The Deficiency of “Redline/Greenline” Approach to Risk Management in AI Applications

A. Kuleshov, A. Ignatiev, A. Abramova
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Abstract

Expanding application of technologies classified as AI draws public attention to associated risks and effective measures for risk mitigation. Policy makers in most countries are currently looking for effective approaches to securing the public interest against AI-related risks and unforeseen consequences of widening AI use. In this connection, there is widespread talk of defining “red” and “green” areas for AI technologies, frequently leading to calls to draw “red lines” and “green lines” for technological innovation. The authors draw on the analysis of AI related risks in a number of international fora and question the efficacy of this “redline/greenline” approach in terms of making the benefits of AI available in the society, while not impeding innovation and technological progress. The authors propose that a more nuanced approach is required, which could involve certification of AI system in sensitive applications, or could apply codified ethical principles to derive specific rules for AI use dependent on the risks created by AI in a particular application.
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人工智能应用中“红线/绿线”风险管理方法的不足
扩大被列为人工智能的技术的应用使公众注意到相关的风险和减轻风险的有效措施。大多数国家的政策制定者目前正在寻找有效的方法,以确保公众利益免受人工智能相关风险和扩大人工智能使用带来的不可预见后果的影响。在这方面,人们普遍谈论为人工智能技术划定“红色”和“绿色”区域,经常导致人们呼吁为技术创新划定“红线”和“绿线”。作者借鉴了一些国际论坛对人工智能相关风险的分析,并质疑这种“红线/绿线”方法的有效性,即在不阻碍创新和技术进步的情况下,使人工智能的好处在社会中可用。作者提出,需要一种更细致入微的方法,这可能涉及对敏感应用中的人工智能系统进行认证,或者可以应用编纂的道德原则,根据人工智能在特定应用中产生的风险,推导出人工智能使用的具体规则。
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