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Artificial Intelligence: A Guide for Thinking Humans Hardcover – October 15, 2019
Melanie Mitchell separates science fact from science fiction in this sweeping examination of the current state of AI and how it is remaking our world
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.
- Print length336 pages
- LanguageEnglish
- PublisherFarrar, Straus and Giroux
- Publication dateOctober 15, 2019
- Dimensions6.31 x 1.17 x 9.37 inches
- ISBN-100374257833
- ISBN-13978-0374257835
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Editorial Reviews
Review
"Mitchell knows what she’s talking about. Even better, she’s a clear, cogent and interesting writer . . . Artificial Intelligence has significantly improved my knowledge when it comes to automation technology, [but] the greater benefit is that it has also enhanced my appreciation for the complexity and ineffability of human cognition."―John Warner, Chicago Tribune
"Without shying away from technical details, this survey provides an accessible course in neural networks, computer vision, and natural-language processing, and asks whether the quest to produce an abstracted, general intelligence is worrisome . . . Mitchell’s view is a reassuring one." ―The New Yorker
"In Mitchell’s telling, artificial intelligence (AI) raises extraordinary issues that have disquieting implications for humanity. AI isn’t for the faint of heart, and neither is this book for nonscientists . . . she is a good writer with broad knowledge of the topic . . . and a canny mindfulness of both the merits and problems of AI." ―Howard Schneider, Undark
"Artificial intelligence can trounce you at chess, but will mistake a school bus for an ostrich or make bizarre connections between birds and hydrants. Mitchell cuts through the hype that the field of A.I. is often prone to and lays out what it does well, where it fails, and how it might do better." ―George Musser, author of Spooky Action at a Distance
"The recent resurgence of AI has led to predictions of everything from the end of the world to immortality. Melanie Mitchell’s very intelligent, clear and sensible book is a welcome corrective to the exaggerated fears and hopes for AI, and the prefect primer to start understanding how the systems actually work." ―Alison Gopnik, professor of Psychology at UC Berkeley, and author of The Philosophical Baby
"Melanie Mitchell writes about AI with a warm, friendly voice and an unpretentious brilliance that no machine could hope to match...for now." ―Steven Strogatz, professor of mathematics, Cornell University, and author of Infinite Powers
"Melanie Mitchell’s book is a must read for anyone interested in the emerging revolution of AI, machine learning and big data. She provides a remarkably lucid and comprehensive overview not just of their power and potential in shaping life in the 21st century but, perhaps more importantly, of their shortcomings and dangers. Mitchell brings a holistic, integrated perspective for understanding what these terms actually mean and the capabilities they promise in a non-technical language that any of us can appreciate. At the same time, she lays bare the hyperbole and misconceptions that are being propagated in the media. This book can be, and should be, read by the proverbial man or woman-on-the-street, the silicon valley guru, members of congress, or a student of the humanities, as well as by professional scientists and engineers. They will all profit enormously from it." ―Geoffrey West, distinguished professor at the Santa Fe Institute, and author of Scale: The Universal Laws of Life, Growth, and Death in Organisms, Cities, and Companies
“If you think you understand AI and all of the related issues, you don’t. By the time you finish this exceptionally lucid and riveting book you will breathe more easily and wisely.” ―Michael S. Gazzaniga, Director of the SAGE Center for the Study of Mind, University of California-Santa Barbara, and author of The Consciousness Instinct
"Computers are capable of feats of astonishing intelligence, while at the same time lacking any semblance of common sense. Melanie Mitchell takes us through an enlightening tour of how artificial intelligence currently works, and how it falls short of true human understanding. The challenges and opportunities discussed in this book will be crucial in shaping the future of humanity and technology." ―Sean Carroll, author of Something Deeply Hidden: Quantum Worlds and the Emergence of Spacetime
“Melanie Mitchell deftly provides the reader with a keen, clear-sighted account of the history of AI and neural networks. She explores refinements of the Turing Test, Ray Kurzweil’s Singularity (a little dubiously), deep machine learning, computer vision, translation programs, ethical issues, and many other topics, their history, modern development, and the ebb and flow of the hype surrounding their various incarnations. What is most impressive is that without getting too technical, Mitchell sketches enough details and clever illustrations that one gets a good intuitive understanding of AI, both its special purpose machines and its attempts at developing a more general intelligence. A wonderfully informative book.” ―John Allen Paulos, Professor of Mathematics, Temple University, and author of Innumeracy: Mathematical Illiteracy and its Consequences
