Moral Responsibility for AI Systems

Abstract

As more and more decisions that have a significant ethical dimension are being outsourced to AI systems, it is important to have a definition of moral responsibility that can be applied to AI systems. Moral responsibility for an outcome of an agent who performs some action is commonly taken to involve both a causal condition and an epistemic condition: the action should cause the outcome, and the agent should have been aware - in some form or other - of the possible moral consequences of their action. This paper presents a formal definition of both conditions within the framework of causal models. I compare my approach to the existing approaches of Braham and van Hees (BvH) and of Halpern and Kleiman-Weiner (HK). I then generalize my definition into a degree of responsibility.

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Cite

Text

Beckers. "Moral Responsibility for AI Systems." Neural Information Processing Systems, 2023.

Markdown

[Beckers. "Moral Responsibility for AI Systems." Neural Information Processing Systems, 2023.](https://mlanthology.org/neurips/2023/beckers2023neurips-moral/)

BibTeX

@inproceedings{beckers2023neurips-moral,
  title     = {{Moral Responsibility for AI Systems}},
  author    = {Beckers, Sander},
  booktitle = {Neural Information Processing Systems},
  year      = {2023},
  url       = {https://mlanthology.org/neurips/2023/beckers2023neurips-moral/}
}