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How online studies must increase their defences against AI

Year: 2026

Type: article

Abstract: 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.

Source: Communications Psychology

DOI: 10.1038/s44271-025-00388-2

Authors: Gerrit Anders, Jürgen Buder, Frank Papenmeier, Markus Huff

Institutions: Leibniz-Institut für Wissensmedien, University of Tübingen

Language: English

Topic: Survey Methodology and Nonresponse

Subfield: Sociology and Political Science

Field: Social Sciences

Domain: Social Sciences

Open Access status: gold

Estimated APC paid: $2,090

OpenAlex ID: W7119095753