In the popular imagination, superhuman artificial intelligence is an approaching tidal wave that threatens not just jobs and human relationships, but civilization itself. Conflict between humans and machines is seen as inevitable and its outcome all too predictable. In this groundbreaking audiobook, distinguished AI researcher Stuart Russell argues that this scenario can be avoided, but only if we rethink AI from the ground up. Russell begins by exploring the idea of intelligence in humans and in machines.

Are we "noble in reason"? Perfect, in God's image? Far from it, says New York University psychologist Gary Marcus. In this lucid and revealing book, Marcus argues that the mind is not an elegantly designed organ but a "kluge", a clumsy, cobbled-together contraption. He unveils a fundamentally new way of looking at the human mind - think duct tape, not supercomputer - that sheds light on some of the most mysterious aspects of human nature.

Today's "machine-learning" systems, trained by data, are so effective that we've invited them to see and hear for us - and to make decisions on our behalf. But alarm bells are ringing. Systems cull résumés until, years later, we discover that they have inherent gender biases. Algorithms decide bail and parole - and appear to assess black and white defendants differently. We can no longer assume that our mortgage application, or even our medical tests, will be seen by human eyes. And autonomous vehicles on our streets can injure or kill.

What does it mean to be smart? To be human? What do we really want from life and the intelligence we have, or might create? With deep and exclusive reporting, across hundreds of interviews, New York Times Silicon Valley journalist Cade Metz brings you into the rooms where these questions are being answered. Where an extraordinarily powerful new artificial intelligence has been built into our biggest companies, our social discourse, and our daily lives, with few of us even noticing.

In Artificial Intelligence, Mitchell turns to the most urgent questions concerning AI today: How intelligent - really - are the best AI programs? How do they work? What can they actually do, and when do they fail? How humanlike do we expect them to become, and how soon do we need to worry about them surpassing us? Along the way, she introduces the dominant methods of modern AI and machine learning, describing cutting-edge AI programs, their human inventors, and the historical lines of thought that led to recent achievements.

We are approaching a critical threshold in the history of our species. Everything is about to change. Soon you will live surrounded by AIs. They will organize your life, operate your business, and run core government services. You will live in a world of DNA printers and quantum computers, engineered pathogens and autonomous weapons, robot assistants and abundant energy.

Under the aegis of machine learning in our data-driven machine age, computers are programming themselves and learning about - and solving - an extraordinary range of problems, from the mundane to the most daunting. Today it is machine learning programs that enable Amazon and Netflix to predict what users will like, Apple to power Siri's ability to understand voices, and Google to pilot cars.

From finding a spouse to finding a parking spot, from organizing one's inbox to understanding the workings of human memory, Algorithms to Live By transforms the wisdom of computer science into strategies for human living.

Futurists insist that AI will soon eclipse the capacities of the most gifted human mind. What hope do we have against superintelligent machines? But we aren't really on the path to developing intelligent machines. In fact, we don't even know where that path might be. Erik Larson takes us on a tour of the landscape of AI to show how far we are from superintelligence and what it would take to get there.

Superintelligence asks the questions: What happens when machines surpass humans in general intelligence? Will artificial agents save or destroy us? Nick Bostrom lays the foundation for understanding the future of humanity and intelligent life. The human brain has some capabilities that the brains of other animals lack. It is to these distinctive capabilities that our species owes its dominant position. If machine brains surpassed human brains in general intelligence, then this new superintelligence could become extremely powerful - possibly beyond our control.

The fruit of the long history of John Brockman's profound engagement with the most important scientific minds who have been thinking about AI - from Alison Gopnik and David Deutsch to Frank Wilczek and Stephen Wolfram - Possible Minds is an ideal introduction to the landscape of crucial issues AI presents. The collision between opposing perspectives is salutary and exhilarating; some of these figures are deeply concerned with the threat of AI, including the existential one, while others have a very different view.

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 map-like 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.

You may be surprised to learn that microchips are the new oil—the scarce resource on which the modern world depends. Today, military, economic, and geopolitical power are built on a foundation of computer chips. Virtually everything—from missiles to microwaves—runs on chips, including cars, smartphones, the stock market, even the electric grid. Until recently, America designed and built the fastest chips and maintained its lead as the #1 superpower, but America’s edge is in danger of slipping, undermined by players in Taiwan, Korea, and Europe taking over manufacturing.

In their bestselling first book, Prediction Machines, eminent economists Ajay Agrawal, Joshua Gans, and Avi Goldfarb explained the simple yet game-changing economics of AI. Now, in Power and Prediction, they go deeper, examining the most basic unit of analysis: the decision. The authors explain that the two key decision-making ingredients are prediction and judgment, and we perform both together in our minds, often without realizing it.

