Babies were plentiful, workers outnumbered retirees, and people aspiring towards the middle class yearned to own homes and cars. Companies didn't need to see any further than Europe and the United States to do well. Printed money was legal tender for all debts, public and private. We grew up learning how to "play the game," and we expected the rules to remain the same as we took our first job, started a family, saw our children grow up, and went into retirement with our finances secure.That world—and those rules—are over.By 2030, a new reality will take hold, and before you know it:- There will be more grandparents than grandchildren- The middle-class in Asia and Sub-Saharan Africa will outnumber the US and Europe combined- The global economy will be driven by the non-Western consumer for the first time in modern history- There will be more global wealth owned by women than men- There will be more robots than workers- There will be more computers than human brains- There will be more currencies than countriesAll these trends, currently underway, will converge in the year 2030 and change everything you know about culture, the economy, and the world.According to Mauro F. Guillen, the only way to truly understand the global transformations underway—and their impacts—is to think laterally. That is, using “peripheral vision,” or approaching problems creatively and from unorthodox points of view. Rather than focusing on a single trend—climate-change or the rise of illiberal regimes, for example—Guillen encourages us to consider the dynamic inter-play between a range of forces that will converge on a single tipping point—2030—that will be, for better or worse, the point of no return.2030 is both a remarkable guide to the coming changes and an exercise in the power of “lateral thinking,” thereby revolutionizing the way you think about cataclysmic change and its consequences.

    Digital technologies—with hardware, software, and networks at their core—will in the near future diagnose diseases more accurately than doctors can, apply enormous data sets to transform retailing, and accomplish many tasks once considered uniquely human.In The Second Machine Age MIT’s Erik Brynjolfsson and Andrew McAfee—two thinkers at the forefront of their field—reveal the forces driving the reinvention of our lives and our economy. As the full impact of digital technologies is felt, we will realize immense bounty in the form of dazzling personal technology, advanced infrastructure, and near-boundless access to the cultural items that enrich our lives.Amid this bounty will also be wrenching change. Professions of all kinds—from lawyers to truck drivers—will be forever upended. Companies will be forced to transform or die. Recent economic indicators reflect this shift: fewer people are working, and wages are falling even as productivity and profits soar.Drawing on years of research and up-to-the-minute trends, Brynjolfsson and McAfee identify the best strategies for survival and offer a new path to prosperity. These include revamping education so that it prepares people for the next economy instead of the last one, designing new collaborations that pair brute processing power with human ingenuity, and embracing policies that make sense in a radically transformed landscape.A fundamentally optimistic book, The Second Machine Age alters how we think about issues of technological, societal, and economic progress.

    It is the basis for a new approach to artificial intelligence that aims to program computers to use example data or past experience to solve a given problem. In this volume in the MIT Press Essential Knowledge series, Ethem Alpayd�n offers a concise and accessible overview of the new AI. This expanded edition offers new material on such challenges facing machine learning as privacy, security, accountability, and bias. Alpayd�n, author of a popular textbook on machine learning, explains that as Big Data has gotten bigger, the theory of machine learning--the foundation of efforts to process that data into knowledge--has also advanced. He describes the evolution of the field, explains important learning algorithms, and presents example applications. He discusses the use of machine learning algorithms for pattern recognition; artificial neural networks inspired by the human brain; algorithms that learn associations between instances; and reinforcement learning, when an autonomous agent learns to take actions to maximize reward. In a new chapter, he considers transparency, explainability, and fairness, and the ethical and legal implications of making decisions based on data.

    Full of extraordinary facts and astonishing stories, The Body: A Guide for Occupants is a brilliant, often very funny attempt to understand the miracle of our physical and neurological make up.A wonderful successor to A Short History of Nearly Everything, this book will have you marvelling at the form you occupy, and celebrating the genius of your existence, time and time again.

