Thinking responsibly about responsible AI and ‘the dark side’ of AI

大裂谷 意外后果 订单(交换) 集合(抽象数据类型) 数据科学 知识管理 计算机科学 业务 社会学 人工智能 认识论 物理 天文 财务 哲学 程序设计语言
作者
Patrick Mikalef,Kieran Conboy,Jenny Eriksson Lundström,Aleš Popovič
出处
期刊:European Journal of Information Systems [Palgrave Macmillan]
卷期号:31 (3): 257-268 被引量:328
标识
DOI:10.1080/0960085x.2022.2026621
摘要

Artificial Intelligence (AI) has been argued to offer a myriad of improvements in how we work and live. The notion of AI comprises a wide-ranging set of technologies that allow individuals and organizations to integrate and analyze data and use that insight to improve or automate decision-making. While most attention has been placed on the positive aspects companies realize by the adoption by the adoption and use of AI, there is a growing concern around the negative and unintended consequences of such technologies. In this special issue we have made a call for research papers that help us explore the dark side of AI use. By adopting a dark side lens, we aimed to expand our understanding of how AI should be implemented in practice, and how to minimize or avoid negative outcomes. In this editorial, we build on the notion of responsible AI, to highlight the different ways in which AI can potentially produce unintended consequences, as well as to suggest alternative paths future IS research can follow to improve our knowledge about how to mitigate such occurrences. We further expand on dark side theorizing in order to uncover hidden assumptions of current literature as well as to propose other prominent themes that can guide future IS research on AI adoption and use.
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