The Many Chefs in the AI Kitchen: Collaborative AI Design and Development in Oncology

Abstract

Advancements in artificial intelligence (AI) are redefining innovation in healthcare. In the radiology do‐ main, advanced AIsystemshaveshownpromisingperformanceinmedicaltaskssuchastumordetection and treatment plan. Given the multidisciplinary nature of the medical AIdevelopmentteam, challenges in collaboration, design, and integration are common. Forexample, the design lens is less present, researchers from different disciplines speak different languages, andcliniciansastheend‐usersoftenplaytheexternal consultant role rather than team members. To address these gaps, wepresentthedevelopmentofacol‐ labor ation platform, anAI‐assistedcomputer‐aideddiagnosis (CAD) system for radiology, usinga Research through Design (RtD) methodology. Throughathree‐phasecasestudy, weshowcaseanovelwayofoper‐ ation ali zing multidisciplinary collaboration with design team playing the coordinating and integrating role, highlightingtheimportanceofincludingsubject‐matterexpertsdirectlyindevelopmentteams. Wealso provideadesignanddevelopmentguidelineformultidisciplinaryresearchteam. Moreover, this case study demonstrate show design struggles and decisions contribute to knowledge generation, offering strategies tobalancehuman‐andtechno‐centricperspectives. Reflecting on the process, we provide pertinent input for design research, HCI, and design and collaboration implications for developing AIsystemsinradiology, and for healthcare AImoregenerally.

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