Artificial Intelligence: A Guide for Thinking Humans by Melanie Mitchell - Book Review


In this sweeping review of AI's current state and how it remakes our planet, Melanie Mitchell distinguishes real science from science fiction.

No recent scientific company, including artificial intelligence, has proved to be sexy, frightening, and filled with extravagant progress and disappointing setbacks. The award-winning author, Melanie Mitchell, a leading computer scientist, reveals the tumultuous past of AI and the rising number of clear milestones, great expectations, and emerging concerns around it.

Mitchell turns to the most urgent questions about AI today in Artificial Intelligence: How intelligent are the best AI systems? How are they functioning? What will they do, and when are they going to fail? How do we expect them to become, and how easily do we need to fear that they will surpass us? She presents the dominant models of modern AI and the machine learning along the way, outlining cutting-edge AI systems, Their inventors, and the historical lines of reasoning behind recent accomplishments. She encounters fellow experts such as Douglas Hofstadter, Escher, Bach, the cognitive scientist and author of the real classic Gödel, recipient of the Pulitzer Prize, who explains why he is "terrified" about AI's future. She discusses the profound disconnect between the hype and AI's real accomplishments, offering a strong sense of what the industry has achieved and how much further it has to go.

Artificial intelligence brims with the most exciting and provocative recent work in the field, with clear-sighted, captivating, and open accounts, flavored with Mitchell's humor and personal insights, interconnecting stories about The science of AI and the individuals behind it. An essential guide to understanding today's AI, its search for "human-level intelligence, and its effect on the future for all of us is this frank, lively novel.


Melanie Mitchell is a computer science professor at the State University of Portland. She worked at the Institute of Santa Fe and the National Laboratory of Los Alamos. Her primary work has concentrated on analogical reasoning, complex systems, genetic algorithms, and cellular automata, and in these fields, her publications are often cited.

In 1990, under Douglas Hofstadter and John Holland, she earned her Ph.D. from the University of Michigan, for which she created the Copycat cognitive architecture. She is the author of Analogy-Making as Interpretation, a book about Copycat in essence. She also criticized A New Kind of Science by Stephen Wolfram and showed that genetic algorithms for one-dimensional cellular automata could find better alternatives to the majority of problems. She is the author of An Introduction to Genetic Algorithms, an introductory book published in 1996 by MIT Press, which is well known. She is also the 2010 Phi Beta Kappa Science Book Award for Complexity: A Guided Tour (Oxford University Press, 2009) and Artificial Intelligence: A Guide to Human Thought (Farrar, Straus, and Giroux).

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