Explainable Artificial Intelligence: Objectives, Stakeholders, and Future Research Opportunities. Issue 1 (2nd January 2022)

• Record Type: Journal Article
• Authors: Meske, Christian; Bunde, Enrico; Schneider, Johannes; Gersch, Martin
• Is Part Of: Information systems management. Volume 39:Issue 1(2022)
• Page Start: 53
• Page End: 63
• Publication Date: 2022-01-02
• Subjects: Artificial Intelligence -- explainability -- accountability -- transparency -- trust -- managing AI; Management information systems -- Periodicals; Information resources management -- Periodicals; 658.403801105
• DOI: 10.1080/10580530.2020.1849465
• Languages: English
• ISSNs: 1058-0530

Abstract

ABSTRACT: Artificial Intelligence (AI) has diffused into many areas of our private and professional life. In this research note, we describe exemplary risks of black-box AI, the consequent need for explainability, and previous research on Explainable AI (XAI) in information systems research. Moreover, we discuss the origin of the term XAI, generalized XAI objectives, and stakeholder groups, as well as quality criteria of personalized explanations. We conclude with an outlook to future research on XAI.