Artificial intelligence tools have increasingly aided emergency managers, public health officials and other professionals tasked with making critical and timely decisions that directly impact society. During disasters, AI can help efficiently direct and allocate resources. Likewise, AI tools help public health officials, community workers and clinics better target interventions to improve health outcomes.

The advancement of AI and its integration into crisis response can significantly impact society and help save lives. But to be truly effective, AI researchers, social scientists, decision-makers and the public must understand and trust these tools.

Led by Carnegie Mellon University, the AI Institute for Societal Decision Making (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. The institute will also develop interdisciplinary training to bolster effective and rapid response in uncertain and dynamic situations.

AI-SDM is one of seven AI institutes awarded today by the National Science Foundation. A five-year, $20 million commitment from the NSF will support the institute.

"The best applications of artificial intelligence in societal domains will come when we not only advance AI for decision-making, but also better understand human decision-making, and when we can bring the two together," said Aarti Singh, a professor in the Machine Learning Department of CMU's School of Computer Science, who will serve as the institute's director. "Social scientists are studying human behavior. Machine learning researchers are developing new AI technologies to aid decision-making. For maximal impact of these technologies, we need to have social scientists and AI researchers collaborate to come up with solutions that will leverage AI capability while ensuring social acceptance."

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, the 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, nonprofits, companies, hospitals and health clinics to enhance decision-making.

"With artificial intelligence advancing at a dizzying pace, our future depends on researchers, social scientists, decision-makers and the public working together to understand these tools and put them to ethical use," said Congresswoman Summer Lee (PA-12), whose district includes CMU. "I'm proud to announce a $20 million research award from the National Science Foundation for CMU to lead the country's AI Institute for Societal Decision Making. A collaboration of several institutions, including my alma mater, Howard University, the institute will work interdisciplinarily to design ethical, human-centric AI tools to help improve disaster response and aid public health officials, community workers and clinics."

AI-SDM is the fifth NSF-funded AI institute to include researchers from CMU, and the first to be led by the university's expertise. CMU faculty already contribute to the AI Institute for Collaborative Assistance and Responsive Interaction for Networked Groups (AI-CARING), the AI Institute for Future Edge Networks and Distributed Intelligence (AI-EDGE), the USDA-NIFA AI Institute for Resilient Agriculture (AIIRA), and the Institute for Agricultural AI for Transforming Workforce and Decision Support (AgAID). These institutes were established in 2021.

"The National AI Research Institutes are a critical component of our nation's AI innovation, infrastructure, technology, education and partnerships ecosystem," said NSF Director Sethuraman Panchanathan. "These institutes are driving discoveries that will ensure our country is at the forefront of the global AI revolution."

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 acceptance of these decisions in the field, such as biases, perception of risk, trust and equity. AI-SDM aims to leverage AI to better understand human decision-making; to improve the ability of AI to make decisions; and to apply those advances to create better, more trusted choices. 

"Artificial intelligence holds extraordinary potential, and at this critical stage in its development, stakeholders from across disciplinary boundaries must come together to responsibly apply these generational breakthroughs to the real world," said Theresa Mayer, CMU's Vice President for Research. "CMU is grateful for the partnership of the National Science Foundation, whose commitment will allow AI-SDM and its partners to advance powerful, human-centric AI solutions for challenging situations that require split-second decision-making."

AI-SDM will undertake several foundational thrusts to improve the understanding of human decision-making and create AI tools to assist with it. Cognitive and behavioral scientists will develop computational models to accurately represent how and why humans make the decisions they do in times of crisis. Predicting human choices is key to developing better AI tools and ensuring their success in society. This work will be led by Cleotilde Gonzalez, a research professor in CMU's Department of Social and Decision Sciences, and Christopher Dancy, an associate professor in the Penn State College of Engineering.

"Our work at the AI-SDM will contribute the foundational research required to accurately predict human choices under conditions of uncertainty, time constraints and temporal dynamics. We will construct the future of experimental and computational cognitive decision science, promoting equity and fairness through human-AI complementarity," said Gonzalez, who will serve as the institute's research co-director.

Armed with this understanding, social scientists and AI researchers will work together to understand human-AI complementarity and create models of group and hybrid human-AI decision-making. This will also generate an understanding of how social values such as equity, ethics and risk influence individual and group choices. Leading this work will be Ariel Procaccia, a professor of computer science at Harvard, and Aaditya Ramdas, an assistant professor in CMU's Department of Statistics & Data Science and Machine Learning Department.

"When AI or humans predict how a particular situation will evolve or propose varying options to take because of different underlying perceptions of risk and utility, it is important to think about how best to elicit these complex preferences and combine them into a group decision," Ramdas said. "In a setting where these agents make repeated decisions, we hope to design algorithms that can learn from experience how to combine these decisions — from AI or humans with possibly different individual incentives — toward a common group goal."

