Explainable artificial intelligence in information systems: A review of the status quo and future research directions

Julia Brasse (), Hanna Rebecca Broder (), Maximilian Förster (), Mathias Klier () and Irina Sigler ()
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Julia Brasse: University of Ulm
Hanna Rebecca Broder: University of Ulm
Maximilian Förster: University of Ulm
Mathias Klier: University of Ulm
Irina Sigler: University of Ulm

Electronic Markets, 2023, vol. 33, issue 1, No 26, 30 pages

Abstract: Abstract The quest to open black box artificial intelligence (AI) systems evolved into an emerging phenomenon of global interest for academia, business, and society and brought about the rise of the research field of explainable artificial intelligence (XAI). With its pluralistic view, information systems (IS) research is predestined to contribute to this emerging field; thus, it is not surprising that the number of publications on XAI has been rising significantly in IS research. This paper aims to provide a comprehensive overview of XAI research in IS in general and electronic markets in particular using a structured literature review. Based on a literature search resulting in 180 research papers, this work provides an overview of the most receptive outlets, the development of the academic discussion, and the most relevant underlying concepts and methodologies. Furthermore, eight research areas with varying maturity in electronic markets are carved out. Finally, directions for a research agenda of XAI in IS are presented.

Keywords: Explainable artificial intelligence; Explainable machine learning; Comprehensible artificial intelligence; Comprehensible machine learning; Literature review (search for similar items in EconPapers)
JEL-codes: M10 (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (2)

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DOI: 10.1007/s12525-023-00644-5

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