IGOR GROSSMANN , MATTHEW FEINBERG, DAWN C. PARKER, NICHOLAS A. CHRISTAKIS, PHILIP E. TETLOCK, AND WILLIAM A. CUNNINGHAM

SCIENCE 15 Jun 2023 Vol 380, Issue 6650

Advances in artificial intelligence (AI), particularly large language models (LLMs), are substantially affecting social science research. These transformer-based machine-learning models pretrained on vast amounts of text data are increasingly capable of simulating human-like responses and behaviors (1, 2), offering opportunities to test theories and hypotheses about human behavior at great scale and speed. This presents urgent challenges: How can social science research practices be adapted, even reinvented, to harness the power of foundational AI? And how can this be done while ensuring transparent and replicable research?

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