Research

My research quantifies the human part of complex socio-technical systems to improve decision-making for:

  1. Human-Machine Teams: For high-risk decisions, human decision-makers need to understand how and when to trust AI recommendations. Participatory research methods support efforts to design effective decision support, which are experimentally tested in the lab before moving toward field tests. Applications include AI in Transplant Healthcare and Biased AI in Hiring.
  2. Infrastructure Transitions: Individuals and organizations struggle to decide which technologies or projects to implement, particularly in the context of rapid technological change (and high uncertainty). Quantitative and qualitative impact evaluations provide inputs to models and simulations. Applications include Rural Broadband, Renewable Energy, and Fully-Mobile Radiation Oncology.

Human-Machine Teams

Infrastructure Transitions