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Ethics Sheet for Automatic Emotion Recognition and Sentiment Analysis
arXiv - CS - Computation and Language Pub Date : 2021-09-17 , DOI: arxiv-2109.08256 Saif M. Mohammad
arXiv - CS - Computation and Language Pub Date : 2021-09-17 , DOI: arxiv-2109.08256 Saif M. Mohammad
The importance and pervasiveness of emotions in our lives makes affective
computing a tremendously important and vibrant line of work. Systems for
automatic emotion recognition (AER) and sentiment analysis can be facilitators
of enormous progress (e.g., in improving public health and commerce) but also
enablers of great harm (e.g., for suppressing dissidents and manipulating
voters). Thus, it is imperative that the affective computing community actively
engage with the ethical ramifications of their creations. In this paper, I have
synthesized and organized information from AI Ethics and Emotion Recognition
literature to present fifty ethical considerations relevant to AER. Notably,
the sheet fleshes out assumptions hidden in how AER is commonly framed, and in
the choices often made regarding the data, method, and evaluation. Special
attention is paid to the implications of AER on privacy and social groups. The
objective of the sheet is to facilitate and encourage more thoughtfulness on
why to automate, how to automate, and how to judge success well before the
building of AER systems. Additionally, the sheet acts as a useful introductory
document on emotion recognition (complementing survey articles).
中文翻译:
自动情绪识别和情绪分析的道德表
情感在我们生活中的重要性和普遍性使情感计算成为一项极其重要和充满活力的工作。用于自动情绪识别 (AER) 和情绪分析的系统可以促进巨大进步(例如,在改善公共卫生和商业方面),但也会带来巨大危害(例如,压制持不同政见者和操纵选民)。因此,情感计算社区必须积极参与其创作的伦理后果。在本文中,我综合并整理了来自 AI 伦理和情感识别文献的信息,以展示与 AER 相关的 50 个伦理考虑。值得注意的是,该表充实了隐藏在 AER 通常如何构建以及在有关数据、方法和评估的选择中隐藏的假设。特别注意 AER 对隐私和社会群体的影响。该表的目的是促进和鼓励在构建 AER 系统之前更深入地思考为什么要自动化、如何自动化以及如何判断成功。此外,该表还可以作为情绪识别的有用介绍性文件(补充调查文章)。
更新日期:2021-09-20
中文翻译:
自动情绪识别和情绪分析的道德表
情感在我们生活中的重要性和普遍性使情感计算成为一项极其重要和充满活力的工作。用于自动情绪识别 (AER) 和情绪分析的系统可以促进巨大进步(例如,在改善公共卫生和商业方面),但也会带来巨大危害(例如,压制持不同政见者和操纵选民)。因此,情感计算社区必须积极参与其创作的伦理后果。在本文中,我综合并整理了来自 AI 伦理和情感识别文献的信息,以展示与 AER 相关的 50 个伦理考虑。值得注意的是,该表充实了隐藏在 AER 通常如何构建以及在有关数据、方法和评估的选择中隐藏的假设。特别注意 AER 对隐私和社会群体的影响。该表的目的是促进和鼓励在构建 AER 系统之前更深入地思考为什么要自动化、如何自动化以及如何判断成功。此外,该表还可以作为情绪识别的有用介绍性文件(补充调查文章)。