RI: HCC: Medium: Equity, Justice, and Incentives in Societal Resource Allocation

Local, state, and nonprofit institutions typically follow a range of different prioritization practices for the allocation of scarce resources. Communities also have to make decisions about how to allocate human resources across space and time (for example, police officers across a district for crime prevention). This project aims to understand how algorithmic techniques for prioritization and for resource allocation can best be used for benefit in such domains. This project will produce algorithms, models, and insights that are of broad interest to researchers studying artificial intelligence (AI), algorithmic models of strategic interactions (i.e., game theory) and mechanism design, multiagent systems, and human-AI interaction. In addition, the work will impact policy through collaborations with community partners and support the training of graduate students. At a technical level, the project will focus on several research problems important to the development of trustworthy AI. These include: (1) The design of algorithmic techniques for facilitating individualized deployment of scarce societal resources based on (potentially poorly calibrated and semantically ambiguous) risk scores, using rank information and/or learned transformations of cardinal risk scores. (2) Developing foundational models for appropriate and efficient deployment of human resources (e.g., police officers, schoolteachers and specialists) across space and time. (3) Use of interpretable machine learning to characterize current human decision-making in public-facing positions and analyze the efficiency of current approaches versus algorithmic ones. (4) Elicitation of reliable information in order to improve societal decision-making, using ideas from mechanism design and audit games. (5) The design of algorithmic decision support tools that can align the incentives of agents with the local agencies they represent while allowing continued use of discretion. 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.