Abstract
While AI-assisted colonoscopy promises improved colorectal cancer screening,
its success relies on effective integration into clinical practice, not just
algorithmic accuracy. This paper, based on an Australian field study
(observations and gastroenterologist interviews), highlights a critical
disconnect: current development prioritizes machine learning model performance,
overlooking essential aspects of user interface design, workflow integration,
and overall user experience. Industry interactions reveal a similar emphasis on
data and algorithms. To realize AI's full potential, the HCI community must
champion user-centered design, ensuring these systems are usable, support
endoscopist expertise, and enhance patient outcomes.