{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,5]],"date-time":"2026-06-05T01:58:23Z","timestamp":1780624703487,"version":"3.54.1"},"reference-count":0,"publisher":"Association for the Advancement of Artificial Intelligence (AAAI)","issue":"1","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["AIES"],"abstract":"<jats:p>As artificial intelligence increasingly shapes healthcare\nsystems, understanding how older adults\u2014who interact with\nhealthcare services more often and face particular\ndifficulties\u2014develop trust in these technologies becomes\ncrucial. While the AIES community has previously examined\nAI\u2019s social implications across dimensions like gender and\nrace, age remains an understudied axis of analysis. Through\na participatory workshop with older adults in Germany, this\npaper investigates two central questions: (1) How do older\nadults perceive and experience trust in AI-driven\nhealthcare technologies? (2) What are the key factors that\nshape trust in AI healthcare technologies among older\nadults? Our findings reveal that while older people trust\ncertain abilities of AI systems, like medical image\nanalysis, there is a strong emphasis on the necessity of\nhuman supervision to trust in these systems. Key trust\nfactors elicited by our study are transparency about\ntraining data demographics and algorithmic decision-making\nprocesses. More importantly, a gradual exposure to AI\nsystems in non-critical settings, prior positive experience\nwith technology, and cultural context\u2014particularly trust in\nlocally developed systems with clear accountability\nmeasures and robust regulatory oversight are key elements\nin trust formation among older adults. This study offers\ncontextualized insights to guide the equitable,\ncommunity-driven design, deployment, and governance of AI\nhealthcare technologies, aiming to better serve older\npopulations. By centering inclusivity in technology\ndevelopment and advancing trustworthy AI systems, this work\ncontributes to ethical, effective healthcare solutions\ntailored to the needs of aging communities.<\/jats:p>","DOI":"10.1609\/aies.v8i1.36566","type":"journal-article","created":{"date-parts":[[2025,10,15]],"date-time":"2025-10-15T13:15:34Z","timestamp":1760534134000},"page":"498-512","source":"Crossref","is-referenced-by-count":3,"title":["Trust Formation in Healthcare AI: An Exploration of Older Adults\u2019 Perspectives"],"prefix":"10.1609","volume":"8","author":[{"given":"\u00d6nder","family":"Celik","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Marlene","family":"Kulla","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Justyna","family":"Stypinska","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"9382","published-online":{"date-parts":[[2025,10,15]]},"container-title":["Proceedings of the AAAI\/ACM Conference on AI, Ethics, and Society"],"original-title":[],"link":[{"URL":"https:\/\/ojs.aaai.org\/index.php\/AIES\/article\/download\/36566\/38704","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/ojs.aaai.org\/index.php\/AIES\/article\/download\/36566\/38704","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,15]],"date-time":"2025-10-15T13:15:34Z","timestamp":1760534134000},"score":1,"resource":{"primary":{"URL":"https:\/\/ojs.aaai.org\/index.php\/AIES\/article\/view\/36566"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,10,15]]},"references-count":0,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2025,10,15]]}},"URL":"https:\/\/doi.org\/10.1609\/aies.v8i1.36566","relation":{},"ISSN":["3065-8365"],"issn-type":[{"value":"3065-8365","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,10,15]]}}}