Advances in artificial intelligence (AI) enable unprecedented technical capabilities: computers can diagnose diseases, translate between languages, and drive cars. Yet integrating AI advances into successful products and services remains an open challenge, as today, the majority of AI initiatives fail. My work focuses on closing this innovation gap by helping innovation teams envision low-risk/high-value AI concepts. I will present new resources and processes that help reveal intersections of user needs and AI capabilities. I will share two healthcare case studies (intensive care and radiology imaging) that demonstrate how teams can do a better job of ideating many concepts and reduce their risks of failure. I will discuss opportunities and challenges for future research to enable human-centered, responsible AI innovation.

Bio: Nur Yildirim is a Human-Computer Interaction (HCI) designer and an assistant professor at the University of Virginia’s School of Data Science. Her research focuses on bringing design thinking and participatory approaches to AI product development, specifically to engage domain stakeholders in early-phase innovation. Nur received her PhD from Carnegie Mellon’s HCI Institute and spent time at Google Research and Microsoft Research working on human-centered AI innovation. She was named a Rising Star by Michigan AI Lab and MIT EECS. The National Institutes of Health, the National Science Foundation, and Accenture have supported her work. Before academia, Nur worked as a design practitioner in the industry, shipping award-winning products ranging from medical to consumer electronics to assistive robots to toys. Homepage: https://nuryildirim.github.io/

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