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Assessing political bias and value misalignment in generative artificial intelligence

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  • Motoki, Fabio Y.S.
  • Pinho Neto, Valdemar
  • Rangel, Victor

Abstract

Our analysis reveals a concerning misalignment of values between ChatGPT and the average American. We also show that ChatGPT displays political leanings when generating text and images, but the degree and direction of skew depend on the theme. Notably, ChatGPT repeatedly refused to generate content representing certain mainstream perspectives, citing concerns over misinformation and bias. As generative AI systems like ChatGPT become ubiquitous, such misalignment with societal norms poses risks of distorting public discourse. Without proper safeguards, these systems threaten to exacerbate societal divides and depart from principles that underpin free societies.

Suggested Citation

  • Motoki, Fabio Y.S. & Pinho Neto, Valdemar & Rangel, Victor, 2025. "Assessing political bias and value misalignment in generative artificial intelligence," Journal of Economic Behavior & Organization, Elsevier, vol. 234(C).
    • Handle: RePEc:eee:jeborg:v:234:y:2025:i:c:s0167268125000241
    DOI: 10.1016/j.jebo.2025.106904
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    1. Kevin Aslett & Zeve Sanderson & William Godel & Nathaniel Persily & Jonathan Nagler & Joshua A. Tucker, 2024. "Online searches to evaluate misinformation can increase its perceived veracity," Nature, Nature, vol. 625(7995), pages 548-556, January.
    2. Klockmann, Victor & von Schenk, Alicia & Villeval, Marie Claire, 2022. "Artificial intelligence, ethics, and intergenerational responsibility," Journal of Economic Behavior & Organization, Elsevier, vol. 203(C), pages 284-317.
    3. Desmond Ang, 2023. "The Birth of a Nation: Media and Racial Hate," American Economic Review, American Economic Association, vol. 113(6), pages 1424-1460, June.
    4. Anton Korinek, 2023. "Generative AI for Economic Research: Use Cases and Implications for Economists," Journal of Economic Literature, American Economic Association, vol. 61(4), pages 1281-1317, December.
    5. Milena Djourelova, 2023. "Persuasion through Slanted Language: Evidence from the Media Coverage of Immigration," American Economic Review, American Economic Association, vol. 113(3), pages 800-835, March.
    6. Matthew Gentzkow & Edward L. Glaeser & Claudia Goldin, 2006. "The Rise of the Fourth Estate. How Newspapers Became Informative and Why It Mattered," NBER Chapters, in: Corruption and Reform: Lessons from America's Economic History, pages 187-230, National Bureau of Economic Research, Inc.
    7. Ryan C. Moore & Ross Dahlke & Jeffrey T. Hancock, 2023. "Exposure to untrustworthy websites in the 2020 US election," Nature Human Behaviour, Nature, vol. 7(7), pages 1096-1105, July.
    8. Lambert, Karras J. & Fegley, Tate, 2023. "Economic Calculation in Light of Advances in Big Data and Artificial Intelligence," Journal of Economic Behavior & Organization, Elsevier, vol. 206(C), pages 243-250.
    9. Lisa Messeri & M. J. Crockett, 2024. "Artificial intelligence and illusions of understanding in scientific research," Nature, Nature, vol. 627(8002), pages 49-58, March.
    10. Valerio Capraro & Roberto Di Paolo & Matjaz Perc & Veronica Pizziol, 2024. "Language-based game theory in the age of artificial intelligence," Papers 2403.08944, arXiv.org.
    11. Douglas Guilbeault & Solène Delecourt & Tasker Hull & Bhargav Srinivasa Desikan & Mark Chu & Ethan Nadler, 2024. "Online images amplify gender bias," Nature, Nature, vol. 626(8001), pages 1049-1055, February.
    12. Czarnitzki, Dirk & Fernández, Gastón P. & Rammer, Christian, 2023. "Artificial intelligence and firm-level productivity," Journal of Economic Behavior & Organization, Elsevier, vol. 211(C), pages 188-205.
    13. Jeffrey, Karen, 2021. "Automation and the future of work: How rhetoric shapes the response in policy preferences," Journal of Economic Behavior & Organization, Elsevier, vol. 192(C), pages 417-433.
    14. Daron Acemoglu & Todd Lensman, 2024. "Regulating Transformative Technologies," American Economic Review: Insights, American Economic Association, vol. 6(3), pages 359-376, September.
    15. Arthur, W. Brian, 2023. "Economics in nouns and verbs," Journal of Economic Behavior & Organization, Elsevier, vol. 205(C), pages 638-647.
    16. Fabio Motoki & Valdemar Pinho Neto & Victor Rodrigues, 2024. "More human than human: measuring ChatGPT political bias," Public Choice, Springer, vol. 198(1), pages 3-23, January.
    17. Margarita Leib & Nils Köbis & Rainer Michael Rilke & Marloes Hagens & Bernd Irlenbusch, 2024. "Corrupted by Algorithms? How AI-generated and Human-written Advice Shape (Dis)honesty," The Economic Journal, Royal Economic Society, vol. 134(658), pages 766-784.
    18. Eva A. M. van Dis & Johan Bollen & Willem Zuidema & Robert van Rooij & Claudi L. Bockting, 2023. "ChatGPT: five priorities for research," Nature, Nature, vol. 614(7947), pages 224-226, February.
    19. Taylor Webb & Keith J. Holyoak & Hongjing Lu, 2023. "Emergent analogical reasoning in large language models," Nature Human Behaviour, Nature, vol. 7(9), pages 1526-1541, September.
    20. Elena Esposito & Tiziano Rotesi & Alessandro Saia & Mathias Thoenig, 2023. "Reconciliation Narratives: The Birth of a Nation after the US Civil War," American Economic Review, American Economic Association, vol. 113(6), pages 1461-1504, June.
    21. Ashesh Rambachan & Jon Kleinberg & Jens Ludwig & Sendhil Mullainathan, 2020. "An Economic Perspective on Algorithmic Fairness," AEA Papers and Proceedings, American Economic Association, vol. 110, pages 91-95, May.
    22. Damian J. Ruck & Luke J. Matthews & Thanos Kyritsis & Quentin D. Atkinson & R. Alexander Bentley, 2020. "The cultural foundations of modern democracies," Nature Human Behaviour, Nature, vol. 4(3), pages 265-269, March.
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    Cited by:

    1. Filippo Gusella & Eugenio Vicario, 2025. "Generative Agents and Expectations: Do LLMs Align with Heterogeneous Agent Models?," Working Papers - Economics wp2025_18.rdf, Universita' degli Studi di Firenze, Dipartimento di Scienze per l'Economia e l'Impresa.
    2. Eduardo Levy Yeyati & César M. Ciappa & Milagros Onofri, 2026. "Same Model, Different Politics? How Language Shapes AI Ideology," School of Government Working Papers wp_gob_2026_07, Universidad Torcuato Di Tella.
    3. Filippo Gusella & Eugenio Vicario, 2025. "Generative Agents and Expectations: Do LLMs Align with Heterogeneous Agent Models?," Papers 2511.08604, arXiv.org.
    4. Leonardo Becchetti & Nazaria Solferino, 2026. "Political biases in chatgpt: insights from comparative analysis with human responses," Economia Politica: Journal of Analytical and Institutional Economics, Springer;Fondazione Edison, vol. 43(1), pages 285-326, April.

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    JEL classification:

    • C89 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Other
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • L86 - Industrial Organization - - Industry Studies: Services - - - Information and Internet Services; Computer Software
    • Z00 - Other Special Topics - - General - - - General

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