  The introduction of artificial intelligence (AI) on visual images for
emotional analysis obliterates the natural subjectivity and contextual
dependence of our facial displays. Emotion AI places itself as an algorithmic
lens on our digital artifacts and real-time interactions, creating the illusion
of a new, objective class of data: our emotional and mental states. Building
upon a rich network of existing public photographs--as well as fresh feeds from
surveillance footage or smart phone cameras--these emotion algorithms require
no additional infrastructure or improvements on image quality. In order to
examine the potential policy and legal remedies for emotion AI as an emerging
technology, we first establish a framework of actors, collection motivations,
time scales, and space considerations that differentiates emotion AI from other
algorithmic lenses. Each of these elements influences available policy
remedies, and should shape continuing discussions on the antecedent conditions
that make emotional AI acceptable or not in particular contexts. Based on our
framework of unique elements, we examine potential available policy remedies to
prevent or remediate harm. Specifically, our paper looks toward the regulatory
role of the Federal Trade Commission in the US, gaps in the EU's General Data
Protection Regulation (GDPR) allowing for emotion data collection, and
precedent set by polygraph technologies in evidentiary and use restrictions set
by law. We also examine the way social norms and adaptations could grow to also
modulate broader use. Given the challenges in controlling the flow of these
data, we call for further research and attention as emotion AI technology
remains poised for adoption.
