Realizing AI for Impact: Uncertainty and Human-Agent Collaboration in Multi-Agent Systems for Public Health and Conservation

AI is now being applied widely in society, including to support decision-making in important, resource-constrained efforts in conservation and public health. Such real-world use cases introduce new challenges, like noisy, limited data and human-in-the-loop decision-making. In addition to addressing these algorithmic challenges, we must also work with all stakeholders in this research, including by making our field more inclusive through efforts like my nonprofit, Try AI.

Elizabeth Bondi-Kelly is an Assistant Professor of Electrical Engineering and Computer Science at the University of Michigan. She has a PhD in Computer Science at Harvard University, where she was advised by Prof. Milind Tambe, and she was formerly a Postdoctoral Fellow at MIT through the CSAIL METEOR Fellowship. Her research interests are focused on artificial intelligence for social impact, particularly spanning the fields of multi-agent systems and data science. Her work, which has been published in venues such as AAAI, AAMAS, AIES, and IJCAI, has applications in conservation and public health, and has been deployed to support conservation efforts. She also founded and currently leads Try AI, a 501(c)(3) nonprofit committed to increasing diversity, equity, inclusion, and belonging in the field of AI through community-building educational programs, largely focused on AI for social impact.