Generative AI entails a credit–blame asymmetry

Publikation: Bidrag til tidsskriftKommentar/debatForskningfagfællebedømt

  • 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.
OriginalsprogEngelsk
TidsskriftNature Machine Intelligence
Vol/bind5
Udgave nummer5
Sider (fra-til)472-475
Antal sider4
DOI
StatusUdgivet - 2023

Bibliografisk note

Funding Information:
We wish to thank an anonymous reviewer for very helpful and timely suggestions for improvements to an earlier version of this article.

ID: 383103263