Reviewing the Need for Explainable Artificial Intelligence (xAI)

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Abstract

The diffusion of artificial intelligence (AI) applications in organizations and society has fueled research on explaining AI decisions. The explainable AI (xAI) field is rapidly expanding with numerous ways of extracting information and visualizing the output of AI technologies (e.g. deep neural networks). Yet, we have a limited understanding of how xAI research addresses the need for explainable AI. We conduct a systematic review of xAI literature on the topic and identify four thematic debates central to how xAI addresses the black-box problem. Based on this critical analysis of the xAI scholarship we synthesize the findings into a future research agenda to further the xAI body of knowledge.
OriginalsprogEngelsk
TitelProceedings of the 54th Hawaii International Conference on System Sciences
Antal sider10
UdgivelsesstedHonolulu
ForlagHawaii International Conference on System Sciences (HICSS)
Publikationsdato2021
Sider1284-1293
ISBN (Elektronisk)9780998133140
DOI
StatusUdgivet - 2021
BegivenhedThe 54th Hawaii International Conference on System Sciences. HICSS 2021 - Online, Virtual, Online, USA
Varighed: 5 jan. 20218 jan. 2021
Konferencens nummer: 54
https://www.insna.org/events/54th-hawaii-international-conference-on-system-sciences-hicss

Konference

KonferenceThe 54th Hawaii International Conference on System Sciences. HICSS 2021
Nummer54
LokationOnline
Land/OmrådeUSA
ByVirtual, Online
Periode05/01/202108/01/2021
SponsorThe Nordic Sociological Association
Internetadresse
NavnProceedings of the Annual Hawaii International Conference on System Sciences
ISSN1060-3425

Citationsformater