How online studies must increase their defences against AI
LLM agents can now pass as human participants, threatening the validity of online social science. We urge a shift from ad-hoc checks to multi-layered, adaptive defenses, borrowing from internet anti-bot practice, and call for cooperation across researchers, platforms, and institutions, to guard against this challenge. LLM agents can now pass as human participants, threatening the validity of online social science. We urge a shift from ad-hoc checks to multi-layered, adaptive defenses, borrowing from internet anti-bot practice, and call for cooperation across researchers, platforms, and institutions, to guard against this challenge.
Authors
- Frank Papenmeier (ORCID: https://orcid.org/0000-0001-5566-9658)
- Markus Huff (ORCID: https://orcid.org/0000-0002-1433-4656)
- Gerrit Anders
- Jürgen Buder
Institutions
- Leibniz-Institut für Wissensmedien (DE)
- University of Tübingen (DE)
Publication Details
- Journal
- Communications Psychology
- Published
- 2026-01-07
- DOI
- https://doi.org/10.1038/s44271-025-00388-2
- Citations
- 1
- Primary Topic
- Computational and Text Analysis Methods
- Type
- article
- Field-Weighted Citation Impact
- 49.38