s e all your powers to d e f e n d me. Studies of "motivated reasoning"13 show that people who are motivated to reach a particular conclusion are even worse reasoners than those in Kuhn's and Perkins's studies, but the mechanism is basically the s a m e : a one-sided search for supporting evidence only. People who are told that they have performed poorly on a test of social intelligence think extra hard to find reasons to discount the test; people who are asked to read a study showing that one of their habits—such as drinking coffee—-is unhealthy think extra hard to find flaws in the study, flaws that people w h o don't drink coffee don't notice. Over and over again, studies show that people set out on a cognitive mission to bring back reasons to support their preferred belief or action.
Radical Technologies: The Design of Everyday Life by Adam Greenfield
3D printing, Airbnb, augmented reality, autonomous vehicles, bank run, barriers to entry, basic income, bitcoin, blockchain, business intelligence, business process, call centre, cellular automata, centralized clearinghouse, centre right, Chuck Templeton: OpenTable:, cloud computing, collective bargaining, combinatorial explosion, Computer Numeric Control, computer vision, Conway's Game of Life, cryptocurrency, David Graeber, dematerialisation, digital map, disruptive innovation, distributed ledger, drone strike, Elon Musk, Ethereum, ethereum blockchain, facts on the ground, fiat currency, global supply chain, global village, Google Glasses, IBM and the Holocaust, industrial robot, informal economy, information retrieval, Internet of things, James Watt: steam engine, Jane Jacobs, Jeff Bezos, job automation, John Conway, John Markoff, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, John von Neumann, joint-stock company, Kevin Kelly, Kickstarter, late capitalism, license plate recognition, lifelogging, M-Pesa, Mark Zuckerberg, means of production, megacity, megastructure, minimum viable product, money: store of value / unit of account / medium of exchange, natural language processing, Network effects, New Urbanism, Occupy movement, Oculus Rift, Pareto efficiency, pattern recognition, Pearl River Delta, performance metric, Peter Eisenman, Peter Thiel, planetary scale, Ponzi scheme, post scarcity, post-work, RAND corporation, recommendation engine, RFID, rolodex, Satoshi Nakamoto, self-driving car, sentiment analysis, shareholder value, sharing economy, Silicon Valley, smart cities, smart contracts, social intelligence, sorting algorithm, special economic zone, speech recognition, stakhanovite, statistical model, stem cell, technoutopianism, Tesla Model S, the built environment, The Death and Life of Great American Cities, The Future of Employment, transaction costs, Uber for X, undersea cable, universal basic income, urban planning, urban sprawl, Whole Earth Review, WikiLeaks, women in the workforce
(Proponents of this approach invariably cite the “precrime” unit of Steven Spielberg’s 2002 Minority Report, evidently mistaking the film’s depiction of dystopian oppression for an aspirational goal.)18 There are a few different approaches and strategies bound up in the practice of predictive policing, but what they all have in common is that they propose to sit in Olympian detachment, far removed from the play of events, and reach down into all the murk of our affairs to wrest the single salient truth from a whirling storm of confusion. The simplest tools mobilized in predictive policing efforts, and in a way the most general, are dedicated to geolocating and otherwise parsing the things people say on social media, in the hopes of drawing actionable inferences from them. This is the province of “location-based social intelligence” applications like Snaptrends and SpatialKey, which promise to “identify, isolate and assess” threats, whether direct or indirect. A Snaptrends brochure for prospective customers in the law enforcement sector makes the proposition explicit: “From angry Facebook posts to suggestive Instagram uploads, today’s would-be criminals often leave A STRING OF CLUES across social media,” and a public-safety agency made aware of those CLUES can deploy its resources in time to preempt the commission of crime.19 Such tools use sentiment analysis, a facet of the emerging pseudoscience of “intent recognition,” to extract actionable intelligence from utterances.20 But it’s astonishing that anyone takes sentiment analysis seriously in any but the most trivial applications, let alone what is all too often the life-or-death context of a police stop.
Giving the Devil His Due: Reflections of a Scientific Humanist by Michael Shermer
Alfred Russel Wallace, anthropic principle, anti-communist, barriers to entry, Berlin Wall, Boycotts of Israel, Chelsea Manning, clean water, clockwork universe, cognitive dissonance, Colonization of Mars, Columbine, cosmological constant, cosmological principle, creative destruction, dark matter, Donald Trump, Edward Snowden, Elon Musk, Flynn Effect, germ theory of disease, gun show loophole, Hans Rosling, hedonic treadmill, helicopter parent, hindsight bias, illegal immigration, income inequality, invisible hand, Johannes Kepler, Joseph Schumpeter, laissez-faire capitalism, Laplace demon, luminiferous ether, McMansion, means of production, mega-rich, Menlo Park, moral hazard, moral panic, More Guns, Less Crime, Peter Singer: altruism, phenotype, positional goods, race to the bottom, Richard Feynman, Ronald Coase, Silicon Valley, Skype, social intelligence, stem cell, Stephen Hawking, Steve Jobs, Steven Pinker, the scientific method, The Wealth of Nations by Adam Smith, transaction costs, WikiLeaks, working poor, Yogi Berra
Along with Martin Gardner, magician James Randi, psychologist Ray Hyman, and, most notably, philosopher Paul Kurtz played primary roles in the foundation and planning of the organization and the subsequent movement it launched that led to the formation of a worldwide phenomenon of humanists, skeptics, atheists, agnostics, and free thinkers of all stripes. Regardless of who might be considered the “father” of the modern skeptical movement, everyone I have spoken to (including the other founders) agrees that it was Paul Kurtz more than anyone else who actually made it happen. All successful social movements have someone who has the organizational skills and social intelligence to get things done. Paul Kurtz is that man. When he founded the organization that launched the modern skeptical movement, I was a graduate student in experimental psychology. About this time (the mid-1970s) Uri Geller entered my radar screen. I recall Psychology Today and other popular magazines published glowing stories about him, and reports were afloat that experimental psychologists had tested the Israeli psychic and determined that he was genuine.
