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.Turing wrote that the “guiding principle” of his investigation into the possibility of intelligent machinery was “The analogy with the human brain.” In his discussion of the investigations that Turing said were guided by this analogy, however, he employs a more far-reaching analogy: he eventually expands the analogy from the human brain out to “the human community as a whole.” Along the way, he takes note of an obvious fact in the bigger scheme of things regarding human intelligence: grownups were once children this leads him to imagine what a machine analogue of childhood might be. He identifies a possible mechanism behind common sense and the capacity to call on background knowledge: the ability to represent objects of thought symbolically. “If our goal is to understand intelligent behavior, we had better understand the difference between making it and faking it,” he observes. 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. Levesque considers the role of language in learning. 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. 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 is what powers a driverless car, for example. 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. 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. What artificial intelligence can tell us about the mind and intelligent behavior.
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