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Artificial Intelligence

A Guide for Thinking Humans

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Artificial Intelligence

By: Melanie Mitchell
Narrated by: Abby Craden, Melanie Mitchell, Tony Wolf
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About this listen

This program includes an introduction read by the author.

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 its turbulent history and the recent surge of apparent successes, grand hopes, and emerging fears that surround AI.

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. She meets with fellow experts like 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 farther it has to go.

Interweaving stories about the science and the people behind it, Artificial Intelligence brims with clear-sighted, captivating, and approachable accounts of the most interesting and provocative modern work in AI, flavored with Mitchell’s humor and personal observations. This frank, lively book will prove an indispensable guide to understanding today’s AI, its quest for “human-level” intelligence, and its impacts on all of our futures.

PLEASE NOTE: When you purchase this title, the accompanying PDF will be available in your Audible Library along with the audio.

©2019 Melanie Mitchell (P)2019 Macmillan Audio
Computer Science Future Studies History & Culture Machine Theory & Artificial Intelligence Social Sciences Technology & Society Technology Data Science Artificial Intelligence Machine Learning Witty Programming
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This book relates many historical accounts on the development of artificial intelligence powered applications, starting with video games. It also details many current flaws such as coding intuition and common sense. Great book!

Excellent book on AI

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Thorough yet easy to follow review of AI technology. Unfortunately, this scientific content was polluted, in parts, by unnecessary and untrue identity politics. Overall, a good book.

Good content polluted by identity politics

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Great intro to AI and its current limitations. These limitations include misidentifying people based on race. It is discussed at length in the audiobook that this mistake is an artefact of the AI training data, which often reflects the biases in society. It is not some “identity politics” rant. You would have to be wilfully ignorant to interpret the text otherwise.

The reviewer who cites “identity politics” is a goose

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This book covers a very wide set of topics within AI, with some of the best examples and explanations of how machine learning and AI work that I have ever heard. The author explains the challenges and issues faced in AI and does so without sounding superior or dismissive.

This is truely the best overview of the current state of AI for people with an interest in the field that I have read.

I highly recommend it if you have some background in AI/ML or if you want more than a newspaper article depth on the topic.

Brilliant.

Brilliant book that goes to just the right depth

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This is an excellent introduction to how AI developed from early rule-based systems to the data-driven learning systems used today.

Mitchell explains why the rule-based approach struggled, and why neural-network methods — inspired by how humans perceive patterns — came to dominate.

The book predates the current LLM wave, but her discussion of progress in language processing, and her warnings about confusing linguistic skill with genuine understanding, feel directly relevant to today’s AI systems.

I highly recommend it to any novice with an interest in the subject.

Every AI novice needs this book!

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