Position: Generative AI Regulation Can Learn from Social Media Regulation

Ruth Elisabeth Appel

Keywords: generative AI, social media, regulation

TL;DR: This paper argues that generative AI regulation can be informed by social media regulation.

Abstract: There is strong agreement that generative AI should be regulated, but strong disagreement on how to approach regulation. In this position paper, we argue that the debates on generative AI regulation can be informed by evidence on social media regulation. For example, AI companies have faced allegations of political bias similar to the allegations social media companies have faced. We discuss four specific policy recommendations based on the evolution of social media and their regulation: (1) counter bias and perceptions thereof (e.g., via transparency, oversight boards, researcher access, democratic input), (2) address specific regulatory concerns (e.g., youth wellbeing, election integrity) and invest in trust and safety, (3) promote computational social science research, and (4) take on a more global perspective. Applying lessons learnt from social media regulation to generative AI regulation can save effort and time, and prevent avoidable mistakes.

Submission Number: 46