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Author: Hector J. Levesque
Publisher: MIT Press
Published: 2017
Total Pages: 190
ISBN-13: 0262036045
DOWNLOAD EBOOKWhat 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
Author: Hector J. Levesque
Publisher: MIT Press
Published: 2018-03-09
Total Pages: 190
ISBN-13: 0262535203
DOWNLOAD EBOOKWhat artificial intelligence can tell us about the mind and intelligent behavior. What can artificial intelligence teach us about the mind? If AI's underlying concept is that thinking is a computational process, then how can computation illuminate thinking? It's a timely question. AI is all the rage, and the buzziest AI buzz surrounds adaptive machine learning: computer systems that learn intelligent behavior from massive amounts of data. This is what powers a driverless car, for example. In this book, Hector Levesque shifts the conversation to “good old fashioned artificial intelligence,” which is based not on heaps of data but on understanding commonsense intelligence. This kind of artificial intelligence is equipped to handle situations that depart from previous patterns—as we do in real life, when, for example, we encounter a washed-out bridge or when the barista informs us there's no more soy milk. Levesque considers the role of language in learning. He argues that a computer program that passes the famous Turing Test could be a mindless zombie, and he proposes another way to test for intelligence—the Winograd Schema Test, developed by Levesque and his colleagues. “If our goal is to understand intelligent behavior, we had better understand the difference between making it and faking it,” he observes. He identifies a possible mechanism behind common sense and the capacity to call on background knowledge: the ability to represent objects of thought symbolically. As AI migrates more and more into everyday life, we should worry if systems without common sense are making decisions where common sense is needed.
Author: Ronald J. Brachman
Publisher: MIT Press
Published: 2022-05-17
Total Pages: 320
ISBN-13: 0262369222
DOWNLOAD EBOOKHow 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.
Author: Hector J. Levesque
Publisher: MIT Press
Published: 2001-02-15
Total Pages: 316
ISBN-13: 9780262263498
DOWNLOAD EBOOKThis book describes in detail the relationship between symbolic representations of knowledge and abstract states of knowledge, exploring along the way the foundations of knowledge, knowledge bases, knowledge-based systems, and knowledge representation and reasoning. The idea of knowledge bases lies at the heart of symbolic, or "traditional," artificial intelligence. A knowledge-based system decides how to act by running formal reasoning procedures over a body of explicitly represented knowledge—a knowledge base. The system is not programmed for specific tasks; rather, it is told what it needs to know and expected to infer the rest. This book is about the logic of such knowledge bases. It describes in detail the relationship between symbolic representations of knowledge and abstract states of knowledge, exploring along the way the foundations of knowledge, knowledge bases, knowledge-based systems, and knowledge representation and reasoning. Assuming some familiarity with first-order predicate logic, the book offers a new mathematical model of knowledge that is general and expressive yet more workable in practice than previous models. The book presents a style of semantic argument and formal analysis that would be cumbersome or completely impractical with other approaches. It also shows how to treat a knowledge base as an abstract data type, completely specified in an abstract way by the knowledge-level operations defined over it.
Author: Nicholas Agar
Publisher: MIT Press
Published: 2019-03-12
Total Pages: 231
ISBN-13: 0262349167
DOWNLOAD EBOOKAn argument in favor of finding a place for humans (and humanness) in the future digital economy. In the digital economy, accountants, baristas, and cashiers can be automated out of employment; so can surgeons, airline pilots, and cab drivers. Machines will be able to do these jobs more efficiently, accurately, and inexpensively. But, Nicholas Agar warns in this provocative book, these developments could result in a radically disempowered humanity. The digital revolution has brought us new gadgets and new things to do with them. The digital revolution also brings the digital economy, with machines capable of doing humans' jobs. Agar explains that developments in artificial intelligence enable computers to take over not just routine tasks but also the kind of “mind work” that previously relied on human intellect, and that this threatens human agency. The solution, Agar argues, is a hybrid social-digital economy. The key value of the digital economy is efficiency. The key value of the social economy is humanness. A social economy would be centered on connections between human minds. We should reject some digital automation because machines will always be poor substitutes for humans in roles that involve direct contact with other humans. A machine can count out pills and pour out coffee, but we want our nurses and baristas to have minds like ours. In a hybrid social-digital economy, people do the jobs for which feelings matter and machines take on data-intensive work. But humans will have to insist on their relevance in a digital age.
Author: Robert Epstein
Publisher: Springer Science & Business Media
Published: 2008-12-01
Total Pages: 520
ISBN-13: 1402096240
DOWNLOAD EBOOKAn exhaustive work that represents a landmark exploration of both the philosophical and methodological issues surrounding the search for true artificial intelligence. Distinguished psychologists, computer scientists, philosophers, and programmers from around the world debate weighty issues such as whether a self-conscious computer would create an internet ‘world mind’. This hugely important volume explores nothing less than the future of the human race itself.