"Melanie Mitchell nails it: current AI does all kinds of neat tricks, but there’s no real understanding there, and until there is, we will never get to the real promise of AI." ―Gary Marcus, Founder and CEO of Robust.AI and co-author of Rebooting AI
About the Author
Product details
- Publisher : Farrar, Straus and Giroux; First Edition (October 15, 2019)
- Language : English
- Hardcover : 336 pages
- ISBN-10 : 0374257833
- ISBN-13 : 978-0374257835
- Item Weight : 1.2 pounds
- Dimensions : 6.31 x 1.17 x 9.37 inches
- Best Sellers Rank: #564,621 in Books (See Top 100 in Books)
- #587 in Computer History & Culture (Books)
- #1,116 in Artificial Intelligence & Semantics
- #25,113 in Social Sciences (Books)
- Customer Reviews:
About the author
Melanie Mitchell is a professor at the Santa Fe Institute. Melanie's book "Complexity: A Guided Tour" won the 2010 Phi Beta Kappa Science Book Award, was named by Amazon.com as one of the ten best science books of 2009, and was longlisted for the Royal Society's 2010 book prize. Her newest book is "Artificial Intelligence: A Guide for Thinking Humans".
Melanie originated the Santa Fe Institute's Complexity Explorer project, which offers free online courses related to complex systems. For more information, go to http://complexityexplorer.org.
Customer reviews
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Customers find the book provides a good overview of artificial intelligence and its history. They appreciate the author's clear writing style that breaks through the hype. The book is described as an entertaining read with just the right level of detail. Readers find the writing clear and intuitive, while still providing a thorough understanding of the topics. However, opinions differ on the visual content, with some finding it helpful and others feeling it gets a bit technical at times.
AI-generated from the text of customer reviews
Customers find the book provides a good overview of artificial intelligence. They appreciate the author's ability to summarize complex topics in a way that is understandable for lay readers. The book provides a great overview of the history of AI and different approaches. It offers a fascinating insight into how AI works and takes both lay people and technically proficient readers along for the information, entertaining ride. Readers appreciate the sober view of the progress and lack of progress in AI. There are many quotable materials and an excellent, up-to-the-minute survey of the capabilities of artificial intelligence.
"...(one would really like to know what she thinks of them) the book is the most accessible, thorough, objective and still profound introduction to this..." Read more
"...part (Part V: The Barrier of Meaning) where Melanie beautifully develops the frameworks, concepts, illustrations and examples you need to deeply..." Read more
"...Ms. Mitchell, however lends a fascinating insight into the myriad ways in which various intrepid pioneers and computer experts attempted to distill..." Read more
"Great book albeit a bit technical, but it is a must read to understand how AI works by showing how it is programmed...." Read more
Customers find the book's writing clear and intuitive. They appreciate the author's general approach and well-defined technical terms. The book provides a comprehensive overview of the state of AI today, providing a look under the hood.
"...the book is the most accessible, thorough, objective and still profound introduction to this fundamental change in..." Read more
"...develops the frameworks, concepts, illustrations and examples you need to deeply understand what it really means for humans to understand "meaning"..." Read more
"...Portland State University takes this conundrum head on in her eminently readable book, ““Artificial Intelligence: A Guide for Thinking Humans.”..." Read more
"...Best read of the year for me. A wonderful, readable, concise review of AI progress during the past 75 years, and a clear exposition of..." Read more
Customers find the book readable and entertaining. They describe it as helpful and informative, with a good sense of humor. The book provides a concise review of AI progress during the last few years.
"This layman found this very enjoyable read to provide an extraordinary clarification of what AI is: where it came from, it's future, and whether it..." Read more
"...Best read of the year for me. A wonderful, readable, concise review of AI progress during the past 75 years, and a clear exposition of..." Read more
"Great book albeit a bit technical, but it is a must read to understand how AI works by showing how it is programmed...." Read more
"...A good sense of humor (and wonder). 3) Lots of figures and diagrams, which really help comprehension...." Read more
Customers find the book provides a good overview of AI with just the right level of detail. They appreciate the explanations of algorithms and methods in an easy-to-understand style. The book also provides a good survey of AI history and methods at a high level.
