Abstract: Advances in computing technology continue to offer us new insights about our health and well-being. As mutually reinforcing trends make the use of  wearable and mobile devices routine, we now collect personal, health-related data at an unprecedented scale.  Meanwhile, the use of deep-learning-based health screening technologies changes relationships between caregivers and care recipients, with multitudinous implications for equity, privacy, safety, and trust . How can researchers take inclusive and responsible approaches to envisioning solutions, training data, and deploying AI/ML-driven solutions? Who should be involved in decisions about how to use ML/AI in digital health and well-being solutions, and even what solutions matter in the first place? In this talk, I will discuss participatory approaches to designing digital health and well-being technologies with patients, family members, and clinicians.  Starting with field studies in clinics exploring how people navigated use of a deployed, diagnostic AI system, and moving onto examples of responsibility AI practices, I will discuss participatory approaches and their importance throughout the technology design, development, and evaluation process.

Bio: Lauren Wilcox, PhD, is a Senior Staff Research Scientist in Responsible AI and Human-Centered Computing in Google Research. She brings sixteen years of experience conducting human-centered computing research in service of human health and well-being. Previously at Google Health, Wilcox led initiatives to align AI advancements in healthcare with the needs of clinicians, patients, and their family members. She also holds an Adjunct Associate Professor position in Georgia Tech’s School of Interactive Computing. Wilcox was an inaugural member of the ACM Future of Computing Academy. She frequently serves on the organizing and technical program committees for premier conferences in the field (e.g., ACM CHI). Wilcox received her PhD in Computer Science from Columbia University in 2013.