Artificial Intelligence
A Guide for Thinking Humans
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- USD 10.99
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- USD 10.99
Descripción editorial
'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 been so alluring, terrifying and filled with extravagant promise and frustrating setbacks as artificial intelligence. Writing with clarity and passion, leading AI researcher Melanie Mitchell offers a captivating account of modern-day artificial intelligence.
Flavoured with personal stories and a twist of humour, Artificial Intelligence illuminates the workings of machines that mimic human learning, perception, language, creativity and common sense. Weaving together advances in AI with cognitive science and philosophy, Mitchell probes the extent to which today's 'smart' machines can actually think or understand, and whether AI even requires such elusive human qualities at all.
Artificial Intelligence: A Guide for Thinking Humans provides readers with an accessible and clear-eyed view of the AI landscape, what the field has actually accomplished, how much further it has to go and what it means for all of our futures.
PUBLISHERS WEEKLY
Mitchell (Complexity: A Guided Tour), a Portland State computer science professor, ably illustrates the current state of artificial intelligence, debunking claims about computers that match or surpass human intelligence. She begins with a meeting that she attended with Google's AI team alongside her former PhD advisor, Douglas Hofstadter, author of G del, Escher, Bach, who revealed he was "terrified" that a "superficial set of brute-force algorithms could explain the human spirit." Mitchell then examines various areas of AI research, including image recognition, question answering, game playing, and translation. Each example yields similar results; namely, that computers can be trained to master specific tasks as with the vaunted Jeopardy! win for IBM's Watson program but not to learn new abilities in general or truly understand meaning. Responding to claims by AI developers, Mitchell suggests that machines can never "fully understand human language until they have human-like common sense." Moreover, AI programs remain susceptible to errors and hacking, in part because they are surprisingly easily fooled. Taking care to keep the text accessible, Mitchell lightens things with amusing facts, such as how Star Trek's ship computer remains the gold standard for many AI researchers. This worthy volume should assuage lay readers' fears about AI, while also reassuring people drawn to the field that much work remains to be done.
