Sanmay Das, Professor, Computer Science, is conducting an exploratory study in the use of techniques from artificial intelligence (AI) to improve early screening and the delivery of targeted assistance to households that are at risk of future homelessness and child maltreatment. Das and the other members of the research team seek to develop novel methods for allocation of scarce housing support to at-risk households, taking into account considerations of both overall efficiency and fairness. This work will necessitate novel problem formulation and algorithm development in AI as well as creating new ethical methods for deciding on how to effectively deliver social services while considering the vast complexity of human behavior.
Das is collaborating with Patrick J. Fowler, Associate Professor at Washington University in St. Louis, on this project.
The researchers will explore the feasibility of using novel algorithmic techniques to inform societal decision-making on the allocation of scarce resources, with the specific goal of improving service system outcomes for both homelessness and child welfare. The team’s focus is on homelessness prevention interventions that offer timely, non-reoccurring resources to stabilize families at risk of experiencing housing crises. In collaboration with researchers at Washington University in St. Louis, Das and Mason collaborators will leverage unique datasets on child welfare and homelessness and use these to inform the design of machine learning approaches to prediction of outcomes (specifically, repeat episodes of homelessness and future interaction with child protective services) and optimization techniques that leverage these predictions to determine which households to target for prevention interventions.
Regarding the importance of the project, Das said: “This project focuses on the use of AI to make resource allocation decisions in a context where the overall allocation must both improve social welfare and satisfy notions of fairness, equity, and justice. This is a challenging domain for AI, while reducing the risks of homelessness and child maltreatment are critical societal goals with the potential to substantively improve the lives of many of our most vulnerable citizens.”
Das received $157,255 from the National Science Foundation for this work. Funding began in April 2021 and will end in late August 2021.
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This part of information is sourced from https://www.eurekalert.org/pub_releases/2021-06/gmu-dru061421.php
