Advances in artificial intelligence (AI) have enabled unprecedented capabilities, yet innovation teams struggle when envisioning AI concepts. Data science teams think of innovations users do not want, while domain experts think of innovations that cannot be built. A lack of effective ideation seems to be a breakdown point. How might multidisciplinary teams identify buildable and desirable use cases? This paper presents a first hand account of ideating AI concepts to improve critical care medicine. As a team of data scientists, clinicians, and HCI researchers, we conducted a series of design workshops to explore more effective approaches to AI concept ideation and problem formulation. We detail our process, the challenges we encountered, and practices and artifacts that proved effective. We discuss the research implications for improved collaboration and stakeholder engagement, and discuss the role HCI might play in reducing the high failure rate experienced in AI innovation.
@article{arxiv.2402.13437,
title = {Sketching AI Concepts with Capabilities and Examples: AI Innovation in the Intensive Care Unit},
author = {Nur Yildirim and Susanna Zlotnikov and Deniz Sayar and Jeremy M. Kahn and Leigh A. Bukowski and Sher Shah Amin and Kathryn A. Riman and Billie S. Davis and John S. Minturn and Andrew J. King and Dan Ricketts and Lu Tang and Venkatesh Sivaraman and Adam Perer and Sarah M. Preum and James McCann and John Zimmerman},
journal= {arXiv preprint arXiv:2402.13437},
year = {2024}
}