Finally, AI researchers in the institute will develop tools capable of making autonomous decisions that will support people in both disaster and public health management. They will have to work in dynamic and uncertain environments and under intense pressure and constraints. They will have to juggle competing objectives with incomplete information and coordinate with many people using imperfect communication, which is a mighty task for current AI. This work will be led by Sham Kakade, a computer science and statistics professor at Harvard, and Jeff Schneider, a research professor in CMU's Robotics Institute.

"We are especially excited by the opportunity for AI to help real people in scenarios where good decision-making is most needed, yet difficult to come by," Schneider said. "Researchers at CMU are already developing advanced AI and robotic systems that will be useful in assisting with societal challenges."

The AI tools created by AI-SDM will not only assist decision-makers with tasks at hand but will also help them reflect on past actions and evaluate decisions not taken. If an emergency manager or public health official sent resources or targeted interventions at one location instead of another, would the result have been different? Tools that can model or simulate these scenarios will help make better decisions. Extensive research in the humanities has looked at how counterfactual and causal reasoning affect human decision-making and acceptance, and applying this research is key to explainable AI that can be trusted. Kun Zhang, an associate professor in CMU's Department of Philosophy, will lead this effort.

"Two decades ago, CMU helped create the modern field of causal discovery," Zhang said. "We are now going to a higher level to find hidden causal variables and causal relations for causal inference and counterfactual reasoning from video, images, text and tabular data. This effort will have direct implications not only in decision-making but also in related fields such as scientific discovery, health care, marketing and more."

AI-SDM will deploy its work in the field alongside experts in public health and disaster management. 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. Maia Majumder, an assistant professor in the Computational Health Informatics Program at Harvard Medical School and Boston Children's Hospital, and Robin Murphy, a professor in computer science and engineering at Texas A&M University will lead these efforts.

The institute will also develop tools that will help make timely interventions in public health and disaster management. This could be messaging to stop the spread of infectious diseases or improve maternal health, or communication efforts during a disaster to direct people to safety and aid. This effort will be led by Gretchen Chapman, head of the Department of Social and Decision Sciences at CMU, and Terri Adams-Fuller, a professor in the Department of Sociology and Criminology at Howard University.

"Successful management of infectious disease outbreaks and natural disasters requires that members of the public engage in behaviors such as getting vaccinated or evacuating an area. Consequently, it is critical for social scientists to understand how the public responds to risk communication about public health," Chapman said. "This new center will combine current AI techniques with behavioral studies to illuminate how individuals make decisions in public health contexts."

Supporting the tools developed by AI-SDM will be research into how to improve the acceptance of AI-assisted decision-making by both people tasked with making choices and the public. Support for AI-enabled decisions depends on many controllable and uncontrollable factors such as ethics, risk, equity and explainability. Doubt in any of these can hamper adoption. This work will be led by Paul Lehner, a senior principal AI and decision scientist at the MITRE Corporation, and by Ozgur Eris, the chief engineer for AI and autonomy at MITRE.

The impact of AI-SDM will be realized through work with various government health departments, emergency management agencies, companies and nonprofit organizations located in the U.S. and abroad. Engagement will include surveys and virtual exercises with emergency managers and public health officials to learn how they make decisions, pilot deployments in the field, and technical and personnel exchanges.

"To have the opportunity to build an AI-focused education network vertically integrated across K-12, community colleges, universities and the professional workforce that truly engages with and puts people and society first and foremost is unprecedented and incredibly exciting," said Rebecca Nugent, head of CMU's Department of Statistics & Data Science and the education and outreach lead for AI-SDM. "We're looking forward to empowering the broader diverse population to use AI and data-informed decision-making to tackle societal challenges and in their daily lives."

This work will be paired with education and workforce development. AI-SDM's goal of widespread adoption of AI-enabled decisions cannot happen without creating a workforce trained on developing and using human-centric AI tools, and educating the public so they are aware and understand AI's complementary role and shortcomings. These efforts will include a collaboration with Winchester Thurston School to create professional development workshops for high school educators, enrichment and leadership activities for underrepresented students, interdisciplinary degrees and courses, curriculum co-design with community colleges and educational partners such as Navajo Tech, workforce training, upskilling, and public engagement activities.

"A big part of this is engagement with the community," Singh said. "The public's understanding and trust of our work is essential to making it viable. Without them, we cannot push forward."

Visit the NSF's website for more information about the AI Institutes.

CMU@AI-SDM

The AI-SDM includes top researchers from CMU’s School of Computer Science and Dietrich College of Humanities and Social Sciences. The institute's personnel include: Aarti Singh (Director), Cleotilde Gonzalez (Co-Director), Jeff Schneider, Gretchen Chapman, Howie Choset, Hoda Heidari, Rebecca Nugent, Aaditya Ramdas, Roni Rosenfeld, Majd Sakr, Peter Spirtes, Bryan Wilder and Kun Zhang.