AI Accountability: Approaches, Affecting Factors, and Challenges

Raja, AK; Zhou, J

AI Accountability: Approaches, Affecting Factors, and Challenges

Raja, AK Zhou, J

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Publisher:: IEEE COMPUTER SOC
Publication Type:: Journal Article
Citation:: Computer, 2023, 56, (4), pp. 61-70
Issue Date:: 2023-04-01

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Full metadata record

Field	Value	Language
dc.contributor.author	Raja, AK
dc.contributor.author	Zhou, J https://orcid.org/0000-0001-6034-644X
dc.date.accessioned	2024-03-26T04:25:12Z
dc.date.available	2024-03-26T04:25:12Z
dc.date.issued	2023-04-01
dc.identifier.citation	Computer, 2023, 56, (4), pp. 61-70
dc.identifier.issn	0018-9162
dc.identifier.issn	1558-0814
dc.identifier.uri	http://hdl.handle.net/10453/177174
dc.description.abstract	Accountability is one of core ethical principles for artificial intelligence (AI) systems. It is often cited as a must-have property especially in high-stake applications. This survey article investigates AI accountability from different key perspectives for its effective operationalization. Major approaches for achieving accountability are reviewed and typical factors affecting accountability are identified.
dc.language	English
dc.publisher	IEEE COMPUTER SOC
dc.relation.ispartof	Computer
dc.relation.isbasedon	10.1109/MC.2023.3238390
dc.rights	info:eu-repo/semantics/embargoedAccess
dc.subject	08 Information and Computing Sciences
dc.subject.classification	Software Engineering
dc.subject.classification	46 Information and computing sciences
dc.title	AI Accountability: Approaches, Affecting Factors, and Challenges
dc.type	Journal Article
utslib.citation.volume	56
utslib.for	08 Information and Computing Sciences
pubs.organisational-group	University of Technology Sydney
pubs.organisational-group	University of Technology Sydney/Faculty of Engineering and Information Technology
utslib.copyright.status	embargoed	*
utslib.copyright.embargo	2025-04-10T00:00:00+1000Z
dc.date.updated	2024-03-26T04:25:11Z
pubs.issue	4
pubs.publication-status	Published
pubs.volume	56
utslib.citation.issue	4

Abstract:

Accountability is one of core ethical principles for artificial intelligence (AI) systems. It is often cited as a must-have property especially in high-stake applications. This survey article investigates AI accountability from different key perspectives for its effective operationalization. Major approaches for achieving accountability are reviewed and typical factors affecting accountability are identified.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/177174