AI Surrogates and illusions of generalizability in cognitive science

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Dans cet article, les autrices discutent de l’idée que les « AI surrogates » pourraient aider à résoudre certains problèmes fréquents en sciences cognitives, comme la généralisation des résultats et le manque de diversité des échantillons. Elles soulignent toutefois les risques d’une confiance excessive envers ces outils, qui peut donner une illusion de généralité et limiter la portée réelle des connaissances produites. 

Résumé : 

Recent advances in artificial intelligence (AI) have generated enthusiasm for using AI simulations of human research participants to generate new knowledge about human cognition and behavior. This vision of ‘AI Surrogates’ promises to enhance research in cognitive science by addressing longstanding challenges to the generalizability of human subjects research. AI Surrogates are envisioned as expanding the diversity of populations and contexts that we can feasibly study with the tools of cognitive science. Here, we caution that investing in AI Surrogates risks entrenching research practices that narrow the scope of cognitive science research, perpetuating ‘illusions of generalizability’ where we believe our findings are more generalizable than they actually are. Taking the vision of AI Surrogates seriously helps illuminate a path toward a more inclusive cognitive science.