  Despite the promises of data-driven artificial intelligence (AI), little is
known about how we can bridge the gulf between traditional physician-driven
diagnosis and a plausible future of medicine automated by AI. Specifically, how
can we involve AI usefully in physicians' diagnosis workflow given that most AI
is still nascent and error-prone (e.g., in digital pathology)? To explore this
question, we first propose a series of collaborative techniques to engage human
pathologists with AI given AI's capabilities and limitations, based on which we
prototype Impetus - a tool where an AI takes various degrees of initiatives to
provide various forms of assistance to a pathologist in detecting tumors from
histological slides. We summarize observations and lessons learned from a study
with eight pathologists and discuss recommendations for future work on
human-centered medical AI systems.
