Considerations for Governing Open Foundation Models

Brief by Rishi Bommasani et al: “Foundation models (e.g., GPT-4, Llama 2) are at the epicenter of AI, driving technological innovation and billions in investment. This paradigm shift has sparked widespread demands for regulation. Animated by factors as diverse as declining transparency and unsafe labor practices, limited protections for copyright and creative work, as well as market concentration and productivity gains, many have called for policymakers to take action.

Central to the debate about how to regulate foundation models is the process by which foundation models are released. Some foundation models like Google DeepMind’s Flamingo are fully closed, meaning they are available only to the model developer; others, such as OpenAI’s GPT-4, are limited access, available to the public but only as a black box; and still others, such as Meta’s Llama 2, are more open, with widely available model weights enabling downstream modification and scrutiny. As of August 2023, the U.K.’s Competition and Markets Authority documents the most common release approach for publicly-disclosed models is open release based on data from Stanford’s Ecosystem Graphs. Developers like Meta, Stability AI, Hugging Face, Mistral, Together AI, and EleutherAI frequently release models openly.

Governments around the world are issuing policy related to foundation models. As part of these efforts, open foundation models have garnered significant attention: The recent U.S. Executive Order on Safe, Secure, and Trustworthy Artificial Intelligence tasks the National Telecommunications and Information Administration with preparing a report on open foundation models for the president. In the EU, open foundation models trained with fewer than 1025 floating point operations (a measure of the amount of compute expended) appear to be exempted under the recently negotiated AI Act. The U.K.’s AI Safety Institute will “consider open-source systems as well as those deployed with various forms of access controls” as part of its initial priorities. Beyond governments, the Partnership on AI has introduced guidelines for the safe deployment of foundation models, recommending against open release for the most capable foundation models.

Policy on foundation models should support the open foundation model ecosystem, while providing resources to monitor risks and create safeguards to address harms. Open foundation models provide significant benefits to society by promoting competition, accelerating innovation, and distributing power. For example, small businesses hoping to build generative AI applications could choose among a variety of open foundation models that offer different capabilities and are often less expensive than closed alternatives. Further, open models are marked by greater transparency and, thereby, accountability. When a model is released with its training data, independent third parties can better assess the model’s capabilities and risks…(More)”.