论文标题
储蓄面：调查面部识别审核的道德问题
Saving Face: Investigating the Ethical Concerns of Facial Recognition Auditing
论文作者
论文摘要
尽管对于揭示有偏见的性能至关重要，但有意进行算法审计的尝试可能会造成这些措施旨在保护的人群的影响。在审核生物识别系统（例如面部识别）时，这种关注更加显着，因为数据是敏感的，并且该技术通常以道德上可疑的方式使用。在审核商业面部处理技术的特定情况下，我们展示了一组五个道德问题，突出了审计师需要意识到的其他设计注意事项和道德紧张局势，因此不会加剧或补充审计系统传播的危害。我们进一步提供了有关这些问题的切实插图，并通过反思这些关注对算法审计的作用意味着什么以及它们所揭示的基本产品限制意味着什么。
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.
