The Gradient of Generative AI Release: Methods and Considerations

Published on Feb 5, 2023


As increasingly powerful generative AI systems are developed, the release method greatly varies. We propose a framework to assess six levels of access to generative AI systems: fully closed; gradual or staged access; hosted access; cloud-based or API access; downloadable access; and fully open. Each level, from fully closed to fully open, can be viewed as an option along a gradient. We outline key considerations across this gradient: release methods come with tradeoffs, especially around the tension between concentrating power and mitigating risks. Diverse and multidisciplinary perspectives are needed to examine and mitigate risk in generative AI systems from conception to deployment. We show trends in generative system release over time, noting closedness among large companies for powerful systems and openness among organizations founded on principles of openness. We also enumerate safety controls and guardrails for generative systems and necessary investments to improve future releases.


Foundational paper for AI openness!

@irenesolaiman will there be a v2 of this work?

There can be expansions if helpful! I'm thinking about more context of legal mechanisms like licenses and landscape of more recent releases like Llama 2

Sign up or log in to comment

Models citing this paper 0

No model linking this paper

Cite in a model to link it from this page.

Datasets citing this paper 2

Spaces citing this paper 0

No Space linking this paper

Cite in a Space to link it from this page.

Collections including this paper 2