"...A wonderful, readable, concise review of AI progress during the past 75 years, and a clear exposition of why what we have accomplished, while..." Read more
"...Bottom-line – This is the best book on AI for the general science/technology reader." Read more
"This is a far-reaching account of the history, key concepts, algorithms, limitations and current state of AI along with the personal perspective of..." Read more
"...explains the algorithms in an easy-to-understand style, and points at the limitations of..." Read more
Customers have different views on the visual content. Some find the writing clear and supported by numerous visual examples, figures, and diagrams that help comprehension. Others feel the book gets a bit technical at times and lacks more general capabilities for abstraction and understanding.
"...Both books are technically accurate, and have a lot of great examples...." Read more
"Great book albeit a bit technical, but it is a must read to understand how AI works by showing how it is programmed...." Read more
"...A good sense of humor (and wonder). 3) Lots of figures and diagrams, which really help comprehension...." Read more
"...human champions at Jeopardy and GO, it lacks more general capabilities for abstraction and understanding...." Read more
Top reviews from the United States
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- Reviewed in the United States on August 22, 2024This layman found this very enjoyable read to provide an extraordinary clarification of what AI is: where it came from, it's future, and whether it will be our salvation or our doom. Although it's slightly out of date since it was published before the "chat"LLM's emerged (one would really like to know what she thinks of them) the book is the most accessible, thorough, objective and still profound introduction to this fundamental change in our lives I have seen.
- Reviewed in the United States on December 28, 2019Thank you Prof Melanie Mitchell for the labor of love and commitment required to create your latest book, Artificial Intelligence A guide for Thinking Humans."
The book is divided into four parts, with the first part serving as an introduction with appropriate historical background, and an update on current important concepts, developments and supporting terminology.
Following the introduction, one core aspect of the book are the three main parts-- each with multiple chapters-- where Melanie explains the fundamentals, workings and applications of of of neural networks and image processing (Part II, Looking and Seeing), of reinforcement learning and game playing (Part III, Learning to Play), and of language processing (Part IV: Artificial Intelligence Meet Natural Language).
If you are a manager or policy maker who desires a technically accurate and precise description of the foundations and key enabling mechanisms of these AI capabilities-- in order to strengthen your own understanding--- and your own "mental models" of what this technology is and how it really works--- the descriptions in this book are amongst the very best descriptions I have every come across (and I do a lot of reading in this area for both technical specialist and for broader audiences).
The second core aspect of this book is the final part (Part V: The Barrier of Meaning) where Melanie beautifully develops the frameworks, concepts, illustrations and examples you need to deeply understand what it really means for humans to understand "meaning" and context, and to make intelligent inferences, predictions, abstractions and analogies based on this ability versus what very brittle and very limited ability of state-of-the-art AI systems to do so.
Just these four chapters in Part V ( On Understanding; Knowledge, Abstraction, and Analogy in Artificial Intelligence; and Questions, Answers, and Speculations) justifies the effort to purchase and carefully read this book.
I think Prof Melanie Mitchell has done modern society a great service by creating this book. She makes it possible for a broad range of people-- from a broad range of backgrounds--- to seriously understand the marvels of AI capabilities and accomplishments, how these capabilities and accomplishments are actually realized through computational methods, the limits of these abilities, why these limits exist, and how these machine-based computational methods that we refer to as Artificial Intelligence compare to human capabilities for understanding and intelligence.
For those of you who look for this type of material to read, it is also important to know about the recently published book, "Rebooting AI" by Gary Marcus and Ernest Davis. I have read both of these books cover-to-cover, carefully. My advice-- get both of these books and read both of them. They do have overlapping concerns, and do cover some of the same types of concepts. But they go about it in very different ways. Both books are technically accurate, and have a lot of great examples. Both books will give you much deeper insight into the capabilities and limitations of state-of-the-art AI (both now, and in the foreseeable future). But they go about it in different ways, and with different styles. So I will refrain from prioritizing one book over the other, as each has its own approach, emphasis, and style. If you enjoy this type of topic, and want to learn more from people who write well, AND who have very deep understanding of these topics--- then go get both of these books, absorb them, understand them, and go on a campaign to make sure all of your friends and professional colleagues understand the key messages of both of these books.
