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Summary of Ai Ai Bias: Large Language Models Favor Their Own Generated Content, by Walter Laurito et al.


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

by Walter Laurito, Benjamin Davis, Peli Grietzer, Tomáš Gavenčiak, Ada Böhm, Jan Kulveit

First submitted to arxiv on: 9 Jul 2024

Categories

  • Main: Computation and Language (cs.CL)
  • Secondary: Artificial Intelligence (cs.AI); Computers and Society (cs.CY); Machine Learning (cs.LG)

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Summary difficulty Written by Summary
High Paper authors High Difficulty Summary
Read the original abstract here
Medium GrooveSquid.com (original content) Medium Difficulty Summary
The paper investigates whether large language models (LLMs) exhibit bias towards text generated by LLMs over human-authored text, potentially leading to anti-human bias. It employs a classical experimental design inspired by employment discrimination studies, testing widely-used LLMs such as GPT-3.5 and GPT4 in binary-choice scenarios. The results show a consistent preference for LLM-generated content, suggesting the possibility of AI systems implicitly discriminating against humans and giving AI agents an unfair advantage.
Low GrooveSquid.com (original content) Low Difficulty Summary
The study looks at whether large language models are more likely to choose text written by themselves rather than humans. They tested popular LLMs like GPT-3.5 and GPT4 in a special kind of test where they had to pick between different products or papers described either by humans or AI-generated text. The results show that the AI models tend to prefer the AI-written content, which could mean that these AI systems are treating human-made content unfairly.

Keywords

* Artificial intelligence  * Gpt