分析大模型通信偏见，提出监管与设计并重的治理新思路
Communication Bias in Large Language Models: A Regulatory Perspective
- 从欧盟AI法案等框架出发，系统梳理大模型偏见风险
- 指出仅靠法规监管不足，需加强竞争与设计治理
- 适合关注AI伦理、政策制定及模型安全的研究者
大型语言模型（LLMs）在众多应用中日益关键，引发对偏见、公平性及合规性的担忧。本文回顾了偏见输出的风险及其社会影响，重点分析欧盟《人工智能法案》和《数字服务法案》等监管框架。研究认为，除持续监管外，还需加强对市场竞争和设计治理的关注，以确保人工智能的公平与可信。本论文为《通讯的ACM》同名文章的预印本。
原文摘要 · Abstract (English)
Large language models (LLMs) are increasingly central to many applications, raising concerns about bias, fairness, and regulatory compliance. This paper reviews risks of biased outputs and their societal impact, focusing on frameworks like the EU's AI Act and the Digital Services Act. We argue that beyond constant regulation, stronger attention to competition and design governance is needed to ensure fair, trustworthy AI. This is a preprint of the Communications of the ACM article of the same title.
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