# The Societal Impact of Foundation Models: Advancing Evidence-based AI Policy

arXiv: https://arxiv.org/abs/2506.23123 · HTML: https://mlsanity.com/paper/2506.23123/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 29 Jun 2025.

## Built on by (most cited first, 1 of 1)

- [Who Evaluates AI's Social Impacts? Mapping Coverage and Gaps in First and Third Party Evaluations](https://mlsanity.com/paper/2511.05613/) (2025)

## Abstract (arXiv)

Artificial intelligence is humanity's most promising technology because of the remarkable capabilities offered by foundation models. Yet, the same technology brings confusion and consternation: foundation models are poorly understood and they may precipitate a wide array of harms. This dissertation explains how technology and society coevolve in the age of AI, organized around three themes. First, the conceptual framing: the capabilities, risks, and the supply chain that grounds foundation models in the broader economy. Second, the empirical insights that enrich the conceptual foundations: transparency created via evaluations at the model level and indexes at the organization level. Finally, the transition from understanding to action: superior understanding of the societal impact of foundation models advances evidence-based AI policy. View together, this dissertation makes inroads into achieving better societal outcomes in the age of AI by building the scientific foundations and research-policy interface required for better AI governance.