Exploring the Design of Generative AI in Supporting Music-based Reminiscence for Older Adults
<|reference_start|>Exploring the Design of Generative AI in Supporting Music-based Reminiscence for Older Adults: 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.<|reference_end|>
@article{jin2024exploring,
    title={Exploring the Design of Generative AI in Supporting Music-based
  Reminiscence for Older Adults},
    author={Yucheng Jin, Wanling Cai, Li Chen, Yizhe Zhang, Gavin Doherty, Tonglin
  Jiang},
    journal={arXiv preprint arXiv:2403.01413},
    year={2024},
    archivePrefix={arXiv},
    eprint={2403.01413},
    primaryClass={cs.HC cs.AI}
}