Valiant (computer science and applied mathematics, Harvard Univ.;
Probably Approximately Correct) proposes that instead of recognizing, measuring, and comparing artificial intelligence to people, one must first consider what makes us human. He uses the theoretical model of educability—the ability to learn and apply those lessons in various experiences—to discuss timely issues such as machine learning, human evolution, technology, and educational systems. Furthermore, generalization, symbolic naming, teaching, chaining, and utilizing the mind’s eye are detailed as a few of the qualities that comprise educability. The book’s short chapters describe the background, approaches, and relevance of the educability model as it pertains to the progression of human achievement. Valiant includes perspectives of other educators, psychologists, and scientists as well. He also compares his model to other well-known experiments, such as the Turing machine mathematical model, Pavlov’s theory of behaviorism, and the Nixon diamond reasoning scenario.
VERDICT This brief, philosophical treatise will be a thoughtful addition to academic collections focused on artificial intelligence and human learning.
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