Explainable Artificial Intelligence: Objectives, Stakeholders, and Future Research Opportunities

IF 3 3区 管理学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS
Christian Meske, Enrico Bunde, Johannes Schneider, Martin Gersch
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引用次数: 154

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.
可解释的人工智能:目标、利益相关者和未来的研究机会
人工智能(AI)已经渗透到我们个人生活和职业生活的许多领域。在这份研究报告中,我们描述了黑箱人工智能的典型风险,随之而来的对可解释性的需求,以及以前在信息系统研究中对可解释性人工智能(XAI)的研究。此外,我们还讨论了术语XAI的起源、广义的XAI目标和利益相关者群体,以及个性化解释的质量标准。最后,对XAI的未来研究进行了展望。
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来源期刊
Information Systems Management
Information Systems Management 工程技术-计算机:信息系统
CiteScore
14.60
自引率
1.60%
发文量
20
审稿时长
>12 weeks
期刊介绍: Information Systems Management (ISM) is the on-going exchange of academic research, best practices, and insights based on managerial experience. The journal’s goal is to advance the practice of information systems management through this exchange. To meet this goal, ISM features themed papers examining a particular topic. In addition to themed papers, the journal regularly publishes on the following topics in IS management. Achieving Strategic IT Alignment and Capabilities IT Governance CIO and IT Leadership Roles IT Sourcing Planning and Managing an Enterprise Infrastructure IT Security Selecting and Delivering Application Solutions Portfolio Management Managing Complex IT Projects E-Business Technologies Supporting Knowledge Work The target readership includes both academics and practitioners. Hence, submissions integrating research and practice, and providing implications for both, are encouraged.
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