Computers today can be very opaque. When they make a mistake, it's hard to understand why, and it's hard to fix the problem. Computers should instead be transparent. They should be able to reason like people and explain their reasoning to people. This book discusses techniques for designing and building transparent computers ranging from declarative methods to neural networks. It describes ways of implementing dialogue, explanation, and learning in transparent computers.
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Erik Mueller is a Senior Director at Capital One, where he leads teams that develop AI capabilities for intelligent assistants. As a member of the original Watson Team at IBM for five years, he helped develop the Watson Jeopardy! system, Watson for Healthcare, and WatsonPaths. He is the author of several books, including Commonsense Reasoning and Daydreaming in Humans and Machines. He holds a Ph.D. and M.S. in computer science from UCLA and an S.B. in computer science and engineering from MIT.
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