Exploring the promise and peril of emotion AI, designing for emotional meaning-making with data, imagining an affirmative biopolitics with data

Abstract

Emotion AI, which predicts psychological characteristics from data, offers potentially transformative benefits for societal well-being, productivity, and security. Drawing on increasingly available biodata-data about people’s bodies and behaviors, such as video, audio, or heart rate-emotion AI predicts emotions, stress, focus, and other characteristics. Emotion AI increasingly informs sensitive decisions in many varied contexts, from social media to online education, online job interviews, or security surveillance systems and criminal investigations.

A key challenge to emotion AI is that algorithmic ways of modeling emotion differ fundamentally from human ways of understanding emotion, making emotion AI predictions difficult to meaningfully interpret and apply in real-world contexts. In addition, even people aware of widespread video surveillance may be unaware that an additional layer of algorithmic surveillance using emotion AI is making sensitive predictions about their inner psychology from video of their facial expressions, leading to privacy and civil liberties risks.

My design research explores both the promise and peril of emotion AI, and contributes design tactics to more effectively support social, embodied, and emotional meaning-making with data. Combining building custom biosensing technologies and realtime data displays with concepts from the arts and humanities, my work explores, how might we imagine a more affirmative biopolitics with data?