Industrial robots, self-driving cars, customer-service chatbots and Google’s algorithmic predictions have brought the topic of artificial intelligence into public debate. Why is AI the source of such intense controversy and what are its economic, political, social and cultural consequences? Tracing the changing fortunes of artificial intelligence, Elliott develops a systematic account of how automated intelligent machines impact different spheres and aspects of public and private life. Among the issues discussed are the automation of workforces, surveillance capitalism, warfare and lethal autonomous weapons, the spread of racist robots and the automation of social inequalities. Elliott also considers the decisive role of AI in confronting global risks and social futures, including global pandemics such as COVID-19, and how smart algorithms are impacting the search for energy security and combating climate change. Making Sense of AI provides a judiciously comprehensive account of artificial intelligence for those with little or no previous knowledge of the topic. It will be an invaluable book both for students in the social sciences and humanities and for general readers.

Industrial robots, self-driving cars, customer-service chatbots and Google’s algorithmic predictions have brought the topic of artificial intelligence into public debate. Why is AI the source of such intense controversy and what are its economic, political, social and cultural consequences? Tracing the changing fortunes of artificial intelligence, Elliott develops a systematic account of how automated intelligent machines impact different spheres and aspects of public and private life. Among the issues discussed are the automation of workforces, surveillance capitalism, warfare and lethal autonomous weapons, the spread of racist robots and the automation of social inequalities. Elliott also considers the decisive role of AI in confronting global risks and social futures, including global pandemics such as COVID-19, and how smart algorithms are impacting the search for energy security and combating climate change. Making Sense of AI provides a judiciously comprehensive account of artificial intelligence for those with little or no previous knowledge of the topic. It will be an invaluable book both for students in the social sciences and humanities and for general readers.

A New York Times New and Noteworthy Book From the bestselling author of Waking Up and The End of Faith, an adaptation of his wildly popular, often controversial podcast “Sam Harris is the most intellectually courageous man I know, unafraid to speak truths out in the open where others keep those very same thoughts buried, fearful of the modish thought police. With his literate intelligence and fluency with words, he brings out the best in his guests, including those with whom he disagrees.” -- Richard Dawkins, author of The Selfish Gene “Civilization rests on a series of successful conversations.” —Sam Harris Sam Harris—neuroscientist, philosopher, and bestselling author—has been exploring some of the most important questions about the human mind, society, and current events on his podcast, Making Sense. With over one million downloads per episode, these discussions have clearly hit a nerve, frequently walking a tightrope where either host or guest—and sometimes both—lose their footing, but always in search of a greater understanding of the world in which we live. For Harris, honest conversation, no matter how difficult or controversial, represents the only path to moral and intellectual progress. This book includes a dozen of the best conversations from Making Sense, including talks with Daniel Kahneman, Timothy Snyder, Nick Bostrom, and Glenn Loury, on topics that range from the nature of consciousness and free will, to politics and extremism, to living ethically. Together they shine a light on what it means to “make sense” in the modern world.

From the inventor of the PalmPilot comes a new and compelling theory of intelligence, brain function, and the future of intelligent machines 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. Hawkins develops a powerful theory of how the human brain works, explaining why computers are not intelligent and how, based on this new theory, we can finally build intelligent machines. The brain is not a computer, but a memory system that stores experiences in a way that reflects the true structure of the world, remembering sequences of events and their nested relationships and making predictions based on those memories. It is this memory-prediction system that forms the basis of intelligence, perception, creativity, and even consciousness. In an engaging style that will captivate audiences from the merely curious to the professional scientist, Hawkins shows how a clear understanding of how the brain works will make it possible for us to build intelligent machines, in silicon, that will exceed our human ability in surprising ways. Written with acclaimed science writer Sandra Blakeslee, On Intelligence promises to completely transfigure the possibilities of the technology age. It is a landmark book in its scope and clarity.

Why embodied approaches to cognition are better able to address the performative dimensions of art than the dualistic conceptions fundamental to theories of digital computing. In Making Sense, Simon Penny proposes that internalist conceptions of cognition have minimal purchase on embodied cognitive practices. Much of the cognition involved in arts practices remains invisible under such a paradigm. Penny argues that the mind-body dualism of Western humanist philosophy is inadequate for addressing performative practices. Ideas of cognition as embodied and embedded provide a basis for the development of new ways of speaking about the embodied and situated intelligences of the arts. Penny argues this perspective is particularly relevant to media arts practices. Penny takes a radically interdisciplinary approach, drawing on philosophy, biology, psychology, cognitive science, neuroscience, cybernetics, artificial intelligence, critical theory, and other fields. He argues that computationalist cognitive rhetoric, with its assumption of mind-body (and software-hardware) dualism, cannot account for the quintessentially performative qualities of arts practices. He reviews post-cognitivist paradigms including situated, distributed, embodied, and enactive, and relates these to discussions of arts and cultural practices in general. Penny emphasizes the way real time computing facilitates new modalities of dynamical, generative and interactive arts practices. He proposes that conventional aesthetics (of the plastic arts) cannot address these new forms and argues for a new "performative aesthetics." Viewing these practices from embodied, enactive, and situated perspectives allows us to recognize the embodied and performative qualities of the "intelligences of the arts."

