Nature, Published online: 08 July 2026; doi:10.1038/d41586-026-01875-0 Large language models could advance experiments in the social sciences, but fundamental questions remain about how they should be used to support research.
The rapid advancement and accessibility of large language models are prompting researchers to explore their utility beyond traditional applications, accelerating their integration into diverse fields like the social sciences.
This indicates a growing acceptance and application of AI tools in research methodologies, potentially democratizing and speeding up scientific discovery in areas previously limited by data collection and analysis bandwidth.
The methodology for conducting social science research could fundamentally shift, moving towards more AI-assisted experimental design and data interpretation, challenging established paradigms of human-led inquiry.
- · Social science researchers
- · AI model developers
- · Academic publishers
- · Governments seeking policy insights
- · Researchers resistant to AI tools
- · Traditional qualitative research methodologies
LLMs become standard tools in social science methodologies for hypothesis generation and data analysis.
Faster iteration and discovery of social phenomena lead to more evidence-based policy making and product development.
The definition of 'human expertise' in social science evolves as AI tools increasingly contribute to knowledge creation, potentially leading to new ethical frameworks for co-authorship with AI.
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