Artificial Intelligence: A Guide For Thinking Humans (Pelican Books)

Description

No recent scientific enterprise has been so alluring, terrifying, and filled with extravagant promise and frustrating setbacks as artificial intelligence. How intelligent are the best of today's AI programs? To what extent can we entrust them with decisions that affect our lives? How human-like do we expect them to become, and how soon do we need to worry about them surpassing us in most, if not all, human endeavours? From leading AI researcher and award-winning author Melanie Mitchell comes a knowledgeable and 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 requires such elusive human qualities in order to be reliable, trustworthy and beneficial. Artificial Intelligence- A Guide for Thinking Humans provides readers with an accessible, entertaining 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.

About the Author

Melanie Mitchell is a professor of computer science at Portland State University. She has worked at the Santa Fe Institute and Los Alamos National Laboratory. Her major work has been in the areas of analogical reasoning, complex systems, genetic algorithms and cellular automata, and her publications in those fields are frequently cited.She received her PhD in 1990 from the University of Michigan under Douglas Hofstadter and John Holland, for which she developed the Copycat cognitive architecture. She is the author of "Analogy-Making as Perception", essentially a book about Copycat. She has also critiqued Stephen Wolfram's A New Kind of Science and showed that genetic algorithms could find better solutions to the majority problem for one-dimensional cellular automata. She is the author of An Introduction to Genetic Algorithms, a widely known introductory book published by MIT Press in 1996. She is also author of Complexity: A Guided Tour (Oxford University Press, 2009), which won the 2010 Phi Beta Kappa Science Book Award.