    With a perspective that is scientific, investigative, and personal, Jennifer L. Eberhardt offers a reasoned look into the effects of implicit racial bias, ranging from the subtle to the dramatic. Racial bias can lead to disparities in education, employment, housing, and the criminal justice system--and then those very disparities further reinforce the problem. In Biased, Eberhardt reveals how even when we are not aware of bias and genuinely wish to treat all people equally, ingrained stereotypes infect our visual perception, attention, memory, and behavior.Eberhardt's extensive work as a consultant to law enforcement, as well as a researcher with unprecedented access to data, including footage from police officers' body-worn cameras, informs every aspect of her book and makes it much more than a work of social psychology. Her research occurs not just in the laboratory but in police departments, courtrooms, prisons, boardrooms, and on the street. Interviews are interwoven with memories and stories from Eberhardt's own life and family. She offers practical suggestions for reform, and takes the reader behind the scenes to police departments implementing her suggestions. Refusing to shy away from the tragic consequences of prejudice, Eberhardt addresses how racial bias is not the fault of, or restricted to, a few "bad apples" in police departments or other institutions. We can see evidence of bias at all levels of society in media, education, and business practices. In Biased, Eberhardt reminds us that racial bias is a human problem--one all people can play a role in solving.

     For his groundbreaking sexual research, Alfred Kinsey and his team interviewed 18,000 people, relying on them to honestly report their most intimate experiences. Using the Internet, the neuroscientists Ogas and Gaddam quietly observed the raw sexual behaviors of half a billion people. By combining their observations with neuroscience and animal research, these two young neuroscientists finally answer the long-disputed question: what do people really like? Ogas and Gaddam's findings are transforming the way scientists and therapists think about sexual desire. In their startling book, Ogas and Gaddam analyze a "billion wicked thoughts" on the Internet: a billion Web searches, a million individual search histories, a million erotic stories, a half-million erotic videos, a million Web sites, millions of online personal ads, and many other enormous sources of sexual data in order to understand the true differences between male and female desires, including: ?Men and women have hardwired sexual cues analogous to our hardwired tastes-there are sexual versions of sweet, sour, salty, savory, and bitter. But men and women are wired with different sets of cues. ?The male sexual brain resembles a reckless hunter, while the female sexual brain resembles a cautious detective agency. ?Men form their sexual interests during adolescence and rarely change. Women's sexual interests are plastic and change frequently. ?The male sexual brain is an "or gate": A single stimulus can arouse it. The female sexual brain is an "and gate": It requires many simultaneous stimuli to arouse it. ?When it comes to sexual arousal, men prefer overweight women to underweight women, and a significant number of men seek out erotic images of women in their 40s, 50s, and 60s. ?Women enjoy writing and sharing erotic stories with other women. The fastest growing genre of erotic stories for women are stories about two heterosexual men having sex. ?Though the male sexual brain is much more different from the female sexual brain than is commonly believed, the sexual brain of gay men is virtually identical to that of straight men. Featuring cutting-edge, jaw-dropping science, this wildly entertaining and controversial book helps readers understand their partner's sexual desires with a depth of knowledge unavailable from any other source. Its fascinating and occasionally disturbing findings will rock our modern understanding of sexuality, just as Kinsey's reports did sixty years ago.

    Later, as you're about to get back to work, a colleague taps you on the shoulder to chat. At home, screens get in the way of quality time with your family. Another day goes by, and once again, your most important personal and professional goals are put on hold.  What would be possible if you followed through on your best intentions? What could you accomplish if you could stay focused and overcome distractions? What if you had the power to become "indistractable"?  International best-selling author, former Stanford lecturer, and behavioral design expert, Nir Eyal, wrote Silicon Valley's handbook for making technology habit-forming. Five years after publishing Hooked, Eyal reveals distraction's Achilles' heel in his groundbreaking new book.  In Indistractable, Eyal reveals the hidden psychology driving us to distraction. He describes why solving the problem is not as simple as swearing off our devices: Abstinence is impractical and often makes us want more.  Eyal lays bare the secret of finally doing what you say you will do with a four-step, research-backed model. Indistractable reveals the key to getting the best out of technology, without letting it get the best of us.  Inside, Eyal overturns conventional wisdom and reveals: Why distraction at work is a symptom of a dysfunctional company culture - and how to fix it  What really drives human behavior and why "time management is pain management"  Why your relationships (and your sex life) depend on you becoming indistractable  How to raise indistractable children in an increasingly distracting world Empowering and optimistic, Indistractable provides practical, novel techniques to control your time and attention - helping you live the life you really want.