Humankind: A Hopeful History by Rutger Bregman
Airbnb, Anton Chekhov, basic income, Berlin Wall, bitcoin, Broken windows theory, call centre, David Graeber, Donald Trump, experimental subject, Fall of the Berlin Wall, Frederick Winslow Taylor, Hans Rosling, invention of writing, invisible hand, knowledge economy, late fees, Mahatma Gandhi, mass incarceration, meta analysis, meta-analysis, Milgram experiment, Nelson Mandela, New Journalism, placebo effect, sharing economy, Shoshana Zuboff, Silicon Valley, social intelligence, Stanford prison experiment, Stephen Hawking, Steve Jobs, Steven Pinker, The Spirit Level, The Wealth of Nations by Adam Smith, transatlantic slave trade, tulip mania, universal basic income, World Values Survey
They certainly hadn’t inherited their brains from their wolf ancestors, because wolves score just as poorly on Brian’s test as orangutans and chimpanzees. And they didn’t pick it up from their owners, because puppies can pass the test at nine weeks old. Brian’s colleague and adviser, the primatologist Richard Wrangham, suggested that canine intelligence might arise on its own, as a chance by-product, like corkscrew tails and drop ears. But Brian didn’t buy that; how could a trait as instrumental as social intelligence be an accident? Rather, the young biologist suspected that our ancestors had selectively bred the smartest dogs. There was only one way Brian could test his suspicion. It was time for a trip to Siberia. Years earlier, Brian had read about an obscure study by a Russian geneticist who purportedly had turned foxes into dogs. By the time Brian stepped off the Trans-Siberian Express, in 2003, Lyudmila and her team had already bred forty-five generations.
The Invention of Science: A New History of the Scientific Revolution by David Wootton
agricultural Revolution, Albert Einstein, British Empire, clockwork universe, Commentariolus, commoditize, conceptual framework, Dava Sobel, double entry bookkeeping, double helix, en.wikipedia.org, Ernest Rutherford, Fellow of the Royal Society, fudge factor, germ theory of disease, Google X / Alphabet X, Hans Lippershey, interchangeable parts, invention of gunpowder, invention of the steam engine, invention of the telescope, Isaac Newton, Jacques de Vaucanson, James Watt: steam engine, Johannes Kepler, John Harrison: Longitude, knowledge economy, lateral thinking, lone genius, Mercator projection, On the Revolutions of the Heavenly Spheres, Philip Mirowski, placebo effect, QWERTY keyboard, Republic of Letters, social intelligence, spice trade, spinning jenny, the scientific method, Thomas Kuhn: the structure of scientific revolutions
The Copernican Question: Prognostication, Skepticism and Celestial Order. Berkeley: University of California Press, 2011. ———. ‘The Copernican Question Revisited: A Reply to Noel Swerdlow and John Heilbron’. Perspectives on Science 21 (2013): 100–36. Westman, Robert S and JE McGuire. Hermeticism and the Scientific Revolution. Los Angeles: William Andrews Clark Memorial Library, 1977. Westrum, Ron. ‘Science and Social Intelligence about Anomalies: The Case of Meteorites’. Social Studies of Science 8 (1978): 461–93. Whewell, William. ‘On the Connexion of the Physical Sciences’. Quarterly Review 51 (1834): 54–68. ———. The Philosophy of the Inductive Sciences, Founded upon Their History. 2 vols. London: John W Parker, 1840. White, Gilbert. The Natural History and Antiquities of Selborne, in the County of Southampton.
Daston, ‘Strange Facts, Plain Facts’ (1996); and Daston, ‘The Language of Strange Facts’ (1997). 128. Berkel, Isaac Beeckman (2013), 144–5. 129. Clark, Thinking with Demons (1997). 130. Arnauld & Nicole, La Logique (1970), Part 4, Ch. 14. 131. Accademia del Cimento, Saggi di naturali esperienze (1667), 146; Accademia del Cimento, Essayes of Natural Experiments (1684), 77. 132. Westrum, ‘Science and Social Intelligence about Anomalies’ (1978). 133. Nield, Incoming! (2011), 67–72. 134. Pantin, ‘New Philosophy and Old Prejudices’ (1999), 260. Gilbert uses the phrase ‘libere philosophare’ in the preface to the reader of De magnete. 135. Goulding, ‘Henry Savile and the Tychonic World-system’ (1995), 175. 136. Jacquot, ‘Thomas Harriot’s Reputation for Impiety’ (1952), 167. 137. Pascal, Oeuvres complètes (1964), 779. 138.
Strategy: A History by Lawrence Freedman
Albert Einstein, anti-communist, Anton Chekhov, Ayatollah Khomeini, barriers to entry, battle of ideas, Black Swan, British Empire, business process, butterfly effect, centre right, Charles Lindbergh, circulation of elites, cognitive dissonance, coherent worldview, collective bargaining, complexity theory, conceptual framework, corporate raider, correlation does not imply causation, creative destruction, cuban missile crisis, Daniel Kahneman / Amos Tversky, defense in depth, desegregation, Edward Lorenz: Chaos theory, en.wikipedia.org, endogenous growth, endowment effect, Ford paid five dollars a day, framing effect, Frederick Winslow Taylor, Gordon Gekko, greed is good, information retrieval, interchangeable parts, invisible hand, John Nash: game theory, John von Neumann, Kenneth Arrow, lateral thinking, linear programming, loose coupling, loss aversion, Mahatma Gandhi, means of production, mental accounting, Murray Gell-Mann, mutually assured destruction, Nash equilibrium, Nelson Mandela, Norbert Wiener, Norman Mailer, oil shock, Pareto efficiency, performance metric, Philip Mirowski, prisoner's dilemma, profit maximization, race to the bottom, Ralph Nader, RAND corporation, Richard Thaler, road to serfdom, Ronald Reagan, Rosa Parks, shareholder value, social intelligence, Steven Pinker, strikebreaker, The Chicago School, The Myth of the Rational Market, the scientific method, theory of mind, Thomas Davenport, Thomas Kuhn: the structure of scientific revolutions, Torches of Freedom, Toyota Production System, transaction costs, ultimatum game, unemployed young men, Upton Sinclair, urban sprawl, Vilfredo Pareto, War on Poverty, women in the workforce, Yogi Berra, zero-sum game
The brain consumes 20 percent of the body’s energy, far more than any other organ, while making up only 2 percent of an adult’s body weight. Something so costly to maintain must have developed to meet a vital need. Richard Byrne and Nadia Corp studied eighteen species from all the major branches of primates and correlated the size of the neocortex to the amount of deception the species practiced. They established a link between the size of the brains and general social intelligence, including the ability to work together and manage conflict, as well as trickery.4 In evolutionary terms, the value of these skills was not hard to imagine in the face of challenges from other species that might be stronger but also more stupid. If neocortex size set the limits on the mental world of a particular animal, then it would also set limits on those with whom relationships could be formed, and therefore the number of allies available at times of conflict.
