Position: On the Societal Impact of Open Foundation Models
| dc.contributor.author | Kapoor, Sayash | en |
| dc.contributor.author | Bommasani, Rishi | en |
| dc.contributor.author | Klyman, Kevin | en |
| dc.contributor.author | Longpre, Shayne | en |
| dc.contributor.author | Ramaswami, Ashwin | en |
| dc.contributor.author | Cihon, Peter | en |
| dc.contributor.author | Hopkins, Aspen | en |
| dc.contributor.author | Bankston, Kevin | en |
| dc.contributor.author | Biderman, Stella | en |
| dc.contributor.author | Bogen, Miranda | en |
| dc.contributor.author | Chowdhury, Rumman | en |
| dc.contributor.author | Engler, Alex | en |
| dc.contributor.author | Henderson, Peter | en |
| dc.contributor.author | Jernite, Yacine | en |
| dc.contributor.author | Lazar, Seth | en |
| dc.contributor.author | Maffulli, Stefano | en |
| dc.contributor.author | Nelson, Alondra | en |
| dc.contributor.author | Pineau, Joelle | en |
| dc.contributor.author | Skowron, Aviya | en |
| dc.contributor.author | Song, Dawn | en |
| dc.contributor.author | Storchan, Victor | en |
| dc.contributor.author | Zhang, Daniel | en |
| dc.contributor.author | Ho, Daniel E. | en |
| dc.contributor.author | Liang, Percy | en |
| dc.contributor.author | Narayanan, Arvind | en |
| dc.date.accessioned | 2025-05-23T09:21:28Z | |
| dc.date.available | 2025-05-23T09:21:28Z | |
| dc.date.issued | 2024 | en |
| dc.description.abstract | Foundation 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.sponsorship | We 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.status | Peer-reviewed | en |
| dc.format.extent | 23 | en |
| dc.identifier.scopus | 85203834338 | en |
| dc.identifier.uri | http://www.scopus.com/inward/record.url?scp=85203834338&partnerID=8YFLogxK | en |
| dc.identifier.uri | https://hdl.handle.net/1885/733751890 | |
| dc.language.iso | en | en |
| dc.relation.ispartofseries | 41st International Conference on Machine Learning, ICML 2024 | en |
| dc.rights | Publisher Copyright: Copyright 2024 by the author(s) | en |
| dc.source | Proceedings of Machine Learning Research | en |
| dc.title | Position: On the Societal Impact of Open Foundation Models | en |
| dc.type | Conference paper | en |
| dspace.entity.type | Publication | en |
| local.bibliographicCitation.lastpage | 23104 | en |
| local.bibliographicCitation.startpage | 23082 | en |
| local.contributor.affiliation | Kapoor, Sayash; Princeton University | en |
| local.contributor.affiliation | Bommasani, Rishi; Stanford University | en |
| local.contributor.affiliation | Klyman, Kevin; Stanford University | en |
| local.contributor.affiliation | Longpre, Shayne; Massachusetts Institute of Technology | en |
| local.contributor.affiliation | Ramaswami, Ashwin; Georgetown University | en |
| local.contributor.affiliation | Cihon, Peter; Microsoft USA | en |
| local.contributor.affiliation | Hopkins, Aspen; Massachusetts Institute of Technology | en |
| local.contributor.affiliation | Bankston, Kevin; Georgetown University | en |
| local.contributor.affiliation | Biderman, Stella; Eleuther AI | en |
| local.contributor.affiliation | Bogen, Miranda; Center for Democracy and Technology | en |
| local.contributor.affiliation | Chowdhury, Rumman; Humane Intelligence | en |
| local.contributor.affiliation | Engler, Alex; The Brookings Institution | en |
| local.contributor.affiliation | Henderson, Peter; Princeton University | en |
| local.contributor.affiliation | Jernite, Yacine; Hugging Face | en |
| local.contributor.affiliation | Lazar, Seth; School of Philosophy, Research School of Social Sciences, ANU College of Arts & Social Sciences, The Australian National University | en |
| local.contributor.affiliation | Maffulli, Stefano; Open Source Initiative | en |
| local.contributor.affiliation | Nelson, Alondra; Institute for Advanced Studies | en |
| local.contributor.affiliation | Pineau, Joelle; Meta | en |
| local.contributor.affiliation | Skowron, Aviya; Eleuther AI | en |
| local.contributor.affiliation | Song, Dawn; University of California at Berkeley | en |
| local.contributor.affiliation | Storchan, Victor; Mozilla AI | en |
| local.contributor.affiliation | Zhang, Daniel; Stanford University | en |
| local.contributor.affiliation | Ho, Daniel E.; Stanford University | en |
| local.contributor.affiliation | Liang, Percy; Stanford University | en |
| local.contributor.affiliation | Narayanan, Arvind; Princeton University | en |
| local.identifier.citationvolume | 235 | en |
| local.identifier.pure | 594a8dec-b10f-4cb4-945e-91b6f8d019f6 | en |
| local.identifier.url | https://www.scopus.com/pages/publications/85203834338 | en |
| local.type.status | Published | en |