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 five ethical 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.

中文翻译：

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面子：人脸识别审计的伦理问题调查

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可能损害这些措施旨在保护的人群的影响。在审核诸如面部识别之类的生物识别系统时，这种担忧更加突出，其中数据是敏感的，并且该技术经常以道德上有问题的方式使用。我们在审计商业面部处理技术的特定案例中展示了一组五个道德问题，强调了审计师需要注意的其他设计考虑因素和道德紧张局势，以免加剧或补充被审计系统传播的危害。我们进一步提供这些问题的切实例证，