Keeley, War Before Civilization: The Myth of the Peaceful Savage (New York: Oxford University Press, 1996), 48. 12. Azar Gat, War in Human Civilization (Oxford: Oxford University Press, 2006), 115–117. 13. Keeping in mind that these societies were relatively simple and social moves within them, including deception, would be less demanding than those in more complex human societies. Kim Sterelny, “Social Intelligence, Human Intelligence and Niche Construction,” Philosophical Transactions of The Royal Society 362, no. 1480 (2007): 719–730. 2 Origins 2: The Bible 1. Steven Brams, Biblical Games: Game Theory and the Hebrew Bible (Cambridge, MA: The MIT Press, 2003). 2. Ibid., 12. 3. Genesis 2:22, 23. All biblical references use the King James Version. 4. Genesis 2:16, 17; 3:16, 17. 5. Diana Lipton, Longing for Egypt and Other Unexpected Biblical Tales, Hebrew Bible Monographs 15 (Sheffield: Sheffield Phoenix Press, 2008). 6.
Blockchain Revolution: How the Technology Behind Bitcoin Is Changing Money, Business, and the World by Don Tapscott, Alex Tapscott
Airbnb, altcoin, asset-backed security, autonomous vehicles, barriers to entry, bitcoin, blockchain, Blythe Masters, Bretton Woods, business process, buy and hold, Capital in the Twenty-First Century by Thomas Piketty, carbon footprint, clean water, cloud computing, cognitive dissonance, commoditize, corporate governance, corporate social responsibility, creative destruction, Credit Default Swap, crowdsourcing, cryptocurrency, disintermediation, disruptive innovation, distributed ledger, Donald Trump, double entry bookkeeping, Edward Snowden, Elon Musk, Erik Brynjolfsson, Ethereum, ethereum blockchain, failed state, fiat currency, financial innovation, Firefox, first square of the chessboard, first square of the chessboard / second half of the chessboard, future of work, Galaxy Zoo, George Gilder, glass ceiling, Google bus, Hernando de Soto, income inequality, informal economy, information asymmetry, intangible asset, interest rate swap, Internet of things, Jeff Bezos, jimmy wales, Kickstarter, knowledge worker, Kodak vs Instagram, Lean Startup, litecoin, Lyft, M-Pesa, Marc Andreessen, Mark Zuckerberg, Marshall McLuhan, means of production, microcredit, mobile money, money market fund, Network effects, new economy, Oculus Rift, off grid, pattern recognition, peer-to-peer, peer-to-peer lending, peer-to-peer model, performance metric, Peter Thiel, planetary scale, Ponzi scheme, prediction markets, price mechanism, Productivity paradox, QR code, quantitative easing, ransomware, Ray Kurzweil, renewable energy credits, rent-seeking, ride hailing / ride sharing, Ronald Coase, Ronald Reagan, Satoshi Nakamoto, Second Machine Age, seigniorage, self-driving car, sharing economy, Silicon Valley, Skype, smart contracts, smart grid, social graph, social intelligence, social software, standardized shipping container, Stephen Hawking, Steve Jobs, Steve Wozniak, Stewart Brand, supply-chain management, TaskRabbit, The Fortune at the Bottom of the Pyramid, The Nature of the Firm, The Wisdom of Crowds, transaction costs, Turing complete, Turing test, Uber and Lyft, uber lyft, unbanked and underbanked, underbanked, unorthodox policies, wealth creators, X Prize, Y2K, Zipcar
., the native token of the blockchain such as Peercoin, NXT, etc.). They needn’t spend energy to vote. Other blockchains, such as Ripple and Stellar, rely on social networks for consensus and may recommend that new participants (i.e., new nodes) generate a unique node list of at least one hundred nodes they can trust in voting on the state of affairs. This type of proof is biased: newcomers need social intelligence and reputation to participate. Proof of activity is another mechanism; it combines proof of work and proof of stake, where a random number of miners must sign off on the block using a cryptokey before the block becomes official.9 Proof of capacity requires miners to allot a sizable volume of their hard drive to mining. A similar concept, proof of storage, requires miners to allocate and share disk space in a distributed cloud.
The Hype Machine: How Social Media Disrupts Our Elections, Our Economy, and Our Health--And How We Must Adapt by Sinan Aral
Airbnb, Albert Einstein, Any sufficiently advanced technology is indistinguishable from magic, augmented reality, Bernie Sanders, bitcoin, carbon footprint, Cass Sunstein, computer vision, coronavirus, correlation does not imply causation, COVID-19, Covid-19, crowdsourcing, cryptocurrency, death of newspapers, disintermediation, Donald Trump, Drosophila, Edward Snowden, Elon Musk, en.wikipedia.org, Erik Brynjolfsson, experimental subject, facts on the ground, Filter Bubble, global pandemic, hive mind, illegal immigration, income inequality, Kickstarter, knowledge worker, longitudinal study, low skilled workers, Lyft, Mahatma Gandhi, Mark Zuckerberg, Menlo Park, meta analysis, meta-analysis, Metcalfe’s law, mobile money, move fast and break things, move fast and break things, multi-sided market, Nate Silver, natural language processing, Network effects, performance metric, phenotype, recommendation engine, Robert Bork, Robert Shiller, Robert Shiller, Second Machine Age, sentiment analysis, shareholder value, skunkworks, Snapchat, social graph, social intelligence, social software, social web, statistical model, stem cell, Stephen Hawking, Steve Jobs, Telecommunications Act of 1996, The Chicago School, The Wisdom of Crowds, theory of mind, Tim Cook: Apple, Uber and Lyft, uber lyft, WikiLeaks, Yogi Berra
Jolly had spent months watching lemurs on the banks of the Mandrare River in Madagascar. She discovered that while lemurs developed complex social orders, they did so without the object-learning capacity and manipulative dexterity that some had thought explained primate intelligence. Having seen strong evidence for the development of a social order, without evidence of object learning or fine gross motor skills, she discovered that, in lemurs at least, social intelligence preceded object and manipulative intelligence. She concluded that “primate society, thus, could develop without the object-learning capacity or manipulative ingenuity of monkeys. This manipulative, object cleverness, however, evolved only in the context of primate social life. Therefore, I would argue that some social life preceded and determined the nature of primate intelligence.” It wasn’t the ability to manipulate and reason about objects that made primates smarter and more social.
