The Political Biases of ChatGPT

David Rozado ()
Additional contact information
David Rozado: Te Pūkenga—New Zealand Institute of Skills and Technology, Hamilton 3244, New Zealand

Social Sciences, 2023, vol. 12, issue 3, 1-8

Abstract: Recent advancements in Large Language Models (LLMs) suggest imminent commercial applications of such AI systems where they will serve as gateways to interact with technology and the accumulated body of human knowledge. The possibility of political biases embedded in these models raises concerns about their potential misusage. In this work, we report the results of administering 15 different political orientation tests (14 in English, 1 in Spanish) to a state-of-the-art Large Language Model, the popular ChatGPT from OpenAI. The results are consistent across tests; 14 of the 15 instruments diagnose ChatGPT answers to their questions as manifesting a preference for left-leaning viewpoints. When asked explicitly about its political preferences, ChatGPT often claims to hold no political opinions and to just strive to provide factual and neutral information. It is desirable that public facing artificial intelligence systems provide accurate and factual information about empirically verifiable issues, but such systems should strive for political neutrality on largely normative questions for which there is no straightforward way to empirically validate a viewpoint. Thus, ethical AI systems should present users with balanced arguments on the issue at hand and avoid claiming neutrality while displaying clear signs of political bias in their content.

Keywords: algorithmic bias; political bias; AI; large language models; LLMs; ChatGPT; OpenAI (search for similar items in EconPapers)
JEL-codes: A B N P Y80 Z00 (search for similar items in EconPapers)
Date: 2023
References: View complete reference list from CitEc
Citations: View citations in EconPapers (5)

Downloads: (external link)
https://www.mdpi.com/2076-0760/12/3/148/pdf (application/pdf)
https://www.mdpi.com/2076-0760/12/3/148/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jscscx:v:12:y:2023:i:3:p:148-:d:1086070

Access Statistics for this article

Social Sciences is currently edited by Ms. Yvonne Chu

More articles in Social Sciences from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().