    Born in the mid-1990s to the mid-2000s and later, iGen is the first generation to spend their entire adolescence in the age of the smartphone. With social media and texting replacing other activities, iGen spends less time with their friends in person—perhaps why they are experiencing unprecedented levels of anxiety, depression, and loneliness. But technology is not the only thing that makes iGen distinct from every generation before them; they are also different in how they spend their time, how they behave, and in their attitudes toward religion, sexuality, and politics. They socialize in completely new ways, reject once sacred social taboos, and want different things from their lives and careers. More than previous generations, they are obsessed with safety, focused on tolerance, and have no patience for inequality. iGen is also growing up more slowly than previous generations: eighteen-year-olds look and act like fifteen-year-olds used to. As this new group of young people grows into adulthood, we all need to understand them: Friends and family need to look out for them; businesses must figure out how to recruit them and sell to them; colleges and universities must know how to educate and guide them. And members of iGen also need to understand themselves as they communicate with their elders and explain their views to their older peers. Because where iGen goes, so goes our nation—and the world.

    Presenting the concept of the "New Jim Code," she shows how a range of discriminatory designs encode inequity by explicitly amplifying racial hierarchies; by ignoring but thereby replicating social divisions; or by aiming to fix racial bias but ultimately doing quite the opposite. Moreover, she makes a compelling case for race itself as a kind of technology, designed to stratify and sanctify social injustice in the architecture of everyday life.This illuminating guide provides conceptual tools for decoding tech promises with sociologically informed skepticism. In doing so, it challenges us to question not only the technologies we are sold but also the ones we ourselves manufacture.If you adopt this book for classroom use in the 2019-2020 academic year, the author would be pleased to arrange to Skype to a session of your class. If interested, enter your details in this sign-up sheet https: //buff.ly/2wJsvZr

    Hackers can activate baby monitors to spy on families, thieves are analyzing social media posts to plot home invasions, and stalkers are exploiting the GPS on smart phones to track their victims’ every move. We all know today’s criminals can steal identities, drain online bank accounts, and wipe out computer servers, but that’s just the beginning. To date, no computer has been created that could not be hacked—a sobering fact given our radical dependence on these machines for everything from our nation’s power grid to air traffic control to financial services.      Yet, as ubiquitous as technology seems today, just over the horizon is a tidal wave of scientific progress that will leave our heads spinning. If today’s Internet is the size of a golf ball, tomorrow’s will be the size of the sun. Welcome to the Internet of Things, a living, breathing, global information grid where every physical object will be online. But with greater connections come greater risks. Implantable medical devices such as pacemakers can be hacked to deliver a lethal jolt of electricity and a car’s brakes can be disabled at high speed from miles away. Meanwhile, 3-D printers can produce AK-47s, bioterrorists can download the recipe for Spanish flu, and cartels are using fleets of drones to ferry drugs across borders.     With explosive insights based upon a career in law enforcement and counterterrorism, Marc Goodman takes readers on a vivid journey through the darkest recesses of the Internet. Reading like science fiction, but based in science fact, Future Crimes explores how bad actors are primed to hijack the technologies of tomorrow, including robotics, synthetic biology, nanotechnology, virtual reality, and artificial intelligence. These fields hold the power to create a world of unprecedented abundance and prosperity. But the technological bedrock upon which we are building our common future is deeply unstable and, like a house of cards, can come crashing down at any moment.     Future Crimes provides a mind-blowing glimpse into the dark side of technological innovation and the unintended consequences of our connected world. Goodman offers a way out with clear steps we must take to survive the progress unfolding before us. Provocative, thrilling, and ultimately empowering, Future Crimes will serve as an urgent call to action that shows how we can take back control over our own devices and harness technology’s tremendous power for the betterment of humanity—before it’s too late.From the Hardcover edition.

