AI AI Bias: Large Language Models Favor Their Own Generated Content

Autor:	Laurito, Walter, Davis, Benjamin, Grietzer, Peli, Gavenčiak, Tomáš, Böhm, Ada, Kulveit, Jan
Rok vydání:	2024
Předmět:	Computer Science - Computation and Language Computer Science - Artificial Intelligence Computer Science - Computers and Society Computer Science - Machine Learning
Druh dokumentu:	Working Paper
Popis:	Are large language models (LLMs) biased towards text generated by LLMs over text authored by humans, leading to possible anti-human bias? Utilizing a classical experimental design inspired by employment discrimination studies, we tested widely-used LLMs, including GPT-3.5 and GPT4, in binary-choice scenarios. These involved LLM-based agents selecting between products and academic papers described either by humans or LLMs under identical conditions. Our results show a consistent tendency for LLM-based AIs to prefer LLM-generated content. This suggests the possibility of AI systems implicitly discriminating against humans, giving AI agents an unfair advantage. Comment: 8 pages, 1 figure
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2407.12856 Zobrazit plný text záznamu View this record from Arxiv