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A Penalty Default Approach to Preemptive Harm Disclosure and Mitigation for AI Systems

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  • Author(s): Yew, Rui-Jie; Hadfield-Menell, Dylan
  • Source:
    ACM|Proceedings of the 2022 AAAI/ACM Conference on AI, Ethics, and Society
  • Document Type:
    article in journal/newspaper
    conference object
  • Language:
    English
  • Additional Information
    • Contributors:
      Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory; Massachusetts Institute of Technology. Institute for Data, Systems, and Society; Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
    • Publication Information:
      ACM|Proceedings of the 2022 AAAI/ACM Conference on AI, Ethics, and Society
    • Publication Date:
      2022
    • Collection:
      DSpace@MIT (Massachusetts Institute of Technology)
    • File Description:
      application/pdf
    • Relation:
      https://doi.org/10.1145/3514094.3534130; https://hdl.handle.net/1721.1/146443; PUBLISHER_CC
    • Online Access:
      https://hdl.handle.net/1721.1/146443
    • Rights:
      Creative Commons Attribution 4.0 International license ; https://creativecommons.org/licenses/by/4.0/ ; The author(s)
    • Accession Number:
      edsbas.586D58F1