THE SCHOOL OF INDUSTRIAL DESIGN 

GEORGIA INSTITUTE OF TECHNOLOGY 

Under the provisions of the regulations for the degree 

MASTER OF INDUSTRIAL DESIGN

on

Tuesday, Dec 2nd  2022

9:00 a.m. – 11:00 a.m.

online

 https://teams.microsoft.com/l/meetup-join/19%3ameeting_N2Y3N2Y2ZGQtYTY4OS00NTIyLTg3ZDYtZWM3NmVkNTE2ZmNj%40thread.v2/0?context=%7b%22Tid%22%3a%22482198bb-ae7b-4b25-8b7a-6d7f32faa083%22%2c%22Oid%22%3a%222df462a2-f246-400a-9678-cf03d53b8c97%22%7d

Xingyu Li

will present a thesis defense entitled,

“Design and Evaluation of an online interface with AI Emotion suggestions to support social communication”

Advisor:

Dr. Harmon, Stephen W  – School of Industrial Design

Committee:

Prof. Noura Howell – School of Digital Media

Prof. Sang-won Leigh – School of Industrial Design

Faculty and students are invited to attend this presentation.

Abstract

Advances in artificial intelligence (AI) have provided great opportunities for participating in social communication and carrying out empathic conversations through collaborating with people. However, AI with low accuracy doesn’t work well in social scenarios as the effect must be studied in the context it is being expressed, and observed emotion signals should not replace internally reported effects for affective computing applications. Perhaps there will be a high-accuracy Emotion AI with an improved algorithm fitting complex social scenarios in the near future. To understand the effects of Emotion AI (artificial intelligence that learns to interpret and respond to human emotions) on people's interpersonal confidence, social experience, and emotion recognition ability, we designed a prototype, Adverb, providing real-time detailed emotion types in the online meeting software.

This thesis study aims to investigate the following questions: How does emotional AI communicate with humans? What’s the impact of AI information displays advice on users' social intelligence and interpersonal confidence? What’s the impact of AI information displays advice on users' emotion recognition ability? We conducted the user study employing both qualitative and quantitive methods, and thirty participants join the survey and interview. This thesis is concluded with a discussion on limitations and future work of human-ai collaboration.