Jill Lepore, best-selling author of These Truths, came across the company’s papers in MIT’s archives and set out to tell this forgotten history, the long-lost backstory to the methods, and the arrogance, of Silicon Valley.Founded in 1959 by some of the nation’s leading social scientists—“the best and the brightest, fatally brilliant, Icaruses with wings of feathers and wax, flying to the sun”—Simulmatics proposed to predict and manipulate the future by way of the computer simulation of human behavior. In summers, with their wives and children in tow, the company’s scientists met on the beach in Long Island under a geodesic, honeycombed dome, where they built a “People Machine” that aimed to model everything from buying a dishwasher to counterinsurgency to casting a vote. Deploying their “People Machine” from New York, Washington, Cambridge, and even Saigon, Simulmatics’ clients included the John F. Kennedy presidential campaign, the New York Times, the Department of Defense, and dozens of major manufacturers: Simulmatics had a hand in everything from political races to the Vietnam War to the Johnson administration’s ill-fated attempt to predict race riots. The company’s collapse was almost as rapid as its ascent, a collapse that involved failed marriages, a suspicious death, and bankruptcy. Exposed for false claims, and even accused of war crimes, it closed its doors in 1970 and all but vanished. Until Lepore came across the records of its remains.The scientists of Simulmatics believed they had invented “the A-bomb of the social sciences.” They did not predict that it would take decades to detonate, like a long-buried grenade. But, in the early years of the twenty-first century, that bomb did detonate, creating a world in which corporations collect data and model behavior and target messages about the most ordinary of decisions, leaving people all over the world, long before the global pandemic, crushed by feelings of helplessness. This history has a past; If Then is its cautionary tale.

    Based on the work of W. Edwards Deming and on Dr. Glasser's own choice theory, it is written for teachers who are trying to abandon the old system of boss-managing, which is effective for less than half of all students. William Glasser, M.D., explains that only through lead-management can teachers create classrooms in which all students not only do competent work but begin to do quality work. These classrooms are the core of a quality school. The book begins by explaining that to persuade students to do quality schoolwork, teachers must first establish warm, totally noncoercive relationships with their students; teach only useful material, which means stressing skills rather than asking students to memorize information; and move from teacher evaluation to student self-evaluation. There are no generalities in this book: It provides the specifics that classroom teachers seek as they begin the move to quality schools.

    If you're like most people, you probably believe that humans are the most intelligent animals on our planet. But there's another kind of entity that can be far smarter: groups of people. In this groundbreaking book, Thomas Malone, the founding director of the MIT Center for Collective Intelligence, shows how groups of people working together in superminds -- like hierarchies, markets, democracies, and communities -- have been responsible for almost all human achievements in business, government, science, and beyond. And these collectively intelligent human groups are about to get much smarter. Using dozens of striking examples and case studies, Malone shows how computers can help create more intelligent superminds simply by connecting humans to one another in a variety of rich, new ways. And although it will probably happen more gradually than many people expect, artificially intelligent computers will amplify the power of these superminds by doing increasingly complex kinds of thinking. Together, these changes will have far-reaching implications for everything from the way we buy groceries and plan business strategies to how we respond to climate change, and even for democracy itself. By understanding how these collectively intelligent groups work, we can learn how to harness their genius to achieve our human goals. Drawing on cutting-edge science and insights from a remarkable range of disciplines, Superminds articulates a bold -- and utterly fascinating -- picture of the future that will change the ways you work and live, both with other people and with computers.

    But it's also more importantly about a community of people who are trying to think rationally about intelligence, and the places that these thoughts are taking them, and what insight they can and can't give us about the future of the human race over the next few years. It explains why these people are worried, why they might be right, and why they might be wrong. It is a book about the cutting edge of our thinking on intelligence and rationality right now by the people who stay up all night worrying about it.Along the way, we discover why we probably don't need to worry about a future AI resurrecting a perfect copy of our minds and torturing us for not inventing it sooner, but we perhaps should be concerned about paperclips destroying life as we know it; how Mickey Mouse can teach us an important lesson about how to program AI; and how a more rational approach to life could be what saves us all.

