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Generative AI entails a credit-blame asymmetry
Journal article   Peer reviewed

Generative AI entails a credit-blame asymmetry

Sebastian Porsdam Mann, Brian D. Earp, Sven Nyholm, John Danaher, Nikolaj Moller, Hilary Bowman-Smart, Joshua Hatherley, Julian Koplin, Monika Plozza, Daniel Rodger, …
Nature machine intelligence, Vol.5(5), pp.472-475
01/05/2023
Handle:
https://hdl.handle.net/10523/20982

Abstract

Computer Science Computer Science, Artificial Intelligence Computer Science, Interdisciplinary Applications Science & Technology Technology
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.

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