This resource is the first of two on the benefits and risks of open-weights model release. This paper broadly supports the open release of foundation model weights, arguing that such openness can drive competition, enhance innovation, and promote transparency. It contends that open models can distribute power more evenly across society, reducing the risk of market monopolies and fostering a diverse ecosystem of AI development. Despite potential risks like disinformation or misuse by malicious actors, the article argues that current evidence about these risks remains limited. It suggests that regulatory interventions might disproportionately harm developers, particularly if policies fail to account for the distinct benefits and challenges of open models compared to closed ones.Original text: https://hai.stanford.edu/sites/default/files/2023-12/Governing-Open-Foundation-Models.pdf Author(s): Rishi Bommasani, Sayash Kapoor, Kevin Klyman, Shayne Longpre, Ashwin Ramaswami, Daniel Zhang, Marietje Schaake, Daniel E. Ho, Arvind Narayanan, Percy LiangA podcast by BlueDot Impact.Learn more on the AI Safety Fundamentals website.

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