{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,31]],"date-time":"2026-07-31T03:26:29Z","timestamp":1785468389295,"version":"3.56.0"},"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>AI is transforming the healthcare domain and is increasingly helping practitioners to make health-related decisions.\nTherefore, accountability becomes a crucial concern for critical AI-driven decisions. Although regulatory bodies, such\nas the EU Commission, provide guidelines, they are highlevel and focus on the \u201cwhat\u201d that should be done and less\non the \u201chow\u201d, creating a knowledge gap for actors. Through\nan extensive analysis, we found that the term accountability is\nperceived and dealt with in many different ways, depending\non the actor\u2019s expertise and domain of work. With increasing concerns about AI accountability issues and the ambiguity around this term, this paper bridges the gap between the\n\u201cwhat\u201d and \u201chow\u201d of AI accountability, specifically for AI\nsystems in healthcare. We do this by analysing the concept\nof accountability, formulating an accountability framework,\nand providing a three-tier structure for handling various accountability mechanisms. Our accountability framework positions the regulations of healthcare AI systems and the mechanisms adopted by the actors under a consistent accountability regime. Moreover, the three-tier structure guides the actors of the healthcare AI system to categorise the mechanisms\nbased on their conduct. Through our framework, we advocate\nthat decision-making in healthcare AI holds shared dependencies, where accountability should be dealt with jointly and\nshould foster collaborations. We highlight the role of explainability in instigating communication and information sharing\nbetween the actors to further facilitate the collaborative process.<\/jats:p>","DOI":"10.1609\/aies.v8i1.36548","type":"journal-article","created":{"date-parts":[[2025,10,15]],"date-time":"2025-10-15T13:19:11Z","timestamp":1760534351000},"page":"279-291","source":"Crossref","is-referenced-by-count":3,"title":["Accountability Framework for Healthcare AI Systems: Towards Joint Accountability in Decision Making"],"prefix":"10.1609","volume":"8","author":[{"given":"Prachi","family":"Bagave","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Marcus","family":"Westberg","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Marijn","family":"Janssen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Aaron Yi","family":"Ding","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\/36548\/38686","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/ojs.aaai.org\/index.php\/AIES\/article\/download\/36548\/38686","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,15]],"date-time":"2025-10-15T13:19:11Z","timestamp":1760534351000},"score":1,"resource":{"primary":{"URL":"https:\/\/ojs.aaai.org\/index.php\/AIES\/article\/view\/36548"}},"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.v8i1.36548","relation":{},"ISSN":["3065-8365"],"issn-type":[{"value":"3065-8365","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,10,15]]}}}