cs.AIMar 22, 2026
SaveToward an automated science of the mind
Organizations: Princeton AI Lab, Princeton University, New Jersey, USA · Institute for Human-Centered AI, Helmholtz Munich, Neuherberg, Germany · Ludwig-Maximilians-University, Munich, 80539, Germany
Abstract
Artificial Intelligence is starting to automate scientific discovery, raising the prospect of an automated science of the mind. We chart this field around four challenges: representing experiments, generating synthetic behavior, synthesizing models, and closing the loop to discover psychological theories.
Figures & tables
Figure 1: An automated cycle of scientific discovery in the cognitive sciences. An experimentalist proposes experiments; a cognitive foundation model simulates behavioral data; a modeller synthesizes and tests computational models; and a critic judges the “interestingness” of the results and passes that signal back to the experimentalist for further optimization. Crucially, discoveries that survive in-silico screening are compiled into targeted human experiments—behavioral and, where relevant, verbal reports, eye-tracking, neural responses, and other physiological measurements—whose outcomes both adjudicate candidate discoveries and help recalibrate the behavioral generator, keeping the loop anchored to empirical data. Solid line indicate primary components of the cycle. Dotted line indicate auxiliary components of the cycle
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