AI-AI bias: Large language models favor communications generated by large language models
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11620%2F25%3A10508489" target="_blank" >RIV/00216208:11620/25:10508489 - isvavai.cz</a>
Result on the web
<a href="https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=..Xy-q6SzJ" target="_blank" >https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=..Xy-q6SzJ</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1073/pnas.2415697122" target="_blank" >10.1073/pnas.2415697122</a>
Alternative languages
Result language
angličtina
Original language name
AI-AI bias: Large language models favor communications generated by large language models
Original language description
Are large language models (LLMs) biased in favor of communications produced by LLMs, leading to possible antihuman discrimination? Using a classical experimental design inspired by employment discrimination studies, we tested widely used LLMs, including GPT-3.5, GPT-4 and a selection of recent open-weight models in binary choice scenarios. These involved LLM-based assistants selecting between goods (the goods we study include consumer products, academic papers, and film-viewings) described either by humans or LLMs. Our results show a consistent tendency for LLM-based AIs to prefer LLM-presented options. This suggests the possibility of future AI systems implicitly discriminating against humans as a class, giving AI agents and AI-assisted humans an unfair advantage.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10700 - Other natural sciences
Result continuities
Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Proceedings of the National Academy of Sciences of the United States of America
ISSN
0027-8424
e-ISSN
1091-6490
Volume of the periodical
122
Issue of the periodical within the volume
31
Country of publishing house
US - UNITED STATES
Number of pages
8
Pages from-to
e2415697122
UT code for WoS article
001547028700001
EID of the result in the Scopus database
2-s2.0-105012649316