    Is it in our genes? The structure of our brains? Our genome may determine our eye color and even aspects of our personality. But our friendships, failures, and passions also shape who we are. The question is: how?Sebastian Seung, a dynamic professor at MIT, is on a quest to discover the biological basis of identity. He believes it lies in the pattern of connections between the brain’s neurons, which change slowly over time as we learn and grow. The connectome, as it’s called, is where our genetic inheritance intersects with our life experience. It’s where nature meets nurture.Seung introduces us to the dedicated researchers who are mapping the brain’s connections, neuron by neuron, synapse by synapse. It is a monumental undertaking—the scientific equivalent of climbing Mount Everest—but if they succeed, it could reveal the basis of personality, intelligence, memory, and perhaps even mental disorders. Many scientists speculate that people with anorexia, autism, and schizophrenia are "wired differently," but nobody knows for sure. The brain’s wiring has never been clearly seen.In sparklingly clear prose, Seung reveals the amazing technological advances that will soon help us map connectomes. He also examines the evidence that these maps will someday allow humans to "upload" their minds into computers, achieving a kind of immortality.Connectome is a mind-bending adventure story, told with great passion and authority. It presents a daring scientific and technological vision for at last understanding what makes us who we are. Welcome to the future of neuroscience.

    With it has come vast amounts of data in a variety of fields such as medicine, biology, finance, and marketing. The challenge of understanding these data has led to the development of new tools in the field of statistics, and spawned new areas such as data mining, machine learning, and bioinformatics. Many of these tools have common underpinnings but are often expressed with different terminology. This book describes the important ideas in these areas in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given, with a liberal use of color graphics. It should be a valuable resource for statisticians and anyone interested in data mining in science or industry. The book's coverage is broad, from supervised learning (prediction) to unsupervised learning. The many topics include neural networks, support vector machines, classification trees and boosting—the first comprehensive treatment of this topic in any book. Trevor Hastie, Robert Tibshirani, and Jerome Friedman are professors of statistics at Stanford University. They are prominent researchers in this area: Hastie and Tibshirani developed generalized additive models and wrote a popular book of that title. Hastie wrote much of the statistical modeling software in S-PLUS and invented principal curves and surfaces. Tibshirani proposed the Lasso and is co-author of the very successful An Introduction to the Bootstrap. Friedman is the co-inventor of many data-mining tools including CART, MARS, and projection pursuit.

    Mitchell covers the field of machine learning, the study of algorithms that allow computer programs to automatically improve through experience and that automatically infer general laws from specific data.

    As society stands on the cusp of unprecedented change, Jerry Kaplan unpacks the latest advances in robotics, machine learning, and perception powering systems that rival or exceed human capabilities. Driverless cars, robotic helpers, and intelligent agents that promote our interests have the potential to usher in a new age of affluence and leisure — but as Kaplan warns, the transition may be protracted and brutal unless we address the two great scourges of the modern developed world: volatile labor markets and income inequality. He proposes innovative, free-market adjustments to our economic system and social policies to avoid an extended period of social turmoil. His timely and accessible analysis of the promise and perils of artificial intelligence is a must-read for business leaders and policy makers on both sides of the aisle.

    Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning.The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. Finally, the book offers research perspectives, covering such theoretical topics as linear factor models, autoencoders, representation learning, structured probabilistic models, Monte Carlo methods, the partition function, approximate inference, and deep generative models.Deep Learning can be used by undergraduate or graduate students planning careers in either industry or research, and by software engineers who want to begin using deep learning in their products or platforms. A website offers supplementary material for both readers and instructors.