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Operationalising AI ethics: conducting socio-technical assessment
Umeå University, Faculty of Science and Technology, Department of Computing Science.ORCID iD: 0000-0002-9808-2037
Umeå University, Faculty of Science and Technology, Department of Computing Science.
Umeå University, Faculty of Science and Technology, Department of Computing Science.ORCID iD: 0000-0001-9499-1535
2023 (English)In: Human-Centered Artificial Intelligence: Advanced Lectures / [ed] Mohamed Chetouani; Virginia Dignum; Paul Lukowicz; Carles Sierra, Springer, 2023, p. 304-321Conference paper, Published paper (Refereed)
Abstract [en]

Several high profile incidents that involve Artificial Intelligence (AI) have captured public attention and increased demand for regulation. Low public trust and attitudes towards AI reinforce the need for concrete policy around its development and use. However, current guidelines and standards rolled out by institutions globally are considered by many as high-level and open to interpretation, making them difficult to put into practice. This paper presents ongoing research in the field of Responsible AI and explores numerous methods of operationalising AI ethics. If AI is to be effectively regulated, it must not be considered as a technology alone—AI is embedded in the fabric of our societies and should thus be treated as a socio-technical system, requiring multi-stakeholder involvement and employment of continuous value-based methods of assessment. When putting guidelines and standards into practice, context is of critical importance. The methods and frameworks presented in this paper emphasise this need and pave the way towards operational AI ethics.

Place, publisher, year, edition, pages
Springer, 2023. p. 304-321
Series
Lecture Notes in Computer Science, ISSN 0302-9743, E-ISSN 1611-3349 ; 13500
Keywords [en]
AI ethics, Responsible AI, Socio-technical assessment
National Category
Computer Sciences Information Systems, Social aspects
Identifiers
URN: urn:nbn:se:umu:diva-206936DOI: 10.1007/978-3-031-24349-3_16Scopus ID: 2-s2.0-85152549666ISBN: 9783031243486 (print)OAI: oai:DiVA.org:umu-206936DiVA, id: diva2:1753631
Conference
18th European Advanced Course on Artificial Intelligence, ACAI 2021, Berlin, Germany, October 11-15, 2021
Note

Part of the book sub series: Lecture Notes in Artificial Intelligence (LNAI)

Conference series: ACAI: ECCAI Advanced Course on Artificial Intelligence

Available from: 2023-04-28 Created: 2023-04-28 Last updated: 2023-04-28Bibliographically approved

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Methnani, LeilaBrännström, MattiasTheodorou, Andreas

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Total: 346 hits
CiteExportLink to record
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