The Age of Spiritual Machines: When Computers Exceed Human Intelligence by Ray Kurzweil
Ada Lovelace, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, Albert Einstein, Any sufficiently advanced technology is indistinguishable from magic, Buckminster Fuller, call centre, cellular automata, combinatorial explosion, complexity theory, computer age, computer vision, cosmological constant, cosmological principle, Danny Hillis, double helix, Douglas Hofstadter, Everything should be made as simple as possible, first square of the chessboard / second half of the chessboard, fudge factor, George Gilder, Gödel, Escher, Bach, I think there is a world market for maybe five computers, information retrieval, invention of movable type, Isaac Newton, iterative process, Jacquard loom, John Markoff, John von Neumann, Lao Tzu, Law of Accelerating Returns, mandelbrot fractal, Marshall McLuhan, Menlo Park, natural language processing, Norbert Wiener, optical character recognition, ought to be enough for anybody, pattern recognition, phenotype, Ralph Waldo Emerson, Ray Kurzweil, Richard Feynman, Robert Metcalfe, Schrödinger's Cat, Search for Extraterrestrial Intelligence, self-driving car, Silicon Valley, social intelligence, speech recognition, Steven Pinker, Stewart Brand, stochastic process, technological singularity, Ted Kaczynski, telepresence, the medium is the message, There's no reason for any individual to have a computer in his home - Ken Olsen, traveling salesman, Turing machine, Turing test, Whole Earth Review, Y2K
Downes, Larry, Chunka Mui, and Nicholas Negroponte. Unleashing the Killer App: Digital Strategies for Market Dominance,. Cambridge, MA: Harvard Business School Press, 1998. Drachmann, A. G. The Mechanical Technology of Greek and Roman Antiquity. Madison: University of Wisconsin Press, 1963. Drexler, K. Eric. Engines of Creation. New York: Doubleday, 1986. _______. “Hypertext Publishing and the Evolution of Knowledge.” Social Intelligence 1:2 (1991). Dreyfus, Hubert. “Alchemy and Artificial Intelligence,” Rand Technical Report, December 1965. ________. Philosophic Issues in Artificial Intelligence. Chicago: Quadrangle Books, 1967. ______. What Computers Can’t Do: The Limits of Artificial Intelligence. New York: Harper and Row, 1979. _______. What Computers Still Can’t Do: A Critique of Artificial Reason. Cambridge, MA: MIT Press, 1992. ______, ed.
The Great Turning: From Empire to Earth Community by David C. Korten
Albert Einstein, banks create money, big-box store, Bretton Woods, British Empire, business cycle, clean water, colonial rule, Community Supported Agriculture, death of newspapers, declining real wages, different worldview, European colonialism, Francisco Pizarro, full employment, George Gilder, global supply chain, global village, God and Mammon, Hernando de Soto, Howard Zinn, informal economy, Intergovernmental Panel on Climate Change (IPCC), invisible hand, joint-stock company, land reform, market bubble, market fundamentalism, Monroe Doctrine, Naomi Klein, neoliberal agenda, new economy, peak oil, planetary scale, plutocrats, Plutocrats, Project for a New American Century, Ronald Reagan, Rosa Parks, sexual politics, shared worldview, social intelligence, source of truth, South Sea Bubble, stem cell, structural adjustment programs, The Chicago School, trade route, Washington Consensus, wealth creators, World Values Survey
Moral Autism For all the efforts of the corporate media to portray the scandals as the work of a few bad apples, it became clear that the corruption was on a grand scale and carried out by profoundly ethically challenged individuals. The responsible individuals did not necessarily intend to harm others. Rather, they appear to have been acting from the purely selfreferential perspective common to young children. Catholic theologian Daniel Maguire refers to this pattern as moral autism.7 Like the young delinquent mentioned earlier, the adult operating from an Imperial Consciousness may have the social intelligence to recognize that it is easiest to steal from those who trust you, but lack the moral capacity to recognize that to do so constitutes a wrong in itself and destroys the fabric of trust essential to healthy social relationships. When such adults appear among the lower socioeconomic classes, the ruling establishment commonly identiﬁes them as sociopaths and conﬁnes them to a prison or mental institution.
Terms of Service: Social Media and the Price of Constant Connection by Jacob Silverman
23andMe, 4chan, A Declaration of the Independence of Cyberspace, Airbnb, airport security, Amazon Mechanical Turk, augmented reality, basic income, Brian Krebs, California gold rush, call centre, cloud computing, cognitive dissonance, commoditize, correlation does not imply causation, Credit Default Swap, crowdsourcing, don't be evil, drone strike, Edward Snowden, feminist movement, Filter Bubble, Firefox, Flash crash, game design, global village, Google Chrome, Google Glasses, hive mind, income inequality, informal economy, information retrieval, Internet of things, Jaron Lanier, jimmy wales, Kevin Kelly, Kickstarter, knowledge economy, knowledge worker, late capitalism, license plate recognition, life extension, lifelogging, Lyft, Mark Zuckerberg, Mars Rover, Marshall McLuhan, mass incarceration, meta analysis, meta-analysis, Minecraft, move fast and break things, move fast and break things, national security letter, Network effects, new economy, Nicholas Carr, Occupy movement, optical character recognition, payday loans, Peter Thiel, postindustrial economy, prediction markets, pre–internet, price discrimination, price stability, profit motive, quantitative hedge fund, race to the bottom, Ray Kurzweil, recommendation engine, rent control, RFID, ride hailing / ride sharing, self-driving car, sentiment analysis, shareholder value, sharing economy, Silicon Valley, Silicon Valley ideology, Snapchat, social graph, social intelligence, social web, sorting algorithm, Steve Ballmer, Steve Jobs, Steven Levy, TaskRabbit, technoutopianism, telemarketer, transportation-network company, Travis Kalanick, Turing test, Uber and Lyft, Uber for X, uber lyft, universal basic income, unpaid internship, women in the workforce, Y Combinator, Zipcar
One answer is that it’s a by-product of the network effect: the more people who are part of a network, the more one’s experience can seem impoverished by being left out. Everyone else is doing it. A billion people on Facebook, hundreds of millions scattered between these other networks—who wants to be on the outside? Who wants to miss a birthday, a friend’s big news, a chance to sign up for Spotify, or the latest bit of juicy social intelligence? And once you’ve joined, the updates begin to flow, the small endorphin boosts of likes and repins becoming the meager rewards for all that work. The feeling of disappointment embedded in each gesture, the sense of “Is this it?”, only advances the process, compelling us to continue sharing and participating. The achievement of social-media evangelists is to make this urge—the urge to share simply so that others might know you are there, that you’re doing this thing, that you’re with this person, that you’ve had this thought, that you have some urgent opinion on what’s trending—second nature.
