Reviewing the Need for Explainable Artificial Intelligence (xAI)

Date
2021-01-05
Authors
Gerlings, Julie
Shollo, Arisa
Constantiou, Ioanna
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1284
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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.
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Explainable Artificial Intelligence (XAI), explainable ai, machine learning, socio-technical, stakeholders, xai
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10 pages
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Related To
Proceedings of the 54th Hawaii International Conference on System Sciences
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Attribution-NonCommercial-NoDerivatives 4.0 International
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