Are open foundation models actually more risky than closed ones?
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A policy brief on open foundation models
Some of the most pressing questions in artificial intelligence concern the future of open foundation models (FMs). Do these models pose risks so large that we must attempt to stop their proliferation? Or are the risks overstated and the benefits under emphasized? Earlier this week, in collaboration with Stanford HAI, CRFM, and RegLab, we released a policy brief addressing these questions. The brief is based on lessons from a workshop we organized this September and our work since. It outlines the current evidence on the risk of open FMs and some recommendations for policymakers on how to…
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