Unravelling responsibility for AI
It is widely acknowledged that we need to establish where responsibility lies for the outputs and impacts of AI-enabled systems. This is important to achieve justice and compensation for victims of AI harms, and to inform policy and engineering practice. But without a clear, thorough understanding o...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-09-01
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| Series: | Journal of Responsible Technology |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666659625000204 |
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| author | Zoe Porter Philippa Ryan Phillip Morgan Joanna Al-Qaddoumi Bernard Twomey Paul Noordhof John McDermid Ibrahim Habli |
| author_facet | Zoe Porter Philippa Ryan Phillip Morgan Joanna Al-Qaddoumi Bernard Twomey Paul Noordhof John McDermid Ibrahim Habli |
| author_sort | Zoe Porter |
| collection | DOAJ |
| description | It is widely acknowledged that we need to establish where responsibility lies for the outputs and impacts of AI-enabled systems. This is important to achieve justice and compensation for victims of AI harms, and to inform policy and engineering practice. But without a clear, thorough understanding of what ‘responsibility’ means, deliberations about where responsibility lies will be, at best, unfocused and incomplete and, at worst, misguided. Furthermore, AI-enabled systems exist within a wider ecosystem of actors, decisions, and governance structures, giving rise to complex networks of responsibility relations. To address these issues, this paper presents a conceptual framework of responsibility, accompanied with a graphical notation and general methodology for visualising these responsibility networks and for tracing different responsibility attributions for AI. Taking the three-part formulation ‘Actor A is responsible for Occurrence O,’ the framework unravels the concept of responsibility to clarify that there are different possibilities of who is responsible for AI, senses in which they are responsible, and aspects of events they are responsible for. The notation allows these permutations to be represented graphically. The methodology enables users to apply the framework to specific scenarios. The aim is to offer a foundation to support stakeholders from diverse disciplinary backgrounds to discuss and address complex responsibility questions in hypothesised and real-world cases involving AI. The work is illustrated by application to a fictitious scenario of a fatal collision between a crewless, AI-enabled maritime vessel in autonomous mode and a traditional, crewed vessel at sea. |
| format | Article |
| id | doaj-art-94dcf468ef3d4aa58ab46bca24eaf30b |
| institution | Kabale University |
| issn | 2666-6596 |
| language | English |
| publishDate | 2025-09-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Journal of Responsible Technology |
| spelling | doaj-art-94dcf468ef3d4aa58ab46bca24eaf30b2025-08-20T03:58:18ZengElsevierJournal of Responsible Technology2666-65962025-09-012310012410.1016/j.jrt.2025.100124Unravelling responsibility for AIZoe Porter0Philippa Ryan1Phillip Morgan2Joanna Al-Qaddoumi3Bernard Twomey4Paul Noordhof5John McDermid6Ibrahim Habli7Department of Computer Science, University of York, York, England, UK; Corresponding author.Department of Computer Science, University of York, York, England, UKYork Law School, University of York, York, England, UKYork Law School, University of York, York, England, UKDepartment of Computer Science, University of York, York, England, UKDepartment of Philosophy, University of York, York, England, UKDepartment of Computer Science, University of York, York, England, UKDepartment of Computer Science, University of York, York, England, UKIt is widely acknowledged that we need to establish where responsibility lies for the outputs and impacts of AI-enabled systems. This is important to achieve justice and compensation for victims of AI harms, and to inform policy and engineering practice. But without a clear, thorough understanding of what ‘responsibility’ means, deliberations about where responsibility lies will be, at best, unfocused and incomplete and, at worst, misguided. Furthermore, AI-enabled systems exist within a wider ecosystem of actors, decisions, and governance structures, giving rise to complex networks of responsibility relations. To address these issues, this paper presents a conceptual framework of responsibility, accompanied with a graphical notation and general methodology for visualising these responsibility networks and for tracing different responsibility attributions for AI. Taking the three-part formulation ‘Actor A is responsible for Occurrence O,’ the framework unravels the concept of responsibility to clarify that there are different possibilities of who is responsible for AI, senses in which they are responsible, and aspects of events they are responsible for. The notation allows these permutations to be represented graphically. The methodology enables users to apply the framework to specific scenarios. The aim is to offer a foundation to support stakeholders from diverse disciplinary backgrounds to discuss and address complex responsibility questions in hypothesised and real-world cases involving AI. The work is illustrated by application to a fictitious scenario of a fatal collision between a crewless, AI-enabled maritime vessel in autonomous mode and a traditional, crewed vessel at sea.http://www.sciencedirect.com/science/article/pii/S2666659625000204ResponsibilityArtificial intelligence |
| spellingShingle | Zoe Porter Philippa Ryan Phillip Morgan Joanna Al-Qaddoumi Bernard Twomey Paul Noordhof John McDermid Ibrahim Habli Unravelling responsibility for AI Journal of Responsible Technology Responsibility Artificial intelligence |
| title | Unravelling responsibility for AI |
| title_full | Unravelling responsibility for AI |
| title_fullStr | Unravelling responsibility for AI |
| title_full_unstemmed | Unravelling responsibility for AI |
| title_short | Unravelling responsibility for AI |
| title_sort | unravelling responsibility for ai |
| topic | Responsibility Artificial intelligence |
| url | http://www.sciencedirect.com/science/article/pii/S2666659625000204 |
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