企业人工智能治理

IF 3 3区管理学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS Information Systems Management Pub Date : 2020-11-20 DOI:10.1080/10580530.2022.2085825

Johannes Schneider, Rene Abraham, Christian Meske, J. Brocke

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引用次数: 26

摘要

摘要尽管人工智能治理在哲学、社会和监管层面进行了深入的讨论，但很少有针对公司的工作。我们通过从文献中推导出一个概念框架来解决这一差距。我们将人工智能治理分解为数据治理、机器学习模型和人工智能系统，沿着谁、什么和如何“被治理”的维度。这种分解使现有治理结构得以演变。新颖的、特定于业务的方面包括测量数据价值和新颖的人工智能治理角色。

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Artificial Intelligence Governance For Businesses

ABSTRACT While artificial intelligence (AI) governance is thoroughly discussed on a philosophical, societal, and regulatory level, few works target companies. We address this gap by deriving a conceptual framework from literature. We decompose AI governance into governance of data, machine learning models, and AI systems along the dimensions of who, what, and how “is governed.” This decomposition enables the evolution of existing governance structures. Novel, business-specific aspects include measuring data value and novel AI governance roles.

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来源期刊

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

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.