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    <titleInfo>
        <title>Ethics Sheet for Automatic Emotion Recognition and Sentiment Analysis</title>
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        <namePart type="given">Saif</namePart>
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    <abstract>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 article, I have synthesized and organized information from AI Ethics and Emotion Recognition literature to present fifty ethical considerations relevant to AER. Notably, this ethics 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. Along the way, key recommendations are made for responsible AER. The objective of the ethics 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 ethics sheet acts as a useful introductory document on emotion recognition (complementing survey articles).</abstract>
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    <identifier type="doi">10.1162/coli_a_00433</identifier>
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        <date>2022-06</date>
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%0 Journal Article
%T Ethics Sheet for Automatic Emotion Recognition and Sentiment Analysis
%A Mohammad, Saif M.
%J Computational Linguistics
%D 2022
%8 June
%V 48
%N 2
%I MIT Press
%C Cambridge, MA
%F mohammad-2022-ethics-sheet
%X 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 article, I have synthesized and organized information from AI Ethics and Emotion Recognition literature to present fifty ethical considerations relevant to AER. Notably, this ethics 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. Along the way, key recommendations are made for responsible AER. The objective of the ethics 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 ethics sheet acts as a useful introductory document on emotion recognition (complementing survey articles).
%R 10.1162/coli_a_00433
%U https://aclanthology.org/2022.cl-2.1
%U https://doi.org/10.1162/coli_a_00433
%P 239-278

Markdown (Informal)

[Ethics Sheet for Automatic Emotion Recognition and Sentiment Analysis](https://aclanthology.org/2022.cl-2.1) (Mohammad, CL 2022)

• Ethics Sheet for Automatic Emotion Recognition and Sentiment Analysis (Mohammad, CL 2022)

ACL

• Saif M. Mohammad. 2022. Ethics Sheet for Automatic Emotion Recognition and Sentiment Analysis. Computational Linguistics, 48(2):239–278.