  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.
Along the way, key recommendations are made for responsible AER. 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).
