Communication Bias in Large Language Models: A Regulatory Perspective
It addresses bias and fairness concerns in LLMs for regulators and society, but is incremental as it reviews existing issues and frameworks.
This paper reviews the risks of biased outputs in large language models and their societal impact, focusing on regulatory frameworks like the EU's AI Act and the Digital Services Act, and argues for stronger attention to competition and design governance to ensure fair, trustworthy AI.
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.