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Poster E in Poster Session E: Thursday, August 6, 10:30 am – 12:15 pm, Kimmel Center, Shorin & Rosenthal Rooms

Minds as machines: Evaluating utility and plausibility

Nelu D. Radpour¹, Michael P. Kaschak²; ¹State University of New York at Buffalo, ²Florida State University

Presenter: Nelu D. Radpour

The metaphor of the mind as a machine has guided cognitive science, artificial intelligence, and computational neuroscience for decades. Critics argue that it is reductionist and fails to capture subjective experience (Brette, 2019; Chemero, 2013; Dreyfus, 1992; Hoel, 2021; Searle, 1980), while practitioners rely on it to construct predictive and testable models. This paper introduces a two-dimensional framework for evaluating computational models along the axes of instrumental usefulness and theoretical plausibility. The application of this framework is demonstrated through case studies of backpropagation and human memory to show that models can be highly effective despite limited biological realism, and conversely how phenomenological richness can resist formalization.

Topic Area: Methods, Tools, Theory & Neural Coding