人工智能系统问责制的现在和未来:文献计量学分析

IF 8.3 3区 管理学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS
Sebastian Clemens Bartsch, Long Hoang Nguyen, Jan-Hendrik Schmidt, Guangyu Du, Martin Adam, Alexander Benlian, Ali Sunyaev
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引用次数: 0

摘要

人工智能(AI)系统,特别是生成式人工智能系统,为组织和社会提供了许多机会。随着人工智能系统变得越来越强大,确保其安全和合乎道德的使用需要问责制,要求参与者解释和证明任何意外行为和结果。认识到对人工智能系统问责制的重要性,包括信息系统(IS)在内的各个研究学科的研究已经开始调查这一主题。然而,在多个研究学科中,人工智能系统的责任似乎是模糊的。因此,我们对5809份出版物进行了文献计量分析,以汇总和综合现有研究,以更好地理解人工智能系统的问责制。我们的分析将信息系统研究与相关的非信息系统学科区分开来,这些研究由科学网站“计算机科学、信息系统”类别定义。这种差异突出了信息系统研究独特的社会技术贡献,同时确保和整合来自更广泛的学术领域对人工智能系统问责制的见解。在这些发现的基础上,我们得出了研究命题,以指导未来对人工智能系统问责制的研究。最后,我们将这些研究命题应用于生成式人工智能系统的背景下,并得出一个研究议程,以指导未来对这一新兴主题的研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Present and Future of Accountability for AI Systems: A Bibliometric Analysis

Artificial intelligence (AI) systems, particularly generative AI systems, present numerous opportunities for organizations and society. As AI systems become more powerful, ensuring their safe and ethical use necessitates accountability, requiring actors to explain and justify any unintended behavior and outcomes. Recognizing the significance of accountability for AI systems, research from various research disciplines, including information systems (IS), has started investigating the topic. However, accountability for AI systems appears ambiguous across multiple research disciplines. Therefore, we conduct a bibliometric analysis with 5,809 publications to aggregate and synthesize existing research to better understand accountability for AI systems. Our analysis distinguishes IS research, defined by the Web of Science “Computer Science, Information Systems” category, from related non-IS disciplines. This differentiation highlights IS research’s unique socio-technical contribution while ensuring and integrating insights from across the broader academic landscape on accountability for AI systems. Building on these findings, we derive research propositions to lead future research on accountability for AI systems. Finally, we apply these research propositions to the context of generative AI systems and derive a research agenda to guide future research on this emerging topic.

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来源期刊
Information Systems Frontiers
Information Systems Frontiers 工程技术-计算机:理论方法
CiteScore
13.30
自引率
18.60%
发文量
127
审稿时长
9 months
期刊介绍: The interdisciplinary interfaces of Information Systems (IS) are fast emerging as defining areas of research and development in IS. These developments are largely due to the transformation of Information Technology (IT) towards networked worlds and its effects on global communications and economies. While these developments are shaping the way information is used in all forms of human enterprise, they are also setting the tone and pace of information systems of the future. The major advances in IT such as client/server systems, the Internet and the desktop/multimedia computing revolution, for example, have led to numerous important vistas of research and development with considerable practical impact and academic significance. While the industry seeks to develop high performance IS/IT solutions to a variety of contemporary information support needs, academia looks to extend the reach of IS technology into new application domains. Information Systems Frontiers (ISF) aims to provide a common forum of dissemination of frontline industrial developments of substantial academic value and pioneering academic research of significant practical impact.
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