TY - GEN
T1 - Exploring the Design of Generative AI in Supporting Music-based Reminiscence for Older Adults
AU - Jin, Yucheng
AU - Cai, Wanling
AU - Chen , Li
AU - Zhang, Yizhe
AU - Doherty, Gavin
AU - Jiang, Tonglin
N1 - This work was supported by China Hong Kong Research Grants Council (RGC) GRF project (RGC/HKBU12201620), and Hong Kong Baptist University IG-FNRA project (RC-FNRA-IG/21-22/SCI/01) and Start-up Grant (RC-STARTUP/21-22/23). This work was also supported, in part, by Science Foundation Ireland grant 13/RC/2094_P2.
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© 2024 Copyright held by the owner/author(s). Publication rights licensed to ACM.
PY - 2024/5/11
Y1 - 2024/5/11
N2 - Music-based reminiscence has the potential to positively impact the psychological well-being of older adults. However, the aging process and physiological changes, such as memory decline and limited verbal communication, may impede the ability of older adults to recall their memories and life experiences. Given the advanced capabilities of generative artificial intelligence (AI) systems, such as generated conversations and images, and their potential to facilitate the reminiscing process, this study aims to explore the design of generative AI to support music-based reminiscence in older adults. This study follows a user-centered design approach incorporating various stages, including detailed interviews with two social workers and two design workshops (involving ten older adults). Our work contributes to an in-depth understanding of older adults’ attitudes toward utilizing generative AI for supporting music-based reminiscence and identifies concrete design considerations for the future design of generative AI to enhance the reminiscence experience of older adults.
AB - Music-based reminiscence has the potential to positively impact the psychological well-being of older adults. However, the aging process and physiological changes, such as memory decline and limited verbal communication, may impede the ability of older adults to recall their memories and life experiences. Given the advanced capabilities of generative artificial intelligence (AI) systems, such as generated conversations and images, and their potential to facilitate the reminiscing process, this study aims to explore the design of generative AI to support music-based reminiscence in older adults. This study follows a user-centered design approach incorporating various stages, including detailed interviews with two social workers and two design workshops (involving ten older adults). Our work contributes to an in-depth understanding of older adults’ attitudes toward utilizing generative AI for supporting music-based reminiscence and identifies concrete design considerations for the future design of generative AI to enhance the reminiscence experience of older adults.
KW - Generative AI
KW - Human-AI Interaction
KW - Music-based Reminiscence
KW - Older Adults
KW - Reminiscence
UR - http://www.scopus.com/inward/record.url?scp=85194833494&partnerID=8YFLogxK
U2 - 10.1145/3613904.3642800
DO - 10.1145/3613904.3642800
M3 - Conference proceeding
SN - 9798400703300
T3 - Conference on Human Factors in Computing Systems - Proceedings
SP - 1
EP - 17
BT - CHI '24: Proceedings of the CHI Conference on Human Factors in Computing Systems
A2 - Mueller, Florian Floyd
A2 - Kyburz, Penny
A2 - Williamson, Julie R.
A2 - Sas, Corina
A2 - Wilson, Max L.
A2 - Dugas, Phoebe Toups
A2 - Shklovski, Irina
PB - Association for Computing Machinery (ACM)
T2 - CHI '24: CHI Conference on Human Factors in Computing Systems
Y2 - 11 May 2024 through 16 May 2024
ER -
