Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14365/5383
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dc.contributor.authorYildirim N.-
dc.contributor.authorZlotnikov S.-
dc.contributor.authorSayar D.-
dc.contributor.authorKahn J.M.-
dc.contributor.authorBukowski L.A.-
dc.contributor.authorAmin S.S.-
dc.contributor.authorRiman K.A.-
dc.date.accessioned2024-06-29T13:07:43Z-
dc.date.available2024-06-29T13:07:43Z-
dc.date.issued2024-
dc.identifier.isbn9798400703300-
dc.identifier.urihttps://doi.org/10.1145/3613904.3641896-
dc.identifier.urihttps://hdl.handle.net/20.500.14365/5383-
dc.descriptionACM SIGCHIen_US
dc.description2024 CHI Conference on Human Factors in Computing Sytems, CHI 2024 -- 11 May 2024 through 16 May 2024-- 199441en_US
dc.description.abstractAdvances in artificial intelligence (AI) have enabled unprecedented capabilities, yet innovation teams struggle when envisioning AI concepts. Data science teams think of innovations users do not want, while domain experts think of innovations that cannot be built. A lack of effective ideation seems to be a breakdown point. How might multidisciplinary teams identify buildable and desirable use cases? This paper presents a first hand account of ideating AI concepts to improve critical care medicine. As a team of data scientists, clinicians, and HCI researchers, we conducted a series of design workshops to explore more effective approaches to AI concept ideation and problem formulation. We detail our process, the challenges we encountered, and practices and artifacts that proved effective. We discuss the research implications for improved collaboration and stakeholder engagement, and discuss the role HCI might play in reducing the high failure rate experienced in AI innovation. © 2024 Copyright held by the owner/author(s)en_US
dc.description.sponsorshipCenter for Machine Learning and Health, School of Computer Science, Carnegie Mellon University, CMLH, SCS, CMU; National Science Foundation, NSF: 2007501; National Science Foundation, NSF; National Institutes of Health, NIH: R35HL144804; National Institutes of Health, NIHen_US
dc.language.isoenen_US
dc.publisherAssociation for Computing Machineryen_US
dc.relation.ispartofConference on Human Factors in Computing Systems - Proceedingsen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectBrainstormingen_US
dc.subjecthealthcareen_US
dc.subjecthuman-centered AIen_US
dc.subjectideationen_US
dc.subjectFailure analysisen_US
dc.subjectHuman engineeringen_US
dc.subjectBrainstormingen_US
dc.subjectBreakdown pointsen_US
dc.subjectCritical care medicineen_US
dc.subjectDesign workshopsen_US
dc.subjectDomain expertsen_US
dc.subjectHealthcareen_US
dc.subjectHuman-centered artificial intelligenceen_US
dc.subjectIdeationen_US
dc.subjectMultidisciplinary teamsen_US
dc.subjectSketchingsen_US
dc.subjectIntensive care unitsen_US
dc.titleSketching AI Concepts with Capabilities and Examples: AI Innovation in the Intensive Care Uniten_US
dc.typeConference Objecten_US
dc.identifier.doi10.1145/3613904.3641896-
dc.identifier.scopus2-s2.0-85194834262en_US
dc.departmentİzmir Ekonomi Üniversitesien_US
dc.authorscopusid57218706672-
dc.authorscopusid58912493800-
dc.authorscopusid55669394200-
dc.authorscopusid22937577300-
dc.authorscopusid56728300300-
dc.authorscopusid58912493900-
dc.authorscopusid57205711246-
dc.institutionauthor-
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.identifier.scopusqualityN/A-
dc.identifier.wosqualityN/A-
item.grantfulltextopen-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.cerifentitytypePublications-
item.openairetypeConference Object-
item.fulltextWith Fulltext-
item.languageiso639-1en-
Appears in Collections:Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
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