Gary Marcus and coauthors argue human imitation is a misplaced goal for AI
ValerioCapraro · x · 2026-10-30
A new paper by Valerio Capraro, Gary Marcus, and Walter Quattrociochi argues that human imitation is a misplaced goal for AI development.
- Conceptual problem: imitating human outputs says little about underlying capacities—identical answers can arise from different processes, and plausible responses don't prove reliable reasoning, generalization, or knowing when to say "I don't know." The Turing test embodies this confusion.
- Ethical problem: humans are biased, inattentive, and fallible; replicating these flaws is unambitious, impersonation can exploit human trust, and the field risks a "Turing's trap" of favoring replacement over augmentation.
The authors propose three changes: developers should build systems that strengthen human capabilities and independent judgment; funders should require assessment of benefits, costs, and their distribution; institutions should base procurement on demonstrated welfare effects. Paper from University of Milano-Bicocca, NYU, and Sapienza University of Rome.
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