- Reviewed in the United States on August 1, 2020René Descartes, a French philosopher, mathematician and scientist in elucidating his famous theory of dualism, expounded that there exist two kinds of foundation: mental and physical. While the mental can exist outside of the body, and the body cannot think. Popularly known as mind-body dualism or Cartesian Duality (after the theory’s proponent), the central tenet of this philosophy is that the immaterial mind and the material body, while being ontologically distinct substances, causally interact. British philosopher Gilbert Ryle‘s in describing René Descartes’ mind-body dualism, introduced the now immortal phrase, “ghost in the machine” to highlight the view of Descartes and others that mental and physical activity occur simultaneously but separately.
Ray Kurzweil, the high priest of futurism and Director of Engineering at Google, takes Cartesian Duality to a higher plane with his public advocacy of concepts such as Technological Singularity and radical life extension. Kurzweil argues that with giant leaps in the domain of Artificial Intelligence, mankind will experience a radical life extension by 2045. Skeptics on the other hand bristle at this very notion, claiming such “Kurzweilian” aspirations to be mere fantasies putting to shame even the most ludicrous of pipe dreams.
The advances in the field of AI have spawned a seminal debate that has a vertical cleave. On one side of the chasm are the undying optimists such as Ray Kurzweil predicting a new epoch in the history of mankind, while on the other side of the divide are placed pessimists and naysayers such as Nick Bostrom, James Barrat and even the likes of Bill Gates, Elon Musk and Stephen Hawking who advocate extreme caution and warn about existential risks. So what is the actual fact? Melanie Mitchell, a computer science professor at Portland State University takes this conundrum head on in her eminently readable book, ““Artificial Intelligence: A Guide for Thinking Humans.” A measured book, that abhors mind numbing technicalities and arcane elaborations, Ms. Mitchell’s work embodies a matter-of-fact narrative that seeks to demystify the future of both AI and its users.
The book begins with a meeting organized by Blaise Agüera y Arcas, a computer scientist leading Google’s foray into machine intelligence. In the meeting, the genius AI pioneer and author of the Pulitzer Prize winning book, “Gödel, Escher, Bach: an Eternal Golden Braid” (or just “gee-ee-bee’), Douglas Hofstadter expresses downright alarm at the principle of Singularity being touted by Kurzweil. “If this actually happens, “we will be superseded. We will be relics. We will be left in the dust.” A former research assistant of Hofstadter, Ms. Mitchell is surprised to hear such an exclamation from her mentor. This spurs her on to assess the impact of AI, in an unbiased vein.
Tracing the modest trajectory of the beginning of AI, Ms. Mitchell informs her reader about a small workshop in Dartmouth in 1956 where the seeds of AI were first sown. John McCarthy, universally acknowledged as the father of AI and the inventor of the term itself, persuaded Marvin Minsky, a fellow student at Princeton, Claude Shannon, the inventor of information theory and Nathaniel Rochester, a pioneering electrical engineer, to help him organize “a 2 month, 10-man study of artificial intelligence to be carried out during the summer of 1956.” What began as a muted endeavor has now morphed into a creature that is both revered and reviled, in equal measure. Ms. Mitchell lends a technical element to the book by dwelling on concepts such as symbolic and sub-symbolic AI. Ms. Mitchell, however lends a fascinating insight into the myriad ways in which various intrepid pioneers and computer experts attempted to distill the element of “learning” into a computer thereby bestowing it with immense scalability and computational skills.
For example, using a technique termed, back-propagation, errors are taken away at the output units and to “propagate” the blame for that error backward so as to assign proper blame to each of the weights in the network. This allows back-propagation to determine how much to change each weight in order to reduce the error. The beauty of Ms. Mitchell’s explanations lies in its simplicity. She breaks down seemingly esoteric concepts into small chunks of ‘learnable’ elements.