From mechanical looms to the combustion engine to the first computers, new technologies have always provoked panic about workers being replaced by machines. For centuries, such fears have been misplaced, and many economists maintain that they remain so today. But as Daniel Susskind demonstrates, this time really is different. Breakthroughs in artificial intelligence mean that all kinds of jobs are increasingly at risk.

When most of us think about artificial intelligence, our minds go straight to cyborgs, robots, and sci-fi thrillers where machines take over the world. But the truth is that artificial intelligence is already among us. It exists in our smartphones, fitness trackers, and refrigerators that tell us when the milk will expire. In some ways the future people dreamed of at the World's Fair in the 1960s is already here. We're teaching our machines how to think like humans, and they're learning at an incredible rate.

Under the aegis of machine learning in our data-driven machine age, computers are programming themselves and learning about - and solving - an extraordinary range of problems, from the mundane to the most daunting. Today it is machine learning programs that enable Amazon and Netflix to predict what users will like, Apple to power Siri's ability to understand voices, and Google to pilot cars.

In The Design of Future Things, best-selling author Donald A. Norman presents a revealing examination of smart technology, from smooth-talking GPS units to cantankerous refrigerators. Exploring the links between design and human psychology, he offers a consumer-oriented theory of natural human-machine interaction that can be put into practice by the engineers and industrial designers of tomorrows thinking machines.

Over a storied career, Daniel C. Dennett has engaged questions about science and the workings of the mind. His answers have combined rigorous argument with strong empirical grounding. And a lot of fun. Intuition Pumps and Other Tools for Thinking offers seventy-seven of Dennett’s most successful “imagination-extenders and focus-holders” meant to guide you through some of life’s most treacherous subject matter: evolution, meaning, mind, and free will.

The first book to reveal how thinking like a designer can help solve the greatest challenges we face in business, society, and our daily lives. What can we learn from the ways great designers think-and how can it improve our world? In this highly original book by journalist Warren Berger, in collaboration with celebrated designer Bruce Mau, ten groundbreaking principles of design are shown in action-addressing business, social, and personal challenges and improving the way we think, work, and live.

As we use the Web for social networking, shopping, and news, we leave a personal trail. These days, linger over a Web page selling lamps, and they will turn up at the advertising margins as you move around the Internet, reminding you, tempting you to make that purchase. Search engines such as Google can now look deep into the data on the Web to pull out instances of the words you are looking for. And there are pages that collect and assess information to give you a snapshot of changing political opinion.

In Mind in Motion, psychologist Barbara Tversky shows that spatial cognition isn't just a peripheral aspect of thought, but its very foundation, enabling us to draw meaning from our bodies and their actions in the world. Our actions in real space get turned into mental actions on thought, often spouting spontaneously from our bodies as gestures. Spatial thinking underlies creating and using maps, assembling furniture, devising football strategies, designing airports, understanding the flow of people, traffic, water, and ideas.

Jeff Hawkins, the man who created the PalmPilot, Treo smart phone, and other handheld devices, has reshaped our relationship to computers. Now he stands ready to revolutionize both neuroscience and computing in one stroke, with a new understanding of intelligence itself.

In a rarified world of scientific research, a revolution has been brewing. Its activists are not anarchists, but rather Nobel Laureates in physics and economics and pony-tailed graduates, mathematicians, and computer scientists from all over the world. They have formed an iconoclastic think-tank and their radical idea is to create a new science: complexity. They want to know how a primordial soup of simple molecules managed to turn itself into the first living cell--and what the origin of life some four billion years ago can tell us about the process of technological innovation today.

Think smart people are just born that way? Think again. Drawing on diverse studies of the mind, from psychology to linguistics, philosophy, and learning science, Art Markman, Ph.D., demonstrates the difference between "smart thinking" and raw intelligence, showing listeners how memory works, how to learn effectively, and how to use knowledge to get things done. He then introduces his own three-part formula for listeners to employ "smart thinking" in their daily lives.

We are living in a world in which cows send texts to farmers when they're in heat, where the most valuable real estate in New York City houses computers, not people, and some of humanity's greatest works are created by crowds, not individuals. We are in the midst of a networking revolution - set to transform the way we access the world's information and the way we connect with one another. Studying biological systems is perhaps the best way to understand such networks, and nature has a lesson for us if we care to listen: Bigger is rarely better in the long run.

We used to know how to know. We got our answers from books or experts. We'd nail down the facts and move on. But in the Internet age, knowledge has moved onto networks. There's more knowledge than ever, of course, but it's different. Topics have no boundaries, and nobody agrees on anything.Yet this is the greatest time in history to be a knowledge seeker - if you know how.

