Generative AI entails a credit–blame asymmetry

Research output: Contribution to journalComment/debateResearchpeer-review

  • Porsdam Mann, Sebastian
  • Brian D. Earp
  • Sven Nyholm
  • John Danaher
  • Nikolaj Møller
  • Hilary Bowman-Smart
  • Joshua Hatherley
  • Julian Koplin
  • Monika Plozza
  • Daniel Rodger
  • Peter V. Treit
  • Gregory Renard
  • John McMillan
  • Julian Savulescu
Generative AI programs can produce high-quality written and visual content that may be used for good or ill. We argue that a credit–blame asymmetry arises for assigning responsibility for these outputs and discuss urgent ethical and policy implications focused on large-scale language models.
Original languageEnglish
JournalNature Machine Intelligence
Volume5
Issue number5
Pages (from-to)472-475
Number of pages4
DOIs
Publication statusPublished - 2023

ID: 383103263