剖析算法偏见引发情绪反应的三类根源，提出应对策略
The Technology of Outrage: Bias in Artificial Intelligence
- 识别出认知、道德、政治三类对算法偏见的过激反应
- 指出当前术语混乱导致讨论偏离本质
- 建议澄清概念、改进审计方法、内置公平性能力
人工智能与机器学习正越来越多地替代人类决策。过去人们常认为机器比人更公正、无偏见，但证据表明并非如此。本文首先考察‘算法可替代人类’和‘算法不会偏见’两个假设，发现将其视为公理会迅速导致荒谬结论。由此出发，深入分析‘偏见’一词在使用中的模糊性，诊断出三种情绪反应：认知型、道德型与政治型的愤怒。接着提出三条可行的应对路径：澄清偏见相关语言、开发新型智能系统审计方法、在系统中嵌入特定能力以缓解偏见。最后总结关于算法偏见讨论的伦理启示，该启示或可推广至人工智能其他领域。
原文摘要 · Abstract (English)
Artificial intelligence and machine learning are increasingly used to offload decision making from people. In the past, one of the rationales for this replacement was that machines, unlike people, can be fair and unbiased. Evidence suggests otherwise. We begin by entertaining the ideas that algorithms can replace people and that algorithms cannot be biased. Taken as axioms, these statements quickly lead to absurdity. Spurred on by this result, we investigate the slogans more closely and identify equivocation surrounding the word 'bias.' We diagnose three forms of outrage-intellectual, moral, and political-that are at play when people react emotionally to algorithmic bias. Then we suggest three practical approaches to addressing bias that the AI community could take, which include clarifying the language around bias, developing new auditing methods for intelligent systems, and building certain capabilities into these systems. We conclude by offering a moral regarding the conversations about algorithmic bias that may transfer to other areas of artificial intelligence.
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