Author: Simone Natale
Publisher: Oxford University Press
Published: 2021-03-03
Total Pages: 240
ISBN-13: 0190080396
DOWNLOAD EBOOKArtificial intelligence (AI) is often discussed as something extraordinary, a dream--or a nightmare--that awakens metaphysical questions on human life. Yet far from a distant technology of the future, the true power of AI lies in its subtle revolution of ordinary life. From voice assistants like Siri to natural language processors, AI technologies use cultural biases and modern psychology to fit specific characteristics of how users perceive and navigate the external world, thereby projecting the illusion of intelligence. Integrating media studies, science and technology studies, and social psychology, Deceitful Media examines the rise of artificial intelligence throughout history and exposes the very human fallacies behind this technology. Focusing specifically on communicative AIs, Natale argues that what we call "AI" is not a form of intelligence but rather a reflection of the human user. Using the term "banal deception," he reveals that deception forms the basis of all human-computer interactions rooted in AI technologies, as technologies like voice assistants utilize the dynamics of projection and stereotyping as a means for aligning with our existing habits and social conventions. By exploiting the human instinct to connect, AI reveals our collective vulnerabilities to deception, showing that what machines are primarily changing is not other technology but ourselves as humans. Deceitful Media illustrates how AI has continued a tradition of technologies that mobilize our liability to deception and shows that only by better understanding our vulnerabilities to deception can we become more sophisticated consumers of interactive media.
Author: Herbert L. Roitblat
Publisher: MIT Press
Published: 2020-10-13
Total Pages: 340
ISBN-13: 0262044129
DOWNLOAD EBOOKWhy a new approach is needed in the quest for general artificial intelligence. Since the inception of artificial intelligence, we have been warned about the imminent arrival of computational systems that can replicate human thought processes. Before we know it, computers will become so intelligent that humans will be lucky to kept as pets. And yet, although artificial intelligence has become increasingly sophisticated—with such achievements as driverless cars and humanless chess-playing—computer science has not yet created general artificial intelligence. In Algorithms Are Not Enough, Herbert Roitblat explains how artificial general intelligence may be possible and why a robopocalypse is neither imminent, nor likely. Existing artificial intelligence, Roitblat shows, has been limited to solving path problems, in which the entire problem consists of navigating a path of choices—finding specific solutions to well-structured problems. Human problem-solving, on the other hand, includes problems that consist of ill-structured situations, including the design of problem-solving paths themselves. These are insight problems, and insight is an essential part of intelligence that has not been addressed by computer science. Roitblat draws on cognitive science, including psychology, philosophy, and history, to identify the essential features of intelligence needed to achieve general artificial intelligence. Roitblat describes current computational approaches to intelligence, including the Turing Test, machine learning, and neural networks. He identifies building blocks of natural intelligence, including perception, analogy, ambiguity, common sense, and creativity. General intelligence can create new representations to solve new problems, but current computational intelligence cannot. The human brain, like the computer, uses algorithms; but general intelligence, he argues, is more than algorithmic processes.
Author: Dean Buonomano
Publisher: W. W. Norton & Company
Published: 2017-04-04
Total Pages: 357
ISBN-13: 0393247953
DOWNLOAD EBOOK"Beautifully written, eloquently reasoned…Mr. Buonomano takes us off and running on an edifying scientific journey." —Carol Tavris, Wall Street Journal In Your Brain Is a Time Machine, leading neuroscientist Dean Buonomano embarks on an "immensely engaging" exploration of how time works inside the brain (Barbara Kiser, Nature). The human brain, he argues, is a complex system that not only tells time, but creates it; it constructs our sense of chronological movement and enables "mental time travel"—simulations of future and past events. These functions are essential not only to our daily lives but to the evolution of the human race: without the ability to anticipate the future, mankind would never have crafted tools or invented agriculture. This virtuosic work of popular science will lead you to a revelation as strange as it is true: your brain is, at its core, a time machine.
Author: Melanie Mitchell
Publisher: Farrar, Straus and Giroux
Published: 2019-10-15
Total Pages: 216
ISBN-13: 0374715238
DOWNLOAD EBOOK“After reading Mitchell’s guide, you’ll know what you don’t know and what other people don’t know, even though they claim to know it. And that’s invaluable." –The New York Times A leading computer scientist brings human sense to the AI bubble No recent scientific enterprise has proved as alluring, terrifying, and filled with extravagant promise and frustrating setbacks as artificial intelligence. The award-winning author Melanie Mitchell, a leading computer scientist, now reveals AI’s turbulent history and the recent spate of apparent successes, grand hopes, and emerging fears surrounding it. 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 models of modern AI and machine learning, describing cutting-edge AI programs, their human inventors, and the historical lines of thought underpinning recent achievements. She meets with fellow experts such as Douglas Hofstadter, the cognitive scientist and Pulitzer Prize–winning author of the modern classic Gödel, Escher, Bach, who explains why he is “terrified” about the future of AI. She explores the profound disconnect between the hype and the actual achievements in AI, providing a clear sense of what the field has accomplished and how much further it has to go. Interweaving stories about the science of AI and the people behind it, Artificial Intelligence brims with clear-sighted, captivating, and accessible accounts of the most interesting and provocative modern work in the field, flavored with Mitchell’s humor and personal observations. This frank, lively book is an indispensable guide to understanding today’s AI, its quest for “human-level” intelligence, and its impact on the future for us all.
