揭穿AI决策中'人在回路'的虚假安全，警惕语言包装下的责任逃避
Humanwashing -- It Should Leave You Feeling Dirty
- 用'人机回路'隐喻掩盖真实监督缺失，造成认知误导
- 当前多数系统未实现有效人类监督，存在严重责任真空
- 适合关注AI伦理、透明性与问责机制的研究者阅读
‘人在回路’一词被广泛用于暗示人工智能决策系统的安全性，但这种说法并不成立。尽管在某些场景下该机制合理适用，但如今主流部署的AI决策系统并不符合这些条件。人类对AI决策过程的监督是应对偏见、歧视、虚假信息、操纵、问责与透明度问题的常见提议。然而，对‘人类监督’具体含义的探讨严重不足。本文提出核心问题：使用‘回路’这一隐喻是否有助于理解特定决策情境中所需与达成的实际效果？泛化使用该隐喻会模糊过程与结果，助长‘humanwashing’——一种类似‘绿色洗白’的行为，即作者和评论者通过语言美化系统，以呈现最有利的形象，实则掩盖了监督的实质缺位。
原文摘要 · Abstract (English)
The phrase 'human in the loop' is increasingly used to imply a sense of safety in relation to AI decision systems. It shouldn't. There are contexts where it can be applied appropriately, but these are not in the deployed decision systems we see dominating today. Human oversight of AI decision processes is one of the most popular proposals for addressing concerns, especially about bias, discrimination, misinformation, manipulation, accountability, and transparency. But there is insufficient examination of what human oversight actually means. The question raised in this paper is whether using the metaphor of a loop does anything to assist understanding of what is required and what is achieved in a particular decision context. Indiscriminate use of the loop metaphor obscures both processes and outcomes. It enables 'humanwashing', an activity analogous to 'greenwashing', where writers and commentators use language primarily aimed at putting systems in the best possible light.
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