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Computer Science > Artificial Intelligence

Title: Algorithmic Social Intervention

Authors: Bryan Wilder
Abstract: Social and behavioral interventions are a critical tool for governments and communities to tackle deep-rooted societal challenges such as homelessness, disease, and poverty. However, real-world interventions are almost always plagued by limited resources and limited data, which creates a computational challenge: how can we use algorithmic techniques to enhance the targeting and delivery of social and behavioral interventions? The goal of my thesis is to provide a unified study of such questions, collectively considered under the name "algorithmic social intervention". This proposal introduces algorithmic social intervention as a distinct area with characteristic technical challenges, presents my published research in the context of these challenges, and outlines open problems for future work. A common technical theme is decision making under uncertainty: how can we find actions which will impact a social system in desirable ways under limitations of knowledge and resources? The primary application area for my work thus far is public health, e.g. HIV or tuberculosis prevention. For instance, I have developed a series of algorithms which optimize social network interventions for HIV prevention. Two of these algorithms have been pilot-tested in collaboration with LA-area service providers for homeless youth, with preliminary results showing substantial improvement over status-quo approaches. My work also spans other topics in infectious disease prevention and underlying algorithmic questions in robust and risk-aware submodular optimization.
Comments: Thesis proposal. 21 pages, 4 figures
Subjects: Artificial Intelligence (cs.AI); Computers and Society (cs.CY); Social and Information Networks (cs.SI)
Cite as: arXiv:1803.05098 [cs.AI]
  (or arXiv:1803.05098v1 [cs.AI] for this version)

Submission history

From: Bryan Wilder [view email]
[v1] Wed, 14 Mar 2018 02:00:54 GMT (1195kb,D)