Position Paper: Model Access should be a Key Concern in AI Governance
Track: Sociotechnical
Keywords: model access governance, AI governance
TL;DR: We spotlight and motivate Model Access Governance, a research field focused on helping organisations and governments make responsible, evidence-based decisions about sharing access to AI models.
Abstract: The downstream use cases, benefits, and risks of AI systems depend significantly on the access afforded to the system, and to whom. However, the downstream implications of different access styles are not well understood, making it difficult for decision-makers to govern model access responsibly. Consequently, we spotlight Model Access Governance, an emerging field focused on helping organisations and governments make responsible, evidence-based access decisions. We outline the motivation for developing this field by highlighting the significant risks of misgoverning model access, the limitations of existing research on the topic, and the opportunity for impact. We then make four sets of recommendations, aimed at helping AI evaluation organisations, frontier AI companies, governments and international bodies build consensus around empirically-driven access governance.
Submission Number: 63
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