Position: On the Societal Impact of Open Foundation Models

dc.contributor.authorKapoor, Sayashen
dc.contributor.authorBommasani, Rishien
dc.contributor.authorKlyman, Kevinen
dc.contributor.authorLongpre, Shayneen
dc.contributor.authorRamaswami, Ashwinen
dc.contributor.authorCihon, Peteren
dc.contributor.authorHopkins, Aspenen
dc.contributor.authorBankston, Kevinen
dc.contributor.authorBiderman, Stellaen
dc.contributor.authorBogen, Mirandaen
dc.contributor.authorChowdhury, Rummanen
dc.contributor.authorEngler, Alexen
dc.contributor.authorHenderson, Peteren
dc.contributor.authorJernite, Yacineen
dc.contributor.authorLazar, Sethen
dc.contributor.authorMaffulli, Stefanoen
dc.contributor.authorNelson, Alondraen
dc.contributor.authorPineau, Joelleen
dc.contributor.authorSkowron, Aviyaen
dc.contributor.authorSong, Dawnen
dc.contributor.authorStorchan, Victoren
dc.contributor.authorZhang, Danielen
dc.contributor.authorHo, Daniel E.en
dc.contributor.authorLiang, Percyen
dc.contributor.authorNarayanan, Arvinden
dc.date.accessioned2025-05-23T09:21:28Z
dc.date.available2025-05-23T09:21:28Z
dc.date.issued2024en
dc.description.abstractFoundation models are powerful technologies: how they are released publicly directly shapes their societal impact. In this position paper, we focus on open foundation models, defined here as those with broadly available model weights (e.g. Llama 3, Stable Diffusion XL). We identify five distinctive properties of open foundation models (e.g. greater customizability, poor monitoring) that mediate their benefits and risks. Open foundation models present significant benefits, with some caveats, that span innovation, competition, the distribution of decision-making power, and transparency. To understand their risks of misuse, we design a risk assessment framework for analyzing their marginal risk. Across several misuse vectors (e.g. cyberattacks, bioweapons), we find that current research is insufficient to effectively characterize the marginal risk of open foundation models relative to pre-existing technologies. The framework helps explain why the marginal risk is low in some cases, clarifies disagreements about misuse risks by revealing that past work has focused on different subsets of the framework with different assumptions, and articulates a way forward for more constructive debate. Overall, our work supports a more grounded assessment of the societal impact of open foundation models by outlining what research is needed to empirically validate their theoretical benefits and risks.en
dc.description.sponsorshipWe thank Ellie Evans, Helen Toner, Ion Stoica, Marietje Schaake, Nate Persily, Nicholas Carlini, Rob Reich, Steven Cao, and Zico Kolter for extensive feedback on this work. We are grateful to the participants of the Stanford Workshop on the Governance of Open Foundation Models and the Princeton-Stanford Workshop on Responsible and Open Foundation Models for their feedback and input. This work was supported in part by the AI2050 program at Schmidt Futures (Grant G-22-63429), the Patrick J. McGovern Foundation, and the Hoffman-Yee grant program of the Stanford Institute for Human-Centered Artificial Intelligence.en
dc.description.statusPeer-revieweden
dc.format.extent23en
dc.identifier.scopus85203834338en
dc.identifier.urihttp://www.scopus.com/inward/record.url?scp=85203834338&partnerID=8YFLogxKen
dc.identifier.urihttps://hdl.handle.net/1885/733751890
dc.language.isoenen
dc.relation.ispartofseries41st International Conference on Machine Learning, ICML 2024en
dc.rightsPublisher Copyright: Copyright 2024 by the author(s)en
dc.sourceProceedings of Machine Learning Researchen
dc.titlePosition: On the Societal Impact of Open Foundation Modelsen
dc.typeConference paperen
dspace.entity.typePublicationen
local.bibliographicCitation.lastpage23104en
local.bibliographicCitation.startpage23082en
local.contributor.affiliationKapoor, Sayash; Princeton Universityen
local.contributor.affiliationBommasani, Rishi; Stanford Universityen
local.contributor.affiliationKlyman, Kevin; Stanford Universityen
local.contributor.affiliationLongpre, Shayne; Massachusetts Institute of Technologyen
local.contributor.affiliationRamaswami, Ashwin; Georgetown Universityen
local.contributor.affiliationCihon, Peter; Microsoft USAen
local.contributor.affiliationHopkins, Aspen; Massachusetts Institute of Technologyen
local.contributor.affiliationBankston, Kevin; Georgetown Universityen
local.contributor.affiliationBiderman, Stella; Eleuther AIen
local.contributor.affiliationBogen, Miranda; Center for Democracy and Technologyen
local.contributor.affiliationChowdhury, Rumman; Humane Intelligenceen
local.contributor.affiliationEngler, Alex; The Brookings Institutionen
local.contributor.affiliationHenderson, Peter; Princeton Universityen
local.contributor.affiliationJernite, Yacine; Hugging Faceen
local.contributor.affiliationLazar, Seth; School of Philosophy, Research School of Social Sciences, ANU College of Arts & Social Sciences, The Australian National Universityen
local.contributor.affiliationMaffulli, Stefano; Open Source Initiativeen
local.contributor.affiliationNelson, Alondra; Institute for Advanced Studiesen
local.contributor.affiliationPineau, Joelle; Metaen
local.contributor.affiliationSkowron, Aviya; Eleuther AIen
local.contributor.affiliationSong, Dawn; University of California at Berkeleyen
local.contributor.affiliationStorchan, Victor; Mozilla AIen
local.contributor.affiliationZhang, Daniel; Stanford Universityen
local.contributor.affiliationHo, Daniel E.; Stanford Universityen
local.contributor.affiliationLiang, Percy; Stanford Universityen
local.contributor.affiliationNarayanan, Arvind; Princeton Universityen
local.identifier.citationvolume235en
local.identifier.pure594a8dec-b10f-4cb4-945e-91b6f8d019f6en
local.identifier.urlhttps://www.scopus.com/pages/publications/85203834338en
local.type.statusPublisheden

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