Artificial intelligence (AI) tools can drive cars, monitor and adjust the temperature in your home, and chat with you online. AI could help public health officials, community workers, and clinics efficiently direct and allocate resources and better target interventions to improve health outcomes during disasters and public health emergencies.
“The COVID-19 pandemic highlighted a need for new approaches to resource allocation during public health crises—approaches that simultaneously serve our society’s most vulnerable communities, improve our overall health and well-being, and maximize impact,” says Maia Majumder, PhD, one of the leaders of the new AI Institute for Societal Decision Making (AI-SDM).
Led by Carnegie Mellon University, AI-SDM will improve the response to societal challenges such as disaster management and public health by creating human-centric AI tools to assist with critical decisions and by developing interdisciplinary training to bolster effective and rapid response in uncertain and dynamic situations. AI-SDM is one of seven AI institutes announced today by the National Science Foundation (NSF). A five-year, $20 million commitment from the NSF will support the institute.
AI-SDM will bring together experts from both the School of Computer Science and Dietrich College of Humanities and Social Sciences at CMU, as well as Harvard University, Boston Children’s Hospital, Howard University, Penn State, Texas A&M University, University of Washington, the MITRE Corporation, Navajo Technical University, and Winchester Thurston School. This diverse group of researchers and practitioners will work with public health departments, emergency management agencies, non-profits, companies, hospitals, and health clinics to enhance decision-making.
“I hope to harness my own lab’s existing partnerships with state health agencies across the US to ensure that the resource allocation tools we build through the Institute make it into practice,” says Majumder, faculty in the Computational Health Informatics Program at Boston Children’s Hospital.
AI-SDM will deploy its work in the field alongside public health and disaster management experts. One area of focus will be to help public health officials and emergency managers equitably allocate resources like health workers, vaccines, tests, treatment options, emergency aid, shelter, food, and rescue efforts during a disaster or health crisis. Majumder will work with Robin Murphy, a computer science and engineering professor at Texas A&M University, to lead these efforts.
“There are two resource allocation projects within the Institute that I’m particularly excited about. The first aims to aid the Madagascar Ministry of Health in deciding where to build their next 70 clinics by pairing electronic health data from existing clinics with techniques from remote sensing. The second project aims to identify pregnant people at high risk of preeclampsia and postnatal depression using data from 20,000 patients across Ethiopia, India, and the US so that healthcare workers can proactively reach out and ensure that pregnant people receive the care that they need,” says Majumder.
By bringing together AI and social science researchers, AI-SDM will enable data-driven, robust, resource-efficient decisions and improve outcomes by accounting for human factors that are key to accepting these decisions in the field, such as biases, perception of risk, trust, and equity. AI-SDM aims to leverage AI to understand human decision-making, improve AI's decision-making ability, and apply those advances to create better, more trusted choices.
Visit the NSF’s website for more information about the AI Institutes.