Addressing Uncertainty in AI Tool Development in Healthcare Through End-User Involvement

Artificial Intelligence (AI) development is an increasingly significant area of interest for Information Systems (IS) scholars, aiming to explore the socio-technical aspects of human-AI collaboration. This paper reports on a qualitative case study focused on a dementia-predicting AI tool currently under development. Through in-depth interviews with AI developers, we aim to gain insights into their expert practices and the uncertainties they encounter during the development process. Using a framework to outline the stages of AI tool development, we uncover four key uncertainties: feasibility, data, decision-making, and adoption. We examine how AI developers cope with these uncertainties through varying methods and present strategies for end-user involvement to reduce uncertainty when possible