AI Institute for Societal Decision Making (AI-SDM)

Decision making in domains such as a public health crisis or disaster response has a significant societal and economic impact. These domains present critical challenges for decision-making as they require complex, potentially life-saving, decisions to be made under dynamic, uncertain and resource-constrained scenarios, while accounting for factors that are key to acceptance of the decisions, such as stakeholders' biases and perception of risk, trust, and equity.

AI advancements and data availability can complement human limitations in navigating this complex decision space, however, current systems fail to account for the stakeholders' mental states and behavior. The AI institute for Societal Decision Making (AI-SDM) will target this opportunity at the confluence of social decision sciences and AI by developing human-centric AI for decision-making and inter-disciplinary training, to enable transformative solutions to societal decision challenges.

By bringing AI and social science researchers, AI-SDM will enable emergency managers, public health officials, first responders, community workers, and the public to make quick, data-driven, and resource-efficient decisions, while also improving outcomes by accounting for human factors governing acceptance. The vision of AI-SDM will be realized via development of novel AI theory and methods, translational research, training, and outreach, enabled by partnerships among diverse universities, government organizations, corporate partners, community colleges, public libraries, and high schools.

The institute will establish the role of AI in advancing and bridging human and autonomous decision-making, under the use-inspired challenges of working in environments that are dynamic, uncertain, resource constrained, and require societal acceptance arising in public health crisis and disaster response. Specifically, the foundational research will develop (1) computational representations of human decision processes, (2) robust aggregation methods for collective decision-making, (3) multi-objective autonomous decision support tools, and corresponding innovations in (4) causal and counterfactual reasoning.

These foundational foci are inspired by, and will be applied to, equitable resource allocation to improve public health and disaster outcomes, timely targeted interventions informed by human decision-making to encourage adherence to policy recommendations, and adoption of AI decision support by understanding how adoption can be modulated by different use patterns. The research will be guided by theoretical advances in computational cognitive science, social-choice theory, distribution-free statistics, game theory, casual and counterfactual reasoning, and interactive and autonomous machine learning.

In addition to impacting use-case domains via a wide network of partners, AI-SDM will develop the next generation of workforce trained on human-centric AI and an AI-aware public via broader impact efforts including professional development workshops for high school educators, enrichment and leadership activities for under-represented students, inter-disciplinary degrees and courses, curriculum co-design with community college and educational partners, workforce training, and public engagement activities.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.