ArticleRoyal Society open science2025
Stereotypical bias amplification and reversal in an experimental model of human interaction with generative artificial intelligence.
Article in Royal Society open science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed.
- Beyond linearity: reimagining AI as a participant in circular bioeconomies.Journal of biological engineering · 2026Article
- Advice-Taking for Objective Face Age Estimates Relative to Subjective Face Trustworthiness Estimates.Behavioral sciences (Basel, Switzerland) · 2025Article
- Stereotypical bias amplification and reversal in an experimental model of human interaction with generative artificial intelligence.Royal Society open science · 2025Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Stereotypical biases are readily acquired and expressed by generative artificial intelligence (AI), causing growing societal concern about these systems amplifying existing human bias. This concern rests on reasonable psychological assumptions, but stereotypical bias amplification during human-AI interaction relative to pre-existing baseline levels has not been demonstrated. Here, we use previous psychological work on gendered character traits to capture and control gender stereotypes expressed in character descriptions generated by Open AI's GPT3.5. In four experiments (
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Registered trials
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