Generative AI entails a credit–blame asymmetry
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.
Bibliographic Details
| Main Authors: |
Porsdam Mann, S,
Earp, BD,
Nyholm, S,
Danaher, J,
Møller, N,
Bowman-Smart, H,
Hatherley, J,
Koplin, J,
Plozza, M,
Rodger, D,
Treit, PV,
Renard, G,
McMillan, J,
Savulescu, J |
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| Format: | Journal article
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| Language: | English |
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| Published: |
Springer Nature
2023
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