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PreprintCited by 3Ethics and Social Impacts of AIAdversarial Robustness in Machine LearningExplainable Artificial Intelligence (XAI)

Open technical problems in open-weight ai model risk management

Open access
Casper, Stephen, O'Brien, Kyle, Longpre, Shayne, Seger, Elizabeth, Klyman, Kevin, Bommasani, Rishi, Nrusimha, Aniruddha, Shumailov, Ilia +14 more·2025·SSRN Electronic Journal
DOI 10.2139/ssrn.5705186
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Crossref · 10.2139/ssrn.5705186

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3 of 3 references verified0 citation errors · 0 not checkable

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  • Many harms stem less from openness than from availability and capability, with widely available proprietary models also enabling misuse at scale.

    “recent work emphasizes that many harms stem less from openness than from availability and capability, with widely available proprietary models also enabling misuse at scale [16].”

    From Reimagining Open Source and Openness in AI: Co-Creating Responsible Technological Futures (2026) · cites this paper as [16]

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Authors
Casper, S., O'Brien, K., Longpre, S., Seger, E., Klyman, K., Bommasani, R., Nrusimha, A., Shumailov, I., Mindermann, S., Basart, S., Rudzicz, F., Pelrine, K., Ghosh, A., Strait, A., Kirk, R., Hendrycks, D., Henderson, P., Kolter, J. Z., Irving, G., Gal, Y., Bengio, Y., & Hadfield-Menell, D.
Affiliations
  • Massachusetts Institute of Technology (US)
  • Apple (United States) (US)
  • Centre for the Governance of AI (GB)
  • Stanford University (US)
  • Google DeepMind (United Kingdom) (GB)
  • University of Toronto (CA)
  • Mila - Quebec Artificial Intelligence Institute (CA)
  • University of Connecticut (US)
  • Princeton University (US)
  • Robert Bosch (United States) (US)
  • University of Oxford (GB)
  • Université de Montréal (CA)
Corresponding author
Casper, Stephen
ORCID
Venue
SSRN Electronic Journal
Publisher
Elsevier BV
Published
2025
ISSN
1556-5068 (ISSN-L)
DOI
10.2139/ssrn.5705186
OpenAlex
W4415965747
Cited by
3
References
3
Citations by year
2026: 3
Type
posted content
Language
en
Open access
Locations
  • SSRN Electronic Journal (acceptedVersion)
  • arXiv (Cornell University) (submittedVersion, cc-by)
  • arXiv (Cornell University) (cc-by)
Topics
  • Social Sciences › Safety Research › Ethics and Social Impacts of AI
  • Physical Sciences › Computer Science › Artificial Intelligence › Adversarial Robustness in Machine Learning
  • Physical Sciences › Computer Science › Artificial Intelligence › Explainable Artificial Intelligence (XAI)
Keywords
model safety, training data, training algorithms, model evaluation, model deployment, ecological monitoring, open research, technical challenges

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