论文标题
适用于生物识别和面部法医算法的可解释AI的四个原理
Four Principles of Explainable AI as Applied to Biometrics and Facial Forensic Algorithms
论文作者
论文摘要
传统上，自动面部识别和生物识别技术的研究人员致力于开发准确的算法。随着该技术被整合到运营系统中，询问了工程师和科学家，这些系统是否符合社会规范？这种探究线的起源是人工智能（AI）系统的“信任”。在本文中，我们专注于适应可解释的AI面对识别和生物识别技术，并提出了可解释的AI原理，以面对识别和生物识别。这些原则用$ \ it {四} $案例研究来说明，这表明了开发可以产生解释的算法的挑战和问题。
Traditionally, researchers in automatic face recognition and biometric technologies have focused on developing accurate algorithms. With this technology being integrated into operational systems, engineers and scientists are being asked, do these systems meet societal norms? The origin of this line of inquiry is `trust' of artificial intelligence (AI) systems. In this paper, we concentrate on adapting explainable AI to face recognition and biometrics, and we present four principles of explainable AI to face recognition and biometrics. The principles are illustrated by $\it{four}$ case studies, which show the challenges and issues in developing algorithms that can produce explanations.
