Porter, Zoe, Conmy, Philippa Ryan orcid.org/0000-0003-1307-5207, Morgan, Phillip orcid.org/0000-0002-8797-4216 et al. (4 more authors) (2023) Unravelling Responsibility for AI. [Preprint]
Abstract
It is widely acknowledged that we need to establish where responsibility lies for the outputs and impacts of AI-enabled systems. But without a clear and precise understanding of what "responsibility" means, deliberations about where responsibility lies will be, at best, unfocused and incomplete and, at worst, misguided. To address this concern, this paper draws upon central distinctions in philosophy and law to clarify the concept of responsibility for AI for policymakers, practitioners, researchers and students from non-philosophical and non-legal backgrounds. Taking the three-part formulation "Actor A is responsible for Occurrence O," the paper unravels the concept of responsibility to clarify that there are different possibilities of who is responsible for AI, the senses in which they are responsible, and aspects of events they are responsible for. Criteria and conditions for fitting attributions of responsibility in the core senses (causal responsibility, role-responsibility, liability responsibility and moral responsibility) are articulated to promote an understanding of when responsibility attributions would be inappropriate or unjust. The analysis is presented with a graphical notation to facilitate informal diagrammatic reasoning and discussion about specific cases. It is illustrated by application to a scenario of a fatal collision between an autonomous AI-enabled ship and a traditional, crewed vessel at sea.
Metadata
Item Type: | Preprint |
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Authors/Creators: |
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Keywords: | cs.AI,cs.CY,cs.RO |
Dates: |
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Institution: | The University of York |
Academic Units: | The University of York > Faculty of Sciences (York) > Computer Science (York) The University of York > Faculty of Social Sciences (York) > The York Law School |
Depositing User: | Pure (York) |
Date Deposited: | 10 Aug 2023 14:30 |
Last Modified: | 11 Mar 2025 00:02 |
Status: | Published |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:202270 |