Given the increasing prevalence of facial analysis technology, the problem of bias in the tools is now becoming an even greater source of concern. Several studies have highlighted the pervasiveness of such discrimination, and many have sought to address the problem by proposing solutions to mitigate it. Despite this effort, to date, understanding, investigating, and mitigating bias for facial affect analysis remain an understudied problem. In this work we aim to provide a guide by 1) providing an overview of the various definitions of bias and measures of fairness within the field of facial affective signal processing and 2) categorizing the algorithms and techniques that can be used to investigate and mitigate bias in facial affective signal processing. We present the opportunities and limitations within the current body of work, discuss the gathered findings, and propose areas that call for further research.

中文翻译：

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面部情感信号处理中的偏见和公平性漫游指南：概述和技术

鉴于面部分析技术的日益流行，工具中的偏见问题现在正成为更令人担忧的问题。几项研究强调了这种歧视的普遍性，许多研究试图通过提出减轻它的解决方案来解决这个问题。尽管做出了这些努力，但迄今为止，理解、调查和减轻面部情感分析的偏见仍然是一个研究不足的问题。在这项工作中，我们旨在通过以下方式提供指导：1) 概述面部情感信号处理领域内偏见的各种定义和公平性措施，以及 2) 对可用于调查和减轻偏见的算法和技术进行分类在面部情感信号处理中。我们展示了当前工作范围内的机会和局限性，