拯救人脸识别:人脸识别审计的伦理问题研究(Computers and Society)
- 2020 年 1 月 8 日
- 筆記
尽管披露有偏见的绩效是必要的,但出于好意的算法审计尝试,可能会对这些措施旨在保护的人群造成伤害。在审核面部识别等生物识别系统时,这种担忧甚至更为突出。在这些系统中,数据是敏感的,而且该技术常常被用于道德上出现问题的行为。我们在审计商业面部处理技术的特定案例中展示了五种伦理担忧,强调了审计师需要意识到的额外设计考虑和伦理紧张,以避免加剧或补充被审计系统所传播的危害。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所揭示的基本产品限制的意义来得出结论。
原文标题:Computers and Society: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 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.
原文作者:Inioluwa Deborah Raji,Timnit Gebru,Margaret Mitchell,Joy Buolamwini,Joonseok Lee,Emily Denton
原文地址:https://arxiv.org/abs/2001.00964