Can AI language models replace human participants?

By Danica Dillion, Niket Tandon, Yuling Gu, Kurt Gray. Trends in Cognitive Sciences, 2023

485 citations recorded by the source corpus.

Recent work suggests that language models such as GPT can make human-like judgments across a number of domains. We explore whether and when language models might replace human participants in psychological science. We review nascent research, provide a theoretical model, and outline caveats of using AI as a participant.

Subfields: Artificial Intelligence, Cognitive Neuroscience, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/2ff8ff6e79652ec4eda5c6892e03f307d2b29175

Citations in the corpus

• Artificial intelligence and illusions of understanding in scientific research (2024, unknown): “In the social sciences, Surrogates are positioned as ideal research participants that “can rapidly answer hundreds of questions without fatigue” and “need fewer incentives than humans to give reliable responses” 3 .”
• Multi-Agent Collaboration Mechanisms: A Survey of LLMs (2025, unknown): “Authors in [5, 36] suggest that LLM-based agents can replace human participants in specific social science experiments, while [88] demonstrates their use in generating diverse natural language data with iterative cross-agent refinement.”