Communication Bias in Large Language Models: A Regulatory Perspective
Computers and Society2025-09-26v1Artificial IntelligenceComputation and LanguageDistributed, Parallel, and Cluster ComputingHuman-Computer InteractionMachine Learning
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.
@article{arxiv.2509.21075,
title = {Communication Bias in Large Language Models: A Regulatory Perspective},
author = {Adrian Kuenzler and Stefan Schmid},
journal= {arXiv preprint arXiv:2509.21075},
year = {2025}
}