Standard
Generative AI entails a credit–blame asymmetry. / Porsdam Mann, Sebastian; Earp, Brian D.; Nyholm, Sven; Danaher, John; Møller, Nikolaj; Bowman-Smart, Hilary; Hatherley, Joshua; Koplin, Julian; Plozza, Monika; Rodger, Daniel; Treit, Peter V.; Renard, Gregory; McMillan, John; Savulescu, Julian.
In:
Nature Machine Intelligence, Vol. 5, No. 5, 2023, p. 472-475.
Research output: Contribution to journal › Comment/debate › Research › peer-review
Harvard
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 2023, '
Generative AI entails a credit–blame asymmetry',
Nature Machine Intelligence, vol. 5, no. 5, pp. 472-475.
https://doi.org/10.1038/s42256-023-00653-1
APA
Porsdam Mann, S., Earp, B. D., Nyholm, S., Danaher, J., Møller, N., Bowman-Smart, H., Hatherley, J., Koplin, J., Plozza, M., Rodger, D., Treit, P. V., Renard, G., McMillan, J., & Savulescu, J. (2023).
Generative AI entails a credit–blame asymmetry.
Nature Machine Intelligence,
5(5), 472-475.
https://doi.org/10.1038/s42256-023-00653-1
Vancouver
Porsdam Mann S, Earp BD, Nyholm S, Danaher J, Møller N, Bowman-Smart H et al.
Generative AI entails a credit–blame asymmetry.
Nature Machine Intelligence. 2023;5(5):472-475.
https://doi.org/10.1038/s42256-023-00653-1
Author
Porsdam Mann, Sebastian ; Earp, Brian D. ; Nyholm, Sven ; Danaher, John ; Møller, Nikolaj ; Bowman-Smart, Hilary ; Hatherley, Joshua ; Koplin, Julian ; Plozza, Monika ; Rodger, Daniel ; Treit, Peter V. ; Renard, Gregory ; McMillan, John ; Savulescu, Julian. / Generative AI entails a credit–blame asymmetry. In: Nature Machine Intelligence. 2023 ; Vol. 5, No. 5. pp. 472-475.
Bibtex
@article{2bfc6025781845ec9c279c7f57fbfdb6,
title = "Generative AI entails a credit–blame asymmetry",
abstract = "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.",
author = "{Porsdam Mann}, Sebastian and Earp, {Brian D.} and Sven Nyholm and John Danaher and Nikolaj M{\o}ller and Hilary Bowman-Smart and Joshua Hatherley and Julian Koplin and Monika Plozza and Daniel Rodger and Treit, {Peter V.} and Gregory Renard and John McMillan and Julian Savulescu",
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.",
year = "2023",
doi = "10.1038/s42256-023-00653-1",
language = "English",
volume = "5",
pages = "472--475",
journal = "Nature Machine Intelligence",
issn = "2522-5839",
publisher = "Springer",
number = "5",
}
RIS
TY - JOUR
T1 - Generative AI entails a credit–blame asymmetry
AU - Porsdam Mann, Sebastian
AU - Earp, Brian D.
AU - Nyholm, Sven
AU - Danaher, John
AU - Møller, Nikolaj
AU - Bowman-Smart, Hilary
AU - Hatherley, Joshua
AU - Koplin, Julian
AU - Plozza, Monika
AU - Rodger, Daniel
AU - Treit, Peter V.
AU - Renard, Gregory
AU - McMillan, John
AU - Savulescu, Julian
N1 - Funding Information:
We wish to thank an anonymous reviewer for very helpful and timely suggestions for improvements to an earlier version of this article.
PY - 2023
Y1 - 2023
N2 - 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.
AB - 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.
U2 - 10.1038/s42256-023-00653-1
DO - 10.1038/s42256-023-00653-1
M3 - Comment/debate
AN - SCOPUS:85158030467
VL - 5
SP - 472
EP - 475
JO - Nature Machine Intelligence
JF - Nature Machine Intelligence
SN - 2522-5839
IS - 5
ER -
