Interaction Design Challenges for AI in Medicine
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Meeting ID: 936 3211 9621
The use of AI for improving medical decision making has garnered great excitement in recent years. Yet, despite growing enthusiasm and increased research, real-world clinical impact has been slow. Often, abandonment of these tools in clinical settings is not related to algorithmic performance, but rather due to inattention towards the technologies’ design and implementation. To understand and address these challenges, I will share two of my lab’s research projects, which use user-centered and participatory design methods to incorporate both providers’ and patients’ perspectives into clinical decision support systems.
Maia Jacobs is an Assistant Professor of Preventive Medicine and the Lisa Wissner-Slivka and Benjamin Slivka Assistant Professor of Computer Science. Jacobs’ research focuses on using human-computer interaction methods to design and evaluate novel technologies to support chronic disease management, including adaptive health information systems and machine learning-based decision support tools. Her research has been funded by the Underwriters Laboratories, National Science Foundation, the National Cancer Institute, and the Harvard Data Science Institute. She completed her PhD in Human Centered Computing at Georgia Institute of Technology and was a postdoctoral fellow in the Center for Research on Computation and Society at Harvard University.