MindTalker: Navigating the Complexities of AI-Enhanced Social Engagement for People with Early-Stage Dementia

要旨

People living with dementia are at risk of social isolation, and conversational AI agents can potentially support such individuals by reducing their loneliness. In our study, a conversational AI agent, called MindTalker, co-designed with therapists and utilizing the GPT-4 Large Language Model (LLM), was developed to support people with early-stage dementia, allowing them to experience a new type of “social relationship” that could be extended to real life. Eight PwD engaged with MindTalker for one month or even longer, and data was collected from interviews. Our findings emphasized that participants valued the novelty of AI, but sought more consistent, deeper interactions. They desired a personal touch from AI, while stressing the irreplaceable value of human interactions. The findings underscore the complexities of AI engagement dynamics, where participants commented on the artificial nature of AI, highlighting important insights into the future design of conversational AI for this population.

著者
Anna Xygkou
University of Kent, Canterbury, United Kingdom
Chee Siang Ang
University of Kent, Canterbury, KENT, United Kingdom
Panote Siriaraya
Kyoto Institute of Technology, Kyoto, Japan
Jonasz Piotr. Kopecki
Adama Mickiewicza w Poznaniu Collegium Maius, Poznań, Poland
Alexandra Covaci
University of Kent, Canterbury, Kent, United Kingdom
Eiman Kanjo
Nottingham Trent University, Nottingham, United Kingdom
Wan-Jou She
Nara institute of Science and Technology, Ikoma City, Nara, Japan
論文URL

https://doi.org/10.1145/3613904.3642538

動画

会議: CHI 2024

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2024.acm.org/)

セッション: Remote Presentations: Highlight on AI

Remote Sessions
14 件の発表
2024-05-13 18:00:00
2024-05-14 02:20:00