It is these kind of techniques that have enabled IBM’s Watson to defeat World Chess Champion Garry Kasparov, and trump over Jeopardy! Champions Ken Jennings and Brad Rutter. So with such stupendous advances, is the time where Artificial Intelligence surpasses human intelligence already upon us? Ms. Mitchell does not think so. Taking recourse to the views of Alan Turing’s “argument from consciousness,” Ms. Mitchell brings to our attention, Turing’s summary of the neurologist Geoffrey Jefferson’s quote:
“Not until a machine can write a sonnet or compose a concerto because of thoughts and emotions felt, and not by the chance fall of symbols, could we agree that machine equals brain—that is, not only write it but know that it had written it. No mechanism could feel (and not merely artificially signal, an easy contrivance) pleasure at its successes, grief when its valves fuse, be warmed by flattery, be made miserable by its mistakes, be charmed by sex, be angry or depressed when it cannot get what it wants.”
Ms. Mitchell also highlights – in a somewhat metaphysical manner – the inherent limitations of a computer to gainfully engage in the attributes of abstraction and analogy. In the words of her own mentor Hofstadter and his coauthor, the psychologist Emmanuel Sander, “Without concepts there can be no thought, and without analogies there can be no concepts.” If computers are bereft of common sense, it is not for the want of their users trying to ‘embed’ some into them. A famous case in point being Douglas Lenat’s Cyc project which ultimately turned out to be a bold, albeit futile exercise.
A computer’s inherent limitation in thinking like a human being was also demonstrated by The Winograd schemas. These were schemas designed precisely to be easy for humans but tricky for computers. Hector Levesque, Ernest Davis, and Leora Morgenstern three AI researchers, “proposed using a large set of Winograd schemas as an alternative to the Turing test. The authors argued that, unlike the Turing test, a test that consists of Winograd schemas forestalls the possibility of a machine giving the correct answer without actually understanding anything about the sentence. The three researchers hypothesized (in notably cautious language) that “with a very high probability, anything that answers correctly is engaging in behaviour that we would say shows thinking in people.”
Finally, Ms. Mitchell concludes by declaring that machines are as yet incapable of generalizing, understanding cause and effect, or transferring knowledge from situation to situation – skills human beings begin to develop in infancy. Thus while computers won’t dethrone man anytime soon, goading them on to bring such an endeavor to fruition might not be a wise idea, after all.
- Reviewed in the United States on October 22, 2024"Don’t worry about AI being too smart and taking over the world -worry about it being too stupid and taking over the world!"
Best read of the year for me.
A wonderful, readable, concise review of AI progress during the past 75 years, and a clear exposition of why what we have accomplished, while exciting, falls far short of AGI.
I found Melanie’s overviews of methodologies very clear and helpful to the argument.
Perhaps the biggest takeaway for me is the issue of adversarial inputs tripping up AIs, which are revealed as exceedingly fragile - hence the quote in my heading.
Top reviews from other countries
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Un libro para reorganizar planes estrategicosReviewed in Mexico on December 29, 2024
5.0 out of 5 stars El camino que lleva la inteligencia artificial y como funciona
Este libro explica que el machine learning hace lo posible por imitar las sinapsis de las neuronas
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F.S. NobreReviewed in Brazil on November 3, 2024
5.0 out of 5 stars Excelente
Recomendo por ser de muita valia
- AshayReviewed in India on August 3, 2024
5.0 out of 5 stars Great for understanding AI, it’s foundations and future
Awesome read to clear questions such as the progress AI has made, it’s flaws, and it’s working! You get to learn about deep neural networks, NLP and most importantly the reasons why we are so far away from GenAI
- HeadphoneReviewer121Reviewed in the United Kingdom on June 14, 2024
5.0 out of 5 stars Brilliant intro to AI, very useful to have some analytical background
I wanted to get up to speed on AI from a user and management / governance perspective and to understand the opportunities and pitfalls involved - this book was excellent to provide me with enough technical detail to get my teeth into, but not too much that I felt my mind was boggled.
It's more about concepts than the coding and maths behind AI and keeps the major technical detail in the notes at the back which have enough for give you a steer on what is happening behind the scenes.
I think it will be accessible to most readers with some background knowledge of mathematics and computing, but no need to be an expert.
- genericblokeReviewed in Germany on March 14, 2024
5.0 out of 5 stars A great pleb friendly book on AI from a domain expert.
If you want to understand the how and why of AI without too much in the way of historical diversion then this is a good book to get your foot in the door. Especially, if like me, you are interested in AI as a new species, and not petrified of change. Change is most certainly coming, but not as soon as the hype would have you believe. However More's law wise were looking at 5-12 months per cycle and not slowing down.
Whether this will get to AGI is doubtful but it starts here.