Large Language Models display an uncanny ability to construct human-sounding speech, and can synthesize concepts in novel ways. Is this because they are truly thinking like human beings in some way, or have they found a way to be human-like without reproducing the internal mechanisms of human thought? Chandra Sripada argues that LLM cognition is more human-like than we suppose, and offers evidence from the ways that cognitive scientists study actual humans.
Chandra Sripada received an M.D. from the University of Texas and a Ph.D. in philosophy from Rutgers University. He is currently a professor of philosophy and psychiatry at the University of Michigan, where he holds the Theophile Raphael Research Professorship and directs the Weinberg Institute for Cognitive Science. He writes Cognition, Decoded, a Substack newsletter about AI, cognitive science, and philosophy.
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