As a former aerospace scientist, Fortune 500 executive, chief innovation officer of two major companies, inventor and software entrepreneur, David Murray has made a living by coming up with new and innovative ideas. In Borrowing Brilliance he explains the origins and evolution of a business idea by showing you how new ideas are merely the combination of existing ideas.

Finally, we are learning that simplicity equals sanity. We’re rebelling against technology that’s too complicated, DVD players with too many menus, and software accompanied by 75-megabyte “read me” manuals. The iPod’s clean gadgetry has made simplicity hip. But sometimes we find ourselves caught up in the simplicity paradox: we want something that’s simple and easy to use, but also does all the complex things we might ever want it to do.

Through narratives and case studies spanning the brilliant history of engineering, Madhavan shows how the concepts of prototyping, efficiency, reliability, standards, optimization, and feedback are put to use in fields as diverse as transportation, retail, health care, and entertainment. Equal parts personal, practical, and profound, Applied Minds charts a path to a future where we apply strategies borrowed from engineering to create useful and inspired solutions to our most pressing challenges.

Are we "noble in reason"? Perfect, in God's image? Far from it, says New York University psychologist Gary Marcus. In this lucid and revealing book, Marcus argues that the mind is not an elegantly designed organ but a "kluge", a clumsy, cobbled-together contraption. He unveils a fundamentally new way of looking at the human mind - think duct tape, not supercomputer - that sheds light on some of the most mysterious aspects of human nature.

Under the aegis of machine learning in our data-driven machine age, computers are programming themselves and learning about - and solving - an extraordinary range of problems, from the mundane to the most daunting. Today it is machine learning programs that enable Amazon and Netflix to predict what users will like, Apple to power Siri's ability to understand voices, and Google to pilot cars.

In Artificial Intelligence, Mitchell turns to the most urgent questions concerning AI today: How intelligent - really - are the best AI programs? How do they work? What can they actually do, and when do they fail? How humanlike do we expect them to become, and how soon do we need to worry about them surpassing us? Along the way, she introduces the dominant methods of modern AI and machine learning, describing cutting-edge AI programs, their human inventors, and the historical lines of thought that led to recent achievements.

In How to Create a Mind, Ray Kurzweil presents a provocative exploration of the most important project in human-machine civilization: reverse-engineering the brain to understand precisely how it works and using that knowledge to create even more intelligent machines. Kurzweil discusses how the brain functions, how the mind emerges, brain-computer interfaces, and the implications of vastly increasing the powers of our intelligence to address the world’s problems.

Artificial intelligence does the seemingly impossible - driving cars, trading stocks, and teaching children. But facing the sea change that AI will bring can be paralyzing. How should companies set strategies, governments design policies, and people plan their lives for a world so different from what we know? In Prediction Machines, three eminent economists recast the rise of AI as a drop in the cost of prediction. With this single, masterful stroke, they lift the curtain on the AI-is-magic hype and show how basic tools from economics provide clarity about the AI revolution and a basis for action by CEOs, managers, policy makers, investors, and entrepreneurs.

Superintelligence asks the questions: What happens when machines surpass humans in general intelligence? Will artificial agents save or destroy us? Nick Bostrom lays the foundation for understanding the future of humanity and intelligent life. The human brain has some capabilities that the brains of other animals lack. It is to these distinctive capabilities that our species owes its dominant position. If machine brains surpassed human brains in general intelligence, then this new superintelligence could become extremely powerful - possibly beyond our control.

"You look like a thing and I love you" is one of the best pickup lines ever...according to an artificial intelligence trained by scientist Janelle Shane, creator of the popular blog AI Weirdness. She creates silly AIs that learn how to name paint colors, create the best recipes, and even flirt (badly) with humans — all to understand the technology that governs so much of our daily lives.

Just about every human being knows how to listen to music, but what does it take to make music? Is musicality something we are born with? Or a skill that anyone can develop at any time? If you don't start piano at the age of six, is there any hope? Is skill learning best left to children or can anyone reinvent him-or herself at any time?

What happens when artificial intelligence saturates political life and depletes the planet? How is AI shaping our understanding of ourselves and our societies? Drawing on more than a decade of research, award-winning scholar Kate Crawford reveals how AI is a technology of extraction: from the minerals drawn from the earth, to the labor pulled from low-wage information workers, to the data taken from every action and expression. This book reveals how this planetary network is fueling a shift toward undemocratic governance and increased inequity.

In their bestselling first book, Prediction Machines, eminent economists Ajay Agrawal, Joshua Gans, and Avi Goldfarb explained the simple yet game-changing economics of AI. Now, in Power and Prediction, they go deeper, examining the most basic unit of analysis: the decision. The authors explain that the two key decision-making ingredients are prediction and judgment, and we perform both together in our minds, often without realizing it.

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 map-like 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.