Informal Embodied Auditing: Exploring Facial Emotion AI (FEAI) through Community Workshops

要旨

Emotion AI (EAI) is increasingly deployed and ethically controversial-motivating a need for greater public understanding, critique, and ethical discussions. Facial Emotion AI (FEAI) is a common type of EAI that infers emotions from facial expressions. We developed Explore-FEAI, an FEAI model and accompanying interactive website that offers open-ended exploration with FEAI firsthand. We designed a workshop wherein participants learn about FEAI using Explore-FEAI and discuss societal implications, partnering with local organizations to host community workshops (N=30). Our findings analyze participants’ growing critical AI literacy through exploring inputs/outputs, mechanistic reasoning, data critiques, sociocultural critiques, ethical concerns, and embodied and material exploration of FEAI. Our discussion offers informal embodied auditing as an approach for critical engagement with AI through embodied and material exploration, as well as reflections on informal auditing for supporting AI literacy, informal auditing for questioning EAI ethics, and expanding participation roles for more holistic EAI training.

著者
Xingyu Li
Georgia Institute of Technology,, Atlanta, Georgia, United States
Alexandra Teixeira Riggs
Georgia Institute of Technology , Atlanta, Georgia, United States
Zhiming Dai
Georgia Institute of Technology, Atlanta, Georgia, United States
Crystal Byrd. Farmer
Decatur Makers, Decatur, Georgia, United States
Kalia G. Morrison
Decatur Makers, Decatur, Georgia, United States
Noura Howell
Georgia Institute of Technology, Atlanta, Georgia, United States

会議: CHI 2026

ACM CHI Conference on Human Factors in Computing Systems

セッション: Affective Agents & Reflective Data

Area 1 + 2 + 3: theatre
7 件の発表
2026-04-14 20:15:00
2026-04-14 21:45:00