Journal article
Can we bridge AI’s responsibility gap at will?
- Abstract:
- Artificial intelligence (AI) increasingly executes tasks that previously only humans could do, such as drive a car, fight in war, or perform a medical operation. However, as the very best AI systems tend to be the least controllable and the least transparent, some scholars argued that humans can no longer be morally responsible for some of the AI-caused outcomes, which would then result in a responsibility gap. In this paper, I assume, for the sake of argument, that at least some of the most sophisticated AI systems do indeed create responsibility gaps, and I ask whether we can bridge these gaps at will, viz. whether certain people could take responsibility for AI-caused harm simply by performing a certain speech act, just as people can give permission for something simply by performing the act of consent. So understood, taking responsibility would be a genuine normative power. I first discuss and reject the view of Champagne and Tonkens, who advocate a view of taking liability. According to this view, a military commander can and must, ahead of time, accept liability to blame and punishment for any harm caused by autonomous weapon systems under her command. I then defend my own proposal of taking answerability, viz. the view that people can makes themselves morally answerable for the harm caused by AI systems, not only ahead of time but also when harm has already been caused.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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(Preview, Version of record, pdf, 700.6KB, Terms of use)
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- Publisher copy:
- 10.1007/s10677-022-10313-9
Authors
+ European Research Council
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- Funder identifier:
- https://ror.org/0472cxd90
- Grant:
- 789270
- Publisher:
- Springer Nature
- Journal:
- Ethical Theory and Moral Practice More from this journal
- Volume:
- 25
- Issue:
- 4
- Pages:
- 575-593
- Publication date:
- 2022-07-29
- Acceptance date:
- 2022-07-04
- DOI:
- EISSN:
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1572-8447
- ISSN:
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1386-2820
- Language:
-
English
- Keywords:
- Pubs id:
-
1272961
- Local pid:
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pubs:1272961
- Deposit date:
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2025-09-03
- ARK identifier:
Terms of use
- Copyright holder:
- Kiener et al
- Copyright date:
- 2022
- Rights statement:
- © 2022 The Authors. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.
- Licence:
- CC Attribution (CC BY)
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