The Master and His Emissary: The Divided Brain and the Making of the Western World by Iain McGilchrist
Albert Einstein, Asperger Syndrome, Benoit Mandelbrot, Berlin Wall, cognitive bias, cognitive dissonance, computer age, Donald Trump, double helix, Douglas Hofstadter, epigenetics, experimental subject, Fellow of the Royal Society, Georg Cantor, hedonic treadmill, Henri Poincaré, Lao Tzu, longitudinal study, Louis Pasteur, mandelbrot fractal, meta analysis, meta-analysis, music of the spheres, Necker cube, Panopticon Jeremy Bentham, pattern recognition, randomized controlled trial, Sapir-Whorf hypothesis, Schrödinger's Cat, social intelligence, social web, source of truth, stem cell, Steven Pinker, the scientific method, theory of mind
Those groups that were most cohesive would survive best, and the whole group’s genes would do better, or not, depending on the acquisition of shared skills that promote bonding – such as music, or ultimately language. Those individuals less able to imitate would be less well bound into the group, and would not prosper to the same degree. The other big selective factor in acquiring skills and fitting in with the group would be flexibility, which comes with expansion of the frontal lobes – particularly the right frontal lobe, which is also the seat of social intelligence. Skills are intuitive, ‘inhabited’ ways of being and behaving, not analytically structured, rule-based techniques. So it may be that we were selected – not for specific abilities, with specific genes for each, such as the ‘language gene(s)’ or the ‘music gene(s)’ – not even ‘group selected’ for such genes – but individually for the dual skills of flexibility and the power to mimic, which are what is required to develop skills in general.
The research was quite independent, despite the temporal proximity: Asperger was not aware of Kanner’s paper, describing the first case histories of classic autism, when he wrote his own. Since that time rates have steadily climbed, and continue to climb. Again, both these conditions are marked by clinical features strongly suggestive of right-hemisphere hypofunction, and the resulting picture is one of left-hemisphere dominance. There is in autism an inability to tell what another is thinking (lack of ‘theory of mind’); a lack of social intelligence – difficulty in judging nonverbal features of communication, such as tone, humour, irony; an inability to detect deceit, and difficulty understanding implicit meaning; a lack of empathy; a lack of imagination; an attraction to the mechanical; a tendency to treat people and body parts as inanimate objects; an alienation from the self (autistic children often fail to develop the first-person perspective and speak of themselves as ‘he’ or ‘she’); an inability to engage in eye contact or mutually directed gaze; and an obsession with detail.76 All these features will be recognisable as signs of left hemisphere predominance.
Empire by Michael Hardt, Antonio Negri
Berlin Wall, Bretton Woods, colonial rule, conceptual framework, equal pay for equal work, European colonialism, Fall of the Berlin Wall, feminist movement, Francis Fukuyama: the end of history, global pandemic, global village, Haight Ashbury, informal economy, invisible hand, late capitalism, low skilled workers, mass immigration, means of production, Monroe Doctrine, Nelson Mandela, New Urbanism, open borders, post-industrial society, postindustrial economy, Scramble for Africa, social intelligence, The Wealth of Nations by Adam Smith, union organizing, urban planning
Life is no longer produced in the cycles ofreproduction that are subordinated to the working day; on the contrary, life is what infuses and dominates all production. In fact, the value of labor and production is deter- mined deep in the viscera oflife. Industry produces no surplus except what is generated by social activity—and this is why, buried in the great whale oflife, value is beyond measure. There would be no surplus ifproduction were not animated throughout by social intelligence, by the general intellect and at the same time by the affective expressions that define social relations and rule over the articulations ofsocial being. The excess ofvalue is determined today in the affects, in the bodies crisscrossed by knowledge, in 366 T H E D E C L I N E A N D F A L L O F E M P I R E the intelligence ofthe mind, and in the sheer power to act. The production ofcommodities tends to be accomplished entirely through language, where by language we mean machines ofintelli- gence that are continuously renovated by the affects and subjec- tive passions.19 It should be clear at this point what constitutes social cooperation here on the surfaces of imperial society: the synergies of life, or really the productive manifestations of naked life.
The Body Keeps the Score: Brain, Mind, and Body in the Healing of Trauma by Bessel van Der Kolk M. D.
anesthesia awareness, British Empire, conceptual framework, deskilling, different worldview, en.wikipedia.org, epigenetics, false memory syndrome, feminist movement, impulse control, longitudinal study, Louis Pasteur, meta analysis, meta-analysis, microbiome, Nelson Mandela, phenotype, placebo effect, profit motive, randomized controlled trial, selective serotonin reuptake inhibitor (SSRI), social intelligence, theory of mind, Yogi Berra
A. Zangi, et al., “A Mindfulness-Based Group Intervention to Reduce Psychological Distress and Fatigue in Patients with Inflammatory Rheumatic Joint Diseases: A Randomised Controlled Trial,” Annals of the Rheumatic Diseases 71, no. 6 (2012): 911–17. CHAPTER 18: FILLING IN THE HOLES: CREATING STRUCTURES 1. Pesso Boyden System Psychomotor. See http://pbsp.com/. 2. D. Goleman, Social Intelligence: The New Science of Human Relationships (Random House Digital, 2006). 3. A. Pesso, “PBSP: Pesso Boyden System Psychomotor,” in Getting in Touch: A Guide to Body-Centered Therapies, ed. S. Caldwell (Wheaton, IL: Theosophical Publishing House, 1997); A. Pesso, Movement in Psychotherapy: Psychomotor Techniques and Training (New York: New York University Press, 1969); A. Pesso, Experience in Action: A Psychomotor Psychology (New York: New York University Press, 1973); A.
