Human-AI Collaborative Innovation in Design

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dc.contributor.authorSong, Binyangen
dc.contributor.authorZhu, Qihaoen
dc.contributor.authorLuo, Jianxien
dc.date.accessioned2024-02-22T18:48:14Zen
dc.date.available2024-02-22T18:48:14Zen
dc.date.issued2024en
dc.description.abstractHuman-AI collaboration (HAIC) is a promising strategy to transform engineering design and innovation, yet how to design artificial intelligence (AI) to boost HAIC remains unclear. Accordingly, this paper provides a new, unified, and comprehensive scheme for classifying AI roles. On this basis, we develop an AI design framework that outlines expected AI capabilities, interactive attributes, and trust enablers across various HAIC scenarios, offering guidance for integrating AI into human teams effectively. We also discuss current advancements, challenges, and prospects for future research.en
dc.description.notesYes, full paper (Peer reviewed?)en
dc.description.versionAccepted versionen
dc.format.mimetypeapplication/pdfen
dc.identifier.urihttps://hdl.handle.net/10919/118113en
dc.language.isoenen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.titleHuman-AI Collaborative Innovation in Designen
dc.title.serialInternational Design Conferenceen
dc.typeConference proceedingen
dc.type.dcmitypeTexten
pubs.finish-date2024-05-23en
pubs.organisational-group/Virginia Techen
pubs.organisational-group/Virginia Tech/Engineeringen
pubs.organisational-group/Virginia Tech/Engineering/Industrial and Systems Engineeringen
pubs.start-date2024-05-20en

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