Foundation Model Transparency Reports

Authors

  • Rishi Bommasani Stanford University
  • Kevin Klyman Stanford University
  • Shayne Longpre Massachusetts Institute of Technology
  • Betty Xiong Stanford University
  • Sayash Kapoor Princeton University
  • Nestor Maslej Stanford University
  • Arvind Narayanan Princeton University
  • Percy Liang Stanford University

DOI:

https://doi.org/10.1609/aies.v7i1.31628

Abstract

Foundation models are critical digital technologies with sweeping societal impact that necessitates transparency. To codify how foundation model developers should provide transparency about the development and deployment of their models, we propose Foundation Model Transparency Reports, drawing upon the transparency reporting practices in social media. While external documentation of societal harms prompted social media transparency reports, our objective is to institutionalize transparency reporting for foundation models while the industry is still nascent. To design our reports, we identify 6 design principles given the successes and shortcomings of social media transparency reporting. To further schematize our reports, we draw upon the 100 transparency indicators from the Foundation Model Transparency Index. Given these indicators, we measure the extent to which they overlap with the transparency requirements included in six prominent government policies (e.g. the EU AI Act, the US Executive Order on Safe, Secure, and Trustworthy AI). Well-designed transparency reports could reduce compliance costs, in part due to overlapping regulatory requirements across different jurisdictions. We encourage foundation model developers to regularly publish transparency reports, building upon recommendations from the G7 and the White House.

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Published

2024-10-16

How to Cite

Bommasani, R., Klyman, K., Longpre, S., Xiong, B., Kapoor, S., Maslej, N., … Liang, P. (2024). Foundation Model Transparency Reports. Proceedings of the AAAI ACM Conference on AI, Ethics, and Society, 7(1), 181–195. https://doi.org/10.1609/aies.v7i1.31628