Responsible AI in the OSS: Reconciling Innovation with Risk Assessment and Disclosure

Abstract

Ethical concerns around AI have increased emphasis on model auditing and reporting requirements. We thoroughly review the current state of governance and evaluation practices to identify specific challenges to responsible AI development in OSS. We then analyze OSS projects to understand if model evaluation is associated with safety assessments, through documentation of limitations, biases, and other risks. Our analysis of 7902 Hugging Face projects found that while risk documentation is strongly associated with evaluation practices, high performers from the platform’s largest competitive leaderboard (N=789) were less accountable. Recognizing these delicate tensions from performance incentives may guide providers in revisiting the objectives of evaluation and legal scholars in formulating platform interventions and policies that balance innovation and responsibility.