Title: “I can help with that” - Designing flexible, personalized and proactive conversational agents for older adults.

Tamara Zubatiy

Ph.D. Student in HCC

School of Interactive Computing 

Georgia Institute of Technology  

Date: March 6, 2024

Time:  10 AM - 1 pm 

Location:  CODA Home Park Room

Virtual link

Committee 

Dr. Elizabeth Mynatt - School of Interactive Computing, Georgia Institute of Technology & Khoury College of Computer Sciences, Northeastern University

Dr. Thomas Ploetz- School of Interactive Computing, Georgia Institute of Technology

Dr. Larry Heck - School of Interactive Computing & School of Electrical and Computer Engineering, Georgia Institute of Technology

Dr. Agata Rozga- School of Interactive Computing, Georgia Institute of Technology

Dr. Annie Anton- School of Interactive Computing, Georgia Institute of Technology

Dr. Kayci Vickers -  Department of Neurology (Neuropsychology Section), Emory University School of Medicine

Abstract 

Observing how older adults interact with commercial conversational agents reveals limitations in existing CA systems and contributes to design guidelines for future systems to overcome these limitations. Despite widespread adoption and study of pre-large-language model conversational agents (CAs), they are still error prone and frustrating due to lack of proactivity, personalization over time and inflexibility of input. Importantly, while they stand to greatly benefit older adults, through on-demand support that doesn’t require interacting with a touch screen, limited research has been done to explore how older adults use CAs over time at home. To contribute to this opportunity at the intersection of technology and health, my research combines user insights gleaned from multiple longitudinal deployments of commercial CAs into the homes of older adults, a battery of qualitative & quantitative statistical analyses, and an understanding of optimal training approaches designed specifically for older adults experiencing age related decline. My research contextualizes the usage patterns & frustrations of older adults into existing literature on CA usage by other populations, reveals clear impacts of cognitive status on CA usage by older adults and points to the power of training to increase CA interaction rigor. It also highlights three specific limitations in existing commercial CAs and points to tradeoffs that future systems, likely powered in part by large language models, will need to address in order to overcome them. This work is interwoven with a privacy-focused component including privacy impact assessments (PIA) two existing and one developing CA systems. Each PIA weighs the impact of these three tradeoffs on future CAs and provides actionable recommendations for privacy preserving future systems that still deliver on the personalized and proactive promise of future CAs.