Science world luminary John Brockman assembles twenty-five of the most important scientific minds, people who have been thinking about the field artificial intelligence for most of their careers, for an unparalleled round-table examination about mind, thinking, intelligence and what it means to be human. "Artificial intelligence is today's story--the story behind all other stories. It is the Second Coming and the Apocalypse at the same time: Good AI versus evil AI." --John Brockman More than sixty years ago, mathematician-philosopher Norbert Wiener published a book on the place of machines in society that ended with a warning: "we shall never receive the right answers to our questions unless we ask the right questions.... The hour is very late, and the choice of good and evil knocks at our door." In the wake of advances in unsupervised, self-improving machine learning, a small but influential community of thinkers is considering Wiener's words again. In Possible Minds, John Brockman gathers their disparate visions of where AI might be taking us. The fruit of the long history of 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, such as computer scientist Stuart Russell, Skype co-founder Jaan Tallinn, and physicist Max Tegmark, are deeply concerned with the threat of AI, including the existential one, while others, notably robotics entrepreneur Rodney Brooks, philosopher Daniel Dennett, and bestselling author Steven Pinker, have a very different view. Serious, searching and authoritative, Possible Minds lays out the intellectual landscape of one of the most important topics of our time.

What kind of AI? -- The big puzzle -- Knowledge and behavior -- Making it and faking it -- Learning with and without experience -- Book smarts and street smarts -- The long tail and the limits to training -- Symbols and symbol processing -- Knowledge-based systems -- AI technology

Communication and artificial intelligence (AI) are closely related. It is communication – particularly interpersonal conversational interaction – that provides AI with its defining test case and experimental evidence. Likewise, recent developments in AI introduce new challenges and opportunities for communication studies. Technologies such as machine translation of human languages, spoken dialogue systems like Siri, algorithms capable of producing publishable journalistic content, and social robots are all designed to communicate with users in a human-like way. This timely and original textbook provides educators and students with a much-needed resource, connecting the dots between the science of AI and the discipline of communication studies. Clearly outlining the topic's scope, content and future, the text introduces key issues and debates, highlighting the importance and relevance of AI to communication studies. In lively and accessible prose, David Gunkel provides a new generation with the information, knowledge, and skills necessary to working and living in a world where social interaction is no longer restricted to humans. The first work of its kind, An Introduction to Communication and Artificial Intelligence is the go-to textbook for students and scholars getting to grips with this crucial interdisciplinary topic.

Two leaders in the field offer a compelling analysis of the current state of the art and reveal the steps we must take to achieve a truly robust artificial intelligence. Despite the hype surrounding AI, creating an intelligence that rivals or exceeds human levels is far more complicated than we have been led to believe. Professors Gary Marcus and Ernest Davis have spent their careers at the forefront of AI research and have witnessed some of the greatest milestones in the field, but they argue that a computer beating a human in Jeopardy! does not signal that we are on the doorstep of fully autonomous cars or superintelligent machines. The achievements in the field thus far have occurred in closed systems with fixed sets of rules, and these approaches are too narrow to achieve genuine intelligence. The real world, in contrast, is wildly complex and open-ended. How can we bridge this gap? What will the consequences be when we do? Taking inspiration from the human mind, Marcus and Davis explain what we need to advance AI to the next level, and suggest that if we are wise along the way, we won't need to worry about a future of machine overlords. If we focus on endowing machines with common sense and deep understanding, rather than simply focusing on statistical analysis and gatherine ever larger collections of data, we will be able to create an AI we can trust—in our homes, our cars, and our doctors' offices. Rebooting AI provides a lucid, clear-eyed assessment of the current science and offers an inspiring vision of how a new generation of AI can make our lives better.

How we can create artificial intelligence with broad, robust common sense rather than narrow, specialized expertise. It’s sometime in the not-so-distant future, and you send your fully autonomous self-driving car to the store to pick up your grocery order. The car is endowed with as much capability as an artificial intelligence agent can have, programmed to drive better than you do. But when the car encounters a traffic light stuck on red, it just sits there—indefinitely. Its obstacle-avoidance, lane-following, and route-calculation capacities are all irrelevant; it fails to act because it lacks the common sense of a human driver, who would quickly figure out what’s happening and find a workaround. In Machines like Us, Ron Brachman and Hector Levesque—both leading experts in AI—consider what it would take to create machines with common sense rather than just the specialized expertise of today’s AI systems. Using the stuck traffic light and other relatable examples, Brachman and Levesque offer an accessible account of how common sense might be built into a machine. They analyze common sense in humans, explain how AI over the years has focused mainly on expertise, and suggest ways to endow an AI system with both common sense and effective reasoning. Finally, they consider the critical issue of how we can trust an autonomous machine to make decisions, identifying two fundamental requirements for trustworthy autonomous AI systems: having reasons for doing what they do, and being able to accept advice. Both in the end are dependent on having common sense.