    Admittedly, computers now play chess at the grandmaster level, but do they understand the game as we do? Can a computer eventually do everything a human mind can do? In this absorbing and frequently contentious book, Roger Penrose--eminent physicist and winner, with Stephen Hawking, of the prestigious Wolf prize--puts forward his view that there are some facets of human thinking that can never be emulated by a machine. Penrose examines what physics and mathematics can tell us about how the mind works, what they can't, and what we need to know to understand the physical processes of consciousness. He is among a growing number of physicists who think Einstein wasn't being stubborn when he said his little finger told him that quantum mechanics is incomplete, and he concludes that laws even deeper than quantum mechanics are essential for the operation of a mind. To support this contention, Penrose takes the reader on a dazzling tour that covers such topics as complex numbers, Turing machines, complexity theory, quantum mechanics, formal systems, Godel undecidability, phase spaces, Hilbert spaces, black holes, white holes, Hawking radiation, entropy, quasicrystals, the structure of the brain, and scores of other subjects. The Emperor's New Mind will appeal to anyone with a serious interest in modern physics and its relation to philosophical issues, as well as to physicists, mathematicians, philosophers and those on either side of the AI debate.

      Statistics are everywhere, as integral to science as they are to business, and in the popular media hundreds of times a day. In this age of big data, a basic grasp of statistical literacy is more important than ever if we want to separate the fact from the fiction, the ostentatious embellishments from the raw evidence -- and even more so if we hope to participate in the future, rather than being simple bystanders. In The Art of Statistics, world-renowned statistician David Spiegelhalter shows readers how to derive knowledge from raw data by focusing on the concepts and connections behind the math. Drawing on real world examples to introduce complex issues, he shows us how statistics can help us determine the luckiest passenger on the Titanic, whether a notorious serial killer could have been caught earlier, and if screening for ovarian cancer is beneficial. The Art of Statistics not only shows us how mathematicians have used statistical science to solve these problems -- it teaches us how we too can think like statisticians. We learn how to clarify our questions, assumptions, and expectations when approaching a problem, and -- perhaps even more importantly -- we learn how to responsibly interpret the answers we receive. Combining the incomparable insight of an expert with the playful enthusiasm of an aficionado, The Art of Statistics is the definitive guide to stats that every modern person needs.

    As Carl Benedikt Frey shows, the Industrial Revolution created unprecedented wealth and prosperity over the long run, but the immediate consequences of mechanization were devastating for large swaths of the population. Middle-income jobs withered, wages stagnated, the labor share of income fell, profits surged, and economic inequality skyrocketed. These trends, Frey documents, broadly mirror those in our current age of automation, which began with the Computer Revolution.Just as the Industrial Revolution eventually brought about extraordinary benefits for society, artificial intelligence systems have the potential to do the same. But Frey argues that this depends on how the short term is managed. In the nineteenth century, workers violently expressed their concerns over machines taking their jobs. The Luddite uprisings joined a long wave of machinery riots that swept across Europe and China. Today’s despairing middle class has not resorted to physical force, but their frustration has led to rising populism and the increasing fragmentation of society. As middle-class jobs continue to come under pressure, there’s no assurance that positive attitudes to technology will persist.The Industrial Revolution was a defining moment in history, but few grasped its enormous consequences at the time. The Technology Trap demonstrates that in the midst of another technological revolution, the lessons of the past can help us to more effectively face the present.

    It’s not only blue-collar jobs at stake. Millions of educated knowledge workers—writers, paralegals, assistants, medical technicians—are threatened by accelerating advances in artificial intelligence. The industrial revolution shifted workers from farms to factories. In the first era of automation, machines relieved humans of manually exhausting work. Today, Era Two of automation continues to wash across the entire services-based economy that has replaced jobs in agriculture and manufacturing. Era Three, and the rise of AI, is dawning. Smart computers are demonstrating they are capable of making better decisions than humans. Brilliant technologies can now decide, learn, predict, and even comprehend much faster and more accurately than the human brain, and their progress is accelerating. Where will this leave lawyers, nurses, teachers, and editors?In Only Humans Need Apply, Thomas Hayes Davenport and Julia Kirby reframe the conversation about automation, arguing that the future of increased productivity and business success isn’t either human or machine. It’s both. The key is augmentation, utilizing technology to help humans work better, smarter, and faster. Instead of viewing these machines as competitive interlopers, we can see them as partners and collaborators in creative problem solving as we move into the next era. The choice is ours.

