AI-AI bias: Large language models favor communications generated by large language models.

Journal: Proceedings of the National Academy of Sciences of the United States of America
Published Date:

Abstract

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.

Authors

  • Walter Laurito
    Information Process Engineering, Forschungszentrum Informatik, Karlsruhe 76131, Germany.
  • Benjamin Davis
    Biomedical Research Center, Carle Foundation Hospital, 61801, Urbana, IL, USA.
  • Peli Grietzer
    Arb Research, Prague 11636, Czech Republic.
  • Tomáš Gavenčiak
    Alignment of Complex Systems (ACS) Research Group, Center for Theoretical Studies, Charles University, Prague 110 00, Czech Republic.
  • Ada Böhm
    Alignment of Complex Systems (ACS) Research Group, Center for Theoretical Studies, Charles University, Prague 110 00, Czech Republic.
  • Jan Kulveit
    Alignment of Complex Systems (ACS) Research Group, Center for Theoretical Studies, Charles University, Prague 110 00, Czech Republic.