保全颜面:调查面部识别审计的伦理问题

Inioluwa Deborah Raji, Timnit Gebru, Margaret Mitchell, Joy Buolamwini, Joonseok Lee, Emily L. Denton
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引用次数: 189

摘要

尽管对于揭示有偏见的表现至关重要,但善意的算法审计尝试可能会产生损害这些措施旨在保护的人群的影响。在审计面部识别等生物识别系统时,这种担忧更为突出,因为这些系统的数据很敏感,而且技术经常被用于道德上有问题的方式。在审计商业面部处理技术的特殊情况下,我们展示了一组五个道德问题,强调了审计师需要意识到的额外设计考虑和道德紧张关系,以避免加剧或补充被审计系统传播的危害。我们进一步提供了这些问题的具体说明,并通过反思这些问题对算法审计的作用和它们揭示的基本产品限制的意义来结束。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Saving Face: Investigating the Ethical Concerns of Facial Recognition Auditing
Although essential to revealing biased performance, well intentioned attempts at algorithmic auditing can have effects that may harm the very populations these measures are meant to protect. This concern is even more salient while auditing biometric systems such as facial recognition, where the data is sensitive and the technology is often used in ethically questionable manners. We demonstrate a set of fiveethical concerns in the particular case of auditing commercial facial processing technology, highlighting additional design considerations and ethical tensions the auditor needs to be aware of so as not exacerbate or complement the harms propagated by the audited system. We go further to provide tangible illustrations of these concerns, and conclude by reflecting on what these concerns mean for the role of the algorithmic audit and the fundamental product limitations they reveal.
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