Principles alone cannot guarantee ethical AI
Principles alone cannot guarantee ethical AI
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DOI：
10.1038/s42256-019-0114-4
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发表时间：
2019-11-01
影响因子：
23.8
通讯作者：
Mittelstadt, Brent
中科院分区：
文献类型：
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作者：
Mittelstadt, Brent
人工智能(AI)伦理现在是学术界和政策界讨论的一个全球性话题。至少有84项公私倡议发表了声明，描述了指导人工智能道德发展、部署和治理的高级原则、价值观和其他原则。根据最近的荟萃分析，人工智能伦理似乎集中在一套原则上，这些原则与医学伦理的四项经典原则非常相似。尽管与医学伦理原则的联系赋予了人工智能伦理的原则性方法最初的可信度，但有理由担心其未来对人工智能发展和治理的影响。医学和人工智能发展之间存在显著差异，这表明后者的原则性方法可能无法获得与前者相比的成功。与医学相比，人工智能的发展缺乏(1)共同目标和受托责任，(2)专业历史和规范，(3)将原则转化为实践的成熟方法，以及(4)强大的法律和专业问责机制。这些分歧表明，我们还不应该庆祝围绕隐藏着严重政治和规范分歧的高级别原则达成的共识。人工智能伦理倡议似乎集中在一套原则上，这些原则与医学伦理的四个经典原则非常相似。尽管如此，Brent Mittelstadt强调了医疗实践和人工智能开发之间的重要差异，这些差异表明原则性方法可能不适用于人工智能。
Artificial intelligence (AI) ethics is now a global topic of discussion in academic and policy circles. At least 84 public-private initiatives have produced statements describing high-level principles, values and other tenets to guide the ethical development, deployment and governance of AI. According to recent meta-analyses, AI ethics has seemingly converged on a set of principles that closely resemble the four classic principles of medical ethics. Despite the initial credibility granted to a principled approach to AI ethics by the connection to principles in medical ethics, there are reasons to be concerned about its future impact on AI development and governance. Significant differences exist between medicine and AI development that suggest a principled approach for the latter may not enjoy success comparable to the former. Compared to medicine, AI development lacks (1) common aims and fiduciary duties, (2) professional history and norms, (3) proven methods to translate principles into practice, and (4) robust legal and professional accountability mechanisms. These differences suggest we should not yet celebrate consensus around high-level principles that hide deep political and normative disagreement. AI ethics initiatives have seemingly converged on a set of principles that closely resemble the four classic principles of medical ethics. Despite this, Brent Mittelstadt highlights important differences between medical practice and AI development that suggest a principled approach may not work in the case of AI.