The Human Swarm: How Our Societies Arise, Thrive, and Fall by Mark W. Moffett
affirmative action, barriers to entry, Berlin Wall, California gold rush, delayed gratification, demographic transition, eurozone crisis, George Santayana, glass ceiling, Howard Rheingold, invention of agriculture, invention of writing, Kevin Kelly, labour mobility, land tenure, long peace, Milgram experiment, out of africa, phenotype, Ralph Waldo Emerson, Ronald Reagan, shared worldview, Silicon Valley, social intelligence, Steve Jobs, Steven Pinker, World Values Survey
See nationalism body adornment and marking, 110, 127, 145, 153–155, 285, 380 bonobos (societies called communities), 38, 41, 43, 133, 150, 164, 203, 205, 281, 378, 386, 391 cooperation and conflict within communities of, 22, 24, 35–36, 113 cooperation and conflict between communities of, 46, 225, 228, 281 friendships between communities, 46 human relation to/comparison with, 7, 58–59, 102, 105, 136, 142, 151, 226, 232, 264 kinship patterns of, 59, 203, 205, 206–207 peacefulness of, 24, 33, 35, 46, 225, 226, 232, 244, 281 societal divisions for, 242–246, 264 societal factions with, 244 strangers, response to, 79 territoriality of, 33 tolerance between societies, 226 boundaries, social, 21, 31, 43, 88, 103–106, 182, 236, 252, 258–259, 264, 287, 315–317, 335, 341, 348–349, 353, 384 See also territories boundary regulation, 256, 392 brain size and social intelligence, 9, 19–21, 30–31, 38, 66, 68, 90–93, 144, 151, 156, 374 See also cognitive abilities; social brain hypothesis budding, 245, 247, 391 Bushmen, 88, 97, 98–99, 102, 106, 107, 108, 109, 115, 117, 119, 126, 127, 128–131, 145–146, 153, 161, 168, 171, 184, 189–190, 201–202, 207, 209, 210, 220, 230, 232, 236, 373, 374, 375, 378, 390 choice of name, versus San, 107, 375 Calusa, 130, 135, 288 cannibalism, 110–111, 223, 288 carrying capacity, 269 chiefdoms agricultural practices and accelerated rise of, 299 conflict and violence between, 288, 344, 345 definition of, 288 ethnicity and race in, 310 power structures and leadership in, 289–291, 296 mergers between, 394–395 settled hunter-gatherers as, 288 state societies relation to, 288–292, 297–298, 300 as a turning point in societies acting as a unit, 288–290 chiefs.
Blueprint: The Evolutionary Origins of a Good Society by Nicholas A. Christakis
agricultural Revolution, Alfred Russel Wallace, Amazon Mechanical Turk, assortative mating, Cass Sunstein, crowdsourcing, David Attenborough, different worldview, disruptive innovation, double helix, epigenetics, experimental economics, experimental subject, invention of agriculture, invention of gunpowder, invention of writing, iterative process, job satisfaction, Joi Ito, joint-stock company, land tenure, Laplace demon, longitudinal study, Mahatma Gandhi, Marc Andreessen, means of production, mental accounting, meta analysis, meta-analysis, microbiome, out of africa, phenotype, Pierre-Simon Laplace, placebo effect, race to the bottom, Ralph Waldo Emerson, replication crisis, Rubik’s Cube, Silicon Valley, social intelligence, social web, stem cell, Steven Pinker, the scientific method, theory of mind, twin studies, ultimatum game, zero-sum game
., “Contrasting Relatedness Patterns in Bottlenose Dolphins (Tursiops sp.) with Different Alliance Strategies,” Proceedings of the Royal Society B 270 (2003): 497–502; J. C. Mitani, “Cooperation and Competition in Chimpanzees: Current Understanding and Future Challenges,” Evolutionary Anthropology 18 (2009): 215–227. 25. Mitani, “Cooperation and Competition”; J. B. Silk et al., “Strong and Consistent Social Bonds Enhance the Longevity of Female Baboons,” Current Biology 20 (2010): 1359–1361. 26. R. C. Connor, “Dolphin Social Intelligence: Complex Alliance Relationships in Bottlenose Dolphins and a Consideration of Selective Environments for Extreme Brain Size Evolution in Mammals,” Philosophical Transactions of the Royal Society B 362 (2007): 587–602. 27. See, for example, J. E. Tanner, F. G. P. Patterson, G. Francine, and R. W. Byrne, “The Development of Spontaneous Gestures in Zoo-Living Gorillas and Sign-Taught Gorillas: From Action and Location to Object Representation,” Journal of Developmental Processes 1 (2006): 69–102; J.
The Organized Mind: Thinking Straight in the Age of Information Overload by Daniel J. Levitin
airport security, Albert Einstein, Amazon Mechanical Turk, Anton Chekhov, Bayesian statistics, big-box store, business process, call centre, Claude Shannon: information theory, cloud computing, cognitive bias, complexity theory, computer vision, conceptual framework, correlation does not imply causation, crowdsourcing, cuban missile crisis, Daniel Kahneman / Amos Tversky, delayed gratification, Donald Trump, en.wikipedia.org, epigenetics, Eratosthenes, Exxon Valdez, framing effect, friendly fire, fundamental attribution error, Golden Gate Park, Google Glasses, haute cuisine, impulse control, index card, indoor plumbing, information retrieval, invention of writing, iterative process, jimmy wales, job satisfaction, Kickstarter, life extension, longitudinal study, meta analysis, meta-analysis, more computing power than Apollo, Network effects, new economy, Nicholas Carr, optical character recognition, Pareto efficiency, pattern recognition, phenotype, placebo effect, pre–internet, profit motive, randomized controlled trial, Rubik’s Cube, shared worldview, Skype, Snapchat, social intelligence, statistical model, Steve Jobs, supply-chain management, the scientific method, The Wealth of Nations by Adam Smith, The Wisdom of Crowds, theory of mind, Thomas Bayes, Turing test, ultimatum game, zero-sum game
These leaders typically work outside of corporate structure, although like anyone, they have to work with big business at some contractual level. Nevertheless, they don’t fit the standard business-school profile of a leader who has significant economic impact. Both kinds of leaders, those inside and outside the corporate world, possess certain psychological traits. They tend to be adaptable and responsive, high in empathy, and able to see problems from all sides. These qualities require two distinct forms of cognition: social intelligence and flexible, deep analytic intelligence. An effective leader can quickly understand opposing views, how people came to hold them, and how to resolve conflicts in ways that are perceived to be mutually satisfying and beneficial. Leaders are often adept at bringing people together—suppliers, potential adversaries, competitors, characters in a story—who appear to have conflicting goals. A great business leader uses her empathy to allow people or organizations to save face in negotiations so that each side in a completed negotiation can feel they got what they wanted (and a gifted negotiator can make each side feel they got a little bit more than the other party).
