设计一个增强的企业风险管理系统来降低人工智能应用的伦理风险

IF 4.6 3区 管理学 Q1 BUSINESS
Quintin P. McGrath;Alan R. Hevner;Gert-Jan de Vreede
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引用次数: 0

摘要

在商业应用程序中引入人工智能(AI)功能提供了巨大的好处,但要求组织管理关键的人工智能道德风险。我们调查了一系列大型组织对企业风险管理(ERM)系统的使用,以预测和减轻人工智能的道德风险。目前的ERM系统存在四个严重缺陷:人工智能伦理原则不能有效地转化为道德实践;需要实时监控人工智能伦理风险;ERM系统强调的是经济风险,而非伦理风险;当发现道德风险时,没有现成的解决方案可以补救。为了解决这些差距,我们提出了一种积极主动的方法,通过扩展当前ERM系统的功能来管理道德风险。一个增强的ERM系统框架由主题专家焦点小组设计和评估。我们总结了观察结果和未来的研究方向,即随着组织普遍使用人工智能驱动的业务应用程序,需要更积极的亲道德管理监督。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Designing an Enhanced Enterprise Risk Management System to Mitigate Ethical Risks of Artificial Intelligence Applications
The introduction of artificial intelligence (AI) capabilities in business applications provides substantial benefits but requires organizations to manage critical AI ethical risks. We survey a range of large organizations on their use of enterprise risk management (ERM) systems to predict and mitigate the ethical risks of AI. Four serious gaps in current ERM systems are identified: AI ethical principles do not translate effectively to ethical practices; real-time monitoring of AI ethical risks is needed; ERM systems emphasize economic, not ethical risks; and when ethical risks are identified, no ready solutions are available for remedy. To address these gaps, we propose a proactive approach to managing ethical risks by extending the capabilities of current ERM systems. An enhanced ERM system framework is designed and evaluated by subject matter expert focus groups. We conclude with observations and future research directions on the need for more aggressive proethical management oversight as organizations move to ubiquitous use of AI-driven business applications.
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来源期刊
IEEE Transactions on Engineering Management
IEEE Transactions on Engineering Management 管理科学-工程:工业
CiteScore
10.30
自引率
19.00%
发文量
604
审稿时长
5.3 months
期刊介绍: Management of technical functions such as research, development, and engineering in industry, government, university, and other settings. Emphasis is on studies carried on within an organization to help in decision making or policy formation for RD&E.
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