Generative AI regulation can learn from social media regulation

TL;DR

The paper addresses how to regulate generative AI by leveraging lessons from social media regulation. It analyzes affordances to identify where AI and social platforms are similar enough to inform policy while acknowledging key differences. It then proposes four concrete policy levers: counter bias and perceptions through transparency, researcher access, and democratic input; invest in trust and safety to address youth wellbeing and election integrity; advance computational social science to rigorously evaluate interventions; and adopt a global perspective with local expertise. Together these contributions aim to save regulatory effort, prevent avoidable mistakes, and align AI development with societal values through global coordination.

Abstract

There is strong agreement that generative AI should be regulated, but strong disagreement on how to approach regulation. While some argue that AI regulation should mostly rely on extensions of existing laws, others argue that entirely new laws and regulations are needed to ensure that generative AI benefits society. In this paper, I argue that the debates on generative AI regulation can be informed by the debates and evidence on social media regulation. For example, AI companies have faced allegations of political bias regarding the images and text their models produce, similar to the allegations social media companies have faced regarding content ranking on their platforms. First, I compare and contrast the affordances of generative AI and social media to highlight their similarities and differences. Then, I discuss specific policy recommendations based on the evolution of social media and their regulation. These recommendations include investments in: efforts to counter bias and perceptions thereof (e.g., via transparency, researcher access, oversight boards, democratic input, research studies), specific areas of regulatory concern (e.g., youth wellbeing, election integrity) and trust and safety, computational social science research, and a more global perspective. Applying lessons learnt from social media regulation to generative AI regulation can save effort and time, and prevent avoidable mistakes.