The Stuff of Thought: Language as a Window Into Human Nature by Steven Pinker
airport security, Albert Einstein, Bob Geldof, colonial rule, conceptual framework, correlation does not imply causation, Daniel Kahneman / Amos Tversky, David Brooks, Douglas Hofstadter, en.wikipedia.org, experimental subject, fudge factor, George Santayana, Laplace demon, loss aversion, luminiferous ether, Norman Mailer, Richard Feynman, Ronald Reagan, Sapir-Whorf hypothesis, science of happiness, social intelligence, speech recognition, stem cell, Steven Pinker, Thomas Bayes, Thorstein Veblen, traffic fines, urban renewal, Yogi Berra
There is in the end an inescapable Rubicon. One or the other must risk . . . CONTACT. Actually, it is not a great risk; unless there is a clearly voluntary companionate pressure, anything less can be erased with an apology. However, once pressure is assayed and returned, the scene becomes electric with erotic potential.52 The ingenuity of these subterfuges shows that implicatures recruit the entirety of social intelligence and are not restricted to interpreting language itself. PASSING THE GIGGLE TEST: THE LOGIC OF NOT-SO-PLAUSIBLE DENIAL One problem remains unsolved: the psychological import of whether an overture is “on” or “off” the record in everyday conversation. The puzzle arises in cases in which two things are true. First, the Identification Problem has been solved and each party knows the other’s intentions.
Human Diversity: The Biology of Gender, Race, and Class by Charles Murray
23andMe, affirmative action, Albert Einstein, Alfred Russel Wallace, Asperger Syndrome, assortative mating, basic income, bioinformatics, Cass Sunstein, correlation coefficient, Daniel Kahneman / Amos Tversky, double helix, Drosophila, epigenetics, equal pay for equal work, European colonialism, feminist movement, glass ceiling, Gunnar Myrdal, income inequality, Kenneth Arrow, labor-force participation, longitudinal study, meta analysis, meta-analysis, out of africa, p-value, phenotype, publication bias, quantitative hedge fund, randomized controlled trial, replication crisis, Richard Thaler, risk tolerance, school vouchers, Scientific racism, selective serotonin reuptake inhibitor (SSRI), Silicon Valley, social intelligence, statistical model, Steven Pinker, The Bell Curve by Richard Herrnstein and Charles Murray, the scientific method, The Wealth of Nations by Adam Smith, theory of mind, Thomas Kuhn: the structure of scientific revolutions, twin studies, universal basic income, working-age population
In 2016, Gardner offered this retrospective on MI’s relationship to classic theories of intelligence: “But, in truth, most psychologists, and particularly most psychometricians, have never warmed to the theory. I think that psychologists are wedded to the creation and administration of short-answer tests, and particularly ones that resemble the IQ test. While such tests can probe linguistic and logical capacities, as well as certain spatial abilities, they are deficient in assessing other abilities, such as interpersonal intelligence (social intelligence), intrapersonal intelligence (akin to emotional intelligence), and other nonacademic intelligences. I have not devoted significant effort to creating such tests.” Gardner (2016): 169. I should emphasize that if you read Frames of Mind mentally substituting the word talent for intelligence and ignoring Gardner’s critique of g, there’s a lot to be learned from him. In that regard, Gardner has an amusing and I think correct observation in a 2018 interview: “I have never been able to reconstruct when I made the fateful decision not to call these abilities, talents, or gifts, but rather to call them ‘intelligences.’
The Impact of Early Life Trauma on Health and Disease by Lanius, Ruth A.; Vermetten, Eric; Pain, Clare
conceptual framework, correlation coefficient, delayed gratification, epigenetics, false memory syndrome, impulse control, intermodal, longitudinal study, meta analysis, meta-analysis, Nelson Mandela, p-value, phenotype, randomized controlled trial, selective serotonin reuptake inhibitor (SSRI), social intelligence, Socratic dialogue, theory of mind, twin studies, yellow journalism
In prospective studies, child neglect is associated with significantly delayed cognitive development and head growth in young children , and lower intelligence quotient (IQ) and academic achievement in adulthood . Chugani and colleagues  reported that previously institutionalized Romanian adoptees exhibited deficits on tasks dependent on PFC function (i.e., social and attention deficits). These children showed significantly decreased metabolism in the orbital frontal gyrus, temporal cortex, PFC, amygdala and brainstem (brain structures involved in cognitive function, social intelligence and anxiety) compared with children with chronic epilepsy and healthy adults. The corpus callosum appears particularly susceptible to the effects of early life stress. A lack of experience-dependent stimulation may lead to delays in myelination in neglected children [71,72]. To date, only a handful of studies involving maltreated children have been reported. The results of these studies suggest that pediatric maltreatment-related PTSD is associated with adverse brain development .
