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Assessing political bias and value misalignment in generative artificial intelligence
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“Recent studies have explored whether LLMs replicate human heuristics (4, 42, 43) or reflect ideological biases learned during training (44–46), but most focus on output-level metrics such as accuracy or bias. Few examine how these outputs are produced.”
From The simulation of judgment in LLMs (2025) · cites this paper as [43]
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“Rather, consistent with recent work on value alignment and political bias in LLMs (e.g., refs. 41 and 43), it likely reflects correlations in the training data—for instance, the co-occurrence of extremist rhetoric and misinformation-rather than an explicit ideological stance.”
From The simulation of judgment in LLMs (2025) · cites this paper as [43]
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Cited by
The simulation of judgment in LLMs
Loru, E., Nudo, J., Di Marco, N., Santirocchi, A., Atzeni, R., Cinelli, M., Cestari, V., Rossi-Arnaud, C., & Quattrociocchi, W. (2025) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2518443122 · Cited by 57
González-Cantera, T., & Bonacchi, C. (2025) · International Journal of Heritage Studies · doi:10.1080/13527258.2025.2543736 · Cited by 4
Metadata
- Authors
- Motoki, F. Y. S., Pinho Neto, V., & Rangel, V.
- ORCID
- Motoki, Fabio Y.S.
- Venue
- Journal of Economic Behavior & Organization
- Publisher
- Elsevier BV
- Published
- 2025-06
- Volume
- 234
- Pages
- 106904
- ISSN
- 0167-2681
- Cited by
- 32
- References
- 16
- Language
- en
- Licence
- www.elsevier.com/tdm/userlicense/1.0/ (tdm)
- www.elsevier.com/legal/tdmrep-license (tdm)
- creativecommons.org/licenses/by-nc/4.0/ (vor)
- Funders
- Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
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