Designing AI-based Conversational Agent for Diabetes Care in a Multilingual Context

Authors

Thuy-Trinh Nguyen, ReML Research GroupFollow
Kellie Sim, ReML Research GroupFollow
Anthony To Yiu Kuen, University of GlasgowFollow
Ronald R. O’donnell, Arizona State UniversityFollow
Suan Tee Lim, National University Health SystemFollow
Wenru Wang, National University of SingaporeFollow
Hoang D. Nguyen, University of GlasgowFollow

Paper Type

FP

Paper Number

308

Abstract

Conversational agents (CAs) represent an emerging research field in health information systems, where there are great potentials in empowering patients with timely information and natural language interfaces. Nevertheless, there have been limited attempts in establishing prescriptive knowledge on designing CAs in the healthcare domain in general, and diabetes care specifically. In this paper, we conducted a Design Science Research project and proposed three design principles for designing health-related CAs that embark on artificial intelligence (AI) to address the limitations of existing solutions. Further, we instantiated the proposed design and developed AMANDA - an AI-based multilingual CA in diabetes care with state-of-theart technologies for natural-sounding localised accent. We employed mean opinion scores and system usability scale to evaluate AMANDA’s speech quality and usability, respectively. This paper provides practitioners with a blueprint for designing CAs in diabetes care with concrete design guidelines that can be extended into other healthcare domains.

Recommended Citation

Nguyen, Thuy-Trinh; Sim, Kellie; Kuen, Anthony To Yiu; O’donnell, Ronald R.; Lim, Suan Tee; Wang, Wenru; and Nguyen, Hoang D., "Designing AI-based Conversational Agent for Diabetes Care in a Multilingual Context" (2021). PACIS 2021 Proceedings. 96.
https://aisel.aisnet.org/pacis2021/96