Review

AI today is exhibiting astounding technology and having a profound impact, but much of the intellectual motivation that gave rise to the field has fallen by the wayside. There are two reasons to re-embrace the intellectual journey. One is that the progress of AI will be impeded otherwise. The other is that the journey is worthy in and of itself -- it is a quest to understand not only computers but ourselves. This extremely well-written book by a leading AI researcher is required reading for anyone interested in this journey. (Yoav Shoham, Professor Emeritus, Stanford University; Principal Scientist, Google)AI is currently dominated by work on machine learning from massive data sets and/or low-level sensory inputs. Levesque reminds us that such an account of intelligence neglects the most important distinguishing feature of human intelligence: our ability to learn about aspects of the world that lie far beyond our direct experience through just a brief exchange of natural language. (Henry Kautz, Robin & Tim Wentworth Director, Goergen Institute for Data Science, University of Rochester)As a leading AI researcher for several decades, Levesque provides a lucid and highly insightful account of the remaining research challenges facing AI, arguing persuasively that common sense reasoning remains an open problem and lies at the core of the versatility of human intelligence. (Bart Selman, Professor of Computer Science, Cornell University)

Read more

About the Author

Hector J. Levesque is Professor Emeritus in the Department of Computer Science at the University of Toronto. He is the author of C ommon Sense, the Turing Test, and the Quest for Real AI, coauthor (with Gerhard Lakemeyer) of The Logic of Knowledge Bases, and coeditor (with Ronald J. Brachman) of Knowledge Representation and Reasoning, all three published by the MIT Press.

Read more

What can artificial intelligence teach us about the mind? If AI's underlying concept is that thinking is a computational process, then how can computation illuminate thinking? It's a timely question. AI is all the rage, and the buzziest AI buzz surrounds adaptive machine learning: computer systems that learn intelligent behavior from massive amounts of data. This is what powers a driverless car, for example. In this book, Hector Levesque shifts the conversation to "good old fashioned artificial intelligence," which is based not on heaps of data but on understanding commonsense intelligence. This kind of artificial intelligence is equipped to handle situations that depart from previous patterns -- as we do in real life, when, for example, we encounter a washed-out bridge or when the barista informs us there's no more soy milk.

Levesque considers the role of language in learning. He argues that a computer program that passes the famous Turing Test could be a mindless zombie, and he proposes another way to test for intelligence -- the Winograd Schema Test, developed by Levesque and his colleagues. "If our goal is to understand intelligent behavior, we had better understand the difference between making it and faking it," he observes. He identifies a possible mechanism behind common sense and the capacity to call on background knowledge: the ability to represent objects of thought symbolically. As AI migrates more and more into everyday life, we should worry if systems without common sense are making decisions where common sense is needed.