The Transhumanist Reader by Max More, Natasha Vita-More
23andMe, Any sufficiently advanced technology is indistinguishable from magic, artificial general intelligence, augmented reality, Bill Joy: nanobots, bioinformatics, brain emulation, Buckminster Fuller, cellular automata, clean water, cloud computing, cognitive bias, cognitive dissonance, combinatorial explosion, conceptual framework, Conway's Game of Life, cosmological principle, data acquisition, discovery of DNA, Douglas Engelbart, Drosophila, en.wikipedia.org, endogenous growth, experimental subject, Extropian, fault tolerance, Flynn Effect, Francis Fukuyama: the end of history, Frank Gehry, friendly AI, game design, germ theory of disease, hypertext link, impulse control, index fund, John von Neumann, joint-stock company, Kevin Kelly, Law of Accelerating Returns, life extension, lifelogging, Louis Pasteur, Menlo Park, meta analysis, meta-analysis, moral hazard, Network effects, Norbert Wiener, pattern recognition, Pepto Bismol, phenotype, positional goods, prediction markets, presumed consent, Ray Kurzweil, reversible computing, RFID, Ronald Reagan, scientific worldview, silicon-based life, Singularitarianism, social intelligence, stem cell, stochastic process, superintelligent machines, supply-chain management, supply-chain management software, technological singularity, Ted Nelson, telepresence, telepresence robot, telerobotics, the built environment, The Coming Technological Singularity, the scientific method, The Wisdom of Crowds, transaction costs, Turing machine, Turing test, Upton Sinclair, Vernor Vinge, Von Neumann architecture, Whole Earth Review, women in the workforce, zero-sum game
See Bartley 1962. 3 Examples include World Wide Web anchors, Microsoft Word bookmarks, Lotus Notes, and Folio Views Popup text. 4 The use of bidirectional links for decentralized consumer reports is already happening on the American Information Exchange. 5 This essay was written well before 1997, thus the fictitious tongue-in-cheek story is actually a hypothetical scenario about electronic media. References Bartley, William W. III (1962) The Retreat to Commitment. Chicago: Open Court Publishing. Drexler, K. Eric (1991) “Hypertext Publishing and the Evolution of Knowledge.” Social Intelligence 1/2. Engelbart, Douglas C. (1962) “Augmenting Human Intellect: A Conceptual Framework.” SRI Project 3578 (October). Popper, Karl R. (1950) The Open Society and its Enemies. Princeton, N.J.: Princeton University Press. Popper, Karl R. (1959) The Logic of Scientific Discovery. New York: Harper & Row. Weinberg, Gerald M. (1985) The Secrets of Consulting. New York: Dorset House Publishing.
The Blank Slate: The Modern Denial of Human Nature by Steven Pinker
affirmative action, Albert Einstein, Alfred Russel Wallace, anti-communist, British Empire, clean water, cognitive dissonance, Columbine, conceptual framework, correlation coefficient, correlation does not imply causation, cuban missile crisis, Daniel Kahneman / Amos Tversky, Defenestration of Prague, desegregation, epigenetics, Exxon Valdez, George Akerlof, germ theory of disease, ghettoisation, glass ceiling, Hobbesian trap, income inequality, invention of agriculture, invisible hand, Joan Didion, long peace, meta analysis, meta-analysis, More Guns, Less Crime, Murray Gell-Mann, mutually assured destruction, Norman Mailer, Peter Singer: altruism, phenotype, plutocrats, Plutocrats, Potemkin village, prisoner's dilemma, profit motive, QWERTY keyboard, Richard Feynman, Richard Thaler, risk tolerance, Robert Bork, Rodney Brooks, Saturday Night Live, social intelligence, speech recognition, Stanford prison experiment, stem cell, Steven Pinker, The Bell Curve by Richard Herrnstein and Charles Murray, the new new thing, theory of mind, Thomas Malthus, Thorstein Veblen, twin studies, ultimatum game, urban renewal, War on Poverty, women in the workforce, Yogi Berra, zero-sum game
As the Holy Book says, “And thou shalt not hide thyself from thine own flesh.” TAMARA [interrupting]: Uncle, he has another wife.16 Yes, within seconds of the miraculous reunion they are bickering, picking up from where they left off when they were separated a decade before. What a wealth of psychology is folded into that scene! Men’s inclination to polygamy and the frustrations it inevitably brings. Women’s keener social intelligence and their preference for verbal over physical aggression against romantic rivals. The stability of personality over the lifespan. The way that social behavior is elicited by the specifics of a situation, especially the specifics of other people, so that two people play out the same dynamic whenever they are together. Though it is a scene of considerable sadness, it has a streak of sly humor, as we watch these pathetic souls forgo their chance to savor a moment of rare good fortune and slip instead into petty quarreling.
Engineering Security by Peter Gutmann
active measures, algorithmic trading, Amazon Web Services, Asperger Syndrome, bank run, barriers to entry, bitcoin, Brian Krebs, business process, call centre, card file, cloud computing, cognitive bias, cognitive dissonance, combinatorial explosion, Credit Default Swap, crowdsourcing, cryptocurrency, Daniel Kahneman / Amos Tversky, Debian, domain-specific language, Donald Davies, Donald Knuth, double helix, en.wikipedia.org, endowment effect, fault tolerance, Firefox, fundamental attribution error, George Akerlof, glass ceiling, GnuPG, Google Chrome, iterative process, Jacob Appelbaum, Jane Jacobs, Jeff Bezos, John Conway, John Markoff, John von Neumann, Kickstarter, lake wobegon effect, Laplace demon, linear programming, litecoin, load shedding, MITM: man-in-the-middle, Network effects, Parkinson's law, pattern recognition, peer-to-peer, Pierre-Simon Laplace, place-making, post-materialism, QR code, race to the bottom, random walk, recommendation engine, RFID, risk tolerance, Robert Metcalfe, Ruby on Rails, Sapir-Whorf hypothesis, Satoshi Nakamoto, security theater, semantic web, Skype, slashdot, smart meter, social intelligence, speech recognition, statistical model, Steve Jobs, Steven Pinker, Stuxnet, telemarketer, text mining, the built environment, The Death and Life of Great American Cities, The Market for Lemons, the payments system, Therac-25, too big to fail, Turing complete, Turing machine, Turing test, web application, web of trust, x509 certificate, Y2K, zero day, Zimmermann PGP
“The Hot Hand in Basketball: On the Misperception of Random Sequences”, Thomas Gilovich, Robert Allone and Amos Tversky, Cognitive Psychology, Vol.17, No.3 (July 1985), p.295. “The Cold Facts about the ‘Hot Hand’ in Basketball”, Amos Tversky and Thomas Gilovich, in “Cognitive Psychology: Key Readings”, Psychology Press, 2004, p.643. “How we Know what Isn’t So”, Thomas Gilovich, The Free Press, 1991. “Interactional Biases in Human Thinking”, Stephen Levinson, in “Social Intelligence and Interaction: Expressions and Implications of the Social Bias in Human Intelligence”, Cambridge University Press, 1995, p.221. “The perception of randomness”, Ruma Falk, Proceedings of the Fifth Conference of the International Group for the Psychology of Mathematics Education (PME5), 1981, p.64. “Dynamical Bias in the Coin Toss”, Persi Diaconis, Susan Holmes and Richard Montgomery, SIAM Review, Vol.49, No.2 (April 2007), p.211.