Guidelines for Assessing and Minimizing Risks of Emotion Recognition Applications - Hernandez, Javier; Lovejoy, Josh; McDuff, Daniel; Suh, Jina; O'Brien, Tim; Sethumadhavan, Arathi; Greene, Gretchen; Picard, Rosalind; Czerwinski, Mary (International Conference on Affective Computing & Intelligent Interaction (ACII 2021), 2021)
Society has witnessed a rapid increase in the adoption of commercial uses of emotion recognition. Tools that were traditionally used by domain experts are now being used by individuals who are often unaware of the technology's limitations and may use them in potentially harmful settings. The change in scale and agency, paired with gaps in regulation, urge the research community to rethink how we design, position, implement and ultimately deploy emotion recognition to anticipate and minimize potential risks. To help understand the current ecosystem of applied emotion recognition, this work provides an overview of some of the most frequent commercial applications and identifies some of the potential sources of harm. Informed by these, we then propose 12 guidelines for systematically assessing and reducing the risks presented by emotion recognition applications. These guidelines can help identify potential misuses and inform future deployments of emotion recognition.