    For all of neuroscience's advances, we've made little progress on its biggest question: How do simple cells in the brain create intelligence? Jeff Hawkins and his team discovered that the brain uses maplike structures to build a model of the world-not just one model, but hundreds of thousands of models of everything we know. This discovery allows Hawkins to answer important questions about how we perceive the world, why we have a sense of self, and the origin of high-level thought.

    There are updates throughout the book as well. These take into account important advances in cognitive psychology and the science of design while confirming and extending the book's basic thesis: that a physical symbol system has the necessary and sufficient means for intelligent action. The chapter "Economic Reality" has also been revised to reflect a change in emphasis in Simon's thinking about the respective roles of organizations and markets in economic systems."People sometimes ask me what they should read to find out about artificial intelligence. Herbert Simon's book The Sciences of the Artificial is always on the list I give them. Every page issues a challenge to conventional thinking, and the layman who digests it well will certainly understand what the field of artificial intelligence hopes to accomplish. I recommend it in the same spirit that I recommend Freud to people who ask about psychoanalysis, or Piaget to those who ask about child psychology: If you want to learn about a subject, start by reading its founding fathers." -- George A. Miller

    They can navigate more data than a doctor or lawyer and act with greater precision. For many years we’ve taken solace in the notion that they can’t create. But now that algorithms can learn and adapt, does the future of creativity belong to machines, too?It is hard to imagine a better guide to the bewildering world of artificial intelligence than Marcus du Sautoy, a celebrated Oxford mathematician whose work on symmetry in the ninth dimension has taken him to the vertiginous edge of mathematical understanding. In The Creativity Code he considers what machine learning means for the future of creativity. The Pollockizer can produce drip paintings in the style of Jackson Pollock, Botnik spins off fanciful (if improbable) scenes inspired by J. K. Rowling, and the music-composing algorithm Emmy managed to fool a panel of Bach experts. But do these programs just mimic, or do they have what it takes to create? Du Sautoy argues that to answer this question, we need to understand how the algorithms that drive them work―and this brings him back to his own subject of mathematics, with its puzzles, constraints, and enticing possibilities.While most recent books on AI focus on the future of work, The Creativity Code moves us to the forefront of creative new technologies and offers a more positive and unexpected vision of our future cohabitation with machines. It challenges us to reconsider what it means to be human―and to crack the creativity code.

    It can also be maintained that it is best to provide the machine with the best sense organs that money can buy, and then teach it to understand and speak English. This process could follow the normal teaching of a child. Things would be pointed out and named, etc. Again I do not know what the right answer is, but I think both approaches should be tried."The first approach has been tried many times in both science fiction and reality. In this new novella, at over 30,000 words, his longest work to date, Ted Chiang offers a detailed imagining of how the second approach might work within the contemporary landscape of startup companies, massively-multiplayer online gaming, and open-source software. It's a story of two people and the artificial intelligences they helped create, following them for more than a decade as they deal with the upgrades and obsolescence that are inevitable in the world of software. At the same time, it's an examination of the difference between processing power and intelligence, and of what it means to have a real relationship with an artificial entity.

    It seems so ordinary, everyone does it. Actually it's more of a black box, which Dehaene cracks open to reveal the awesome secrets within."--The New York Times Book Review An illuminating dive into the latest science on our brain's remarkable learning abilities and the potential of the machines we program to imitate themThe human brain is an extraordinary learning machine. Its ability to reprogram itself is unparalleled, and it remains the best source of inspiration for recent developments in artificial intelligence. But how do we learn? What innate biological foundations underlie our ability to acquire new information, and what principles modulate their efficiency?In How We Learn, Stanislas Dehaene finds the boundary of computer science, neurobiology, and cognitive psychology to explain how learning really works and how to make the best use of the brain's learning algorithms in our schools and universities, as well as in everyday life and at any age.

