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Stanford CRFM

crfm.stanford.edu · 3,363 words · saved by 1 readers

As foundation models (e.g., GPT-3, PaLM, DALL-E 2) become more powerful and ubiquitous, the issue of responsible release becomes critically important. In this blog post, we use the term release to mean research access: foundation model developers making assets such as data, code, and models accessible to external researchers. Deploying to users for testing and collecting feedback (Ouyang et al. 2022; Scheurer et al. 2022; AI Test Kitchen) and deploying to end users in products (Schwartz et al. 2022) are other forms of release that are out of scope for this blog post. Foundation model developers presently take divergent positions on the topic of release and research access. For example, EleutherAI, Meta, and the BigScience project led by Hugging Face embrace broadly open release (see EleutherAI’s statement and Meta’s recent release). In contrast, OpenAI advocates for a staged release and currently provides the general public with only API access; Microsoft also provides API access, but

Stanford CRFM The Time Is Now to Develop Community Norms for the Release of Foundation Models Authors: Percy Liang and Rishi Bommasani and Kathleen Creel and Rob Reich Perspectives about the benefits and risks of release vary widely. We propose setting up a review board to develop community norms and encourage coordination on release of foundation models for research access. As foundation models (e.g., GPT-3 , PaLM , DALL-E 2 ) become more powerful and ubiquitous, the issue of responsible release becomes critically important. In this blog post, we use the term release to mean research access :

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