    Scientists have made progress: computers can now beat chess grandmasters and help prevent terrorist attacks. Yet we still await a machine that exhibits the rich complexity of human thought — one that doesn’t just crunch numbers, or take us to a relevant Web page, but understands us and gives us what we need.That vision has driven a team of engineers at IBM. Over three years, they created “Watson” and prepared it for a showdown on Jeopardy!, where it would take on two of the game’s all-time champions, Ken Jennings and Brad Rutter, in a nationally televised event. Final Jeopardy is the entertaining, illuminating story of that computer and that epic match.It’s a classic tale of Man vs. Machine. Like its human competitors, Watson has to understand language, including puns and irony, and master everything from history, literature, and science to arts, entertainment, and game strategy. After years of training, Watson can find the scrambled state capital in “Hair Gel” (“What is Raleigh?”) and even come up with the facial accessory that made Moshe Dayan recognizable worldwide (“What is an eye patch?”). Watson may just be the smartest machine on earth.Final Jeopardy traces the arc of Watson’s “life,” from its birth in the IBM labs to its big night on the podium. We meet Hollywood moguls and Jeopardy! masters, genius computer programmers and ambitious scientists, including Watson’s eccentric creator, David Ferrucci. We gain access to Ferrucci’s War Room, where the IBM team works tirelessly to boost Watson’s speed to the buzzer, improve its performance in “train wreck” categories (such as “Books in Español”), and fix glitches like the speech defect Watson developed during its testing phase, when it started adding a d to words ending in n (“What is Pakistand?”).Much is at stake, especially for IBM. A new generation of Watsons could transform medicine, the law, marketing, even science itself, as machines process huge amounts of data at lightning speed, answer our questions, and possibly come up with new hypotheses.Showdown aside, it’s clear that the future has arrived. But with it come questions: Where does it leave humans? What will Watson’s heirs be capable of in ten or twenty years? Is it time to declare defeat in the realm of facts? What should we teach our children? And what should we carry around in our own heads?Final Jeopardy takes on these questions and more in a narrative that’s as fast and fun as the game itself. Baker shows us how smart machines will fit into our world — and how they’ll disrupt it. www.finaljeopardy.net

    Pulitzer prize-winning New York Times science writer John Markoff argues that we must decide to design ourselves into our future, or risk being excluded from it altogether.In the past decade, Google introduced us to driverless cars; Apple debuted Siri, a personal assistant that we keep in our pockets; and an Internet of Things connected the smaller tasks of everyday life to the farthest reaches of the Web. Robots have become an integral part of society on the battlefield and the road; in business, education, and health care. Cheap sensors and powerful computers will ensure that in the coming years, these robots will act on their own. This new era offers the promise of immensely powerful machines, but it also reframes a question first raised more than half a century ago, when the intelligent machine was born. Will we control these systems, or will they control us?In Machines of Loving Grace, John Markoff offers a sweeping history of the complicated and evolving relationship between humans and computers. In recent years, the pace of technological change has accelerated dramatically, posing an ethical quandary. If humans delegate decisions to machines, who will be responsible for the consequences? As Markoff chronicles the history of automation, from the birth of the artificial intelligence and intelligence augmentation communities in the 1950s and 1960s, to the modern-day brain trusts at Google and Apple in Silicon Valley, and on to the expanding robotics economy around Boston, he traces the different ways developers have addressed this fundamental problem and urges them to carefully consider the consequences of their work. We are on the brink of the next stage of the computer revolution, Markoff argues, and robots will profoundly transform modern life. Yet it remains for us to determine whether this new world will be a utopia. Moreover, it is now incumbent upon the designers of these robots to draw a bright line between what is human and what is machine.After nearly forty years covering the tech industry, Markoff offers an unmatched perspective on the most drastic technology-driven societal shifts since the introduction of the Internet. Machines of Loving Grace draws on an extensive array of research and interviews to present an eye-opening history of one of the most pressing questions of our time, and urges us to remember that we still have the opportunity to design ourselves into the future—before it's too late.