{"type":"ScholarlyArticle","title":"Algorithmic Social Intervention","authors":[{"name":"Bryan Wilder","slug":"bryan-wilder","given":"Bryan","family":"Wilder","affiliation":"University of Southern California"}],"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.","doi":"10.24963/ijcai.2018/840","url":"https://ijcai.org/proceedings/2018/840","pdf":"https://ijcai.org/proceedings/2018/0840.pdf","markdown":"https://ijcai.org/proceedings/2018/840.md","bibtex":"https://ijcai.org/proceedings/2018/bibtex/840","volume":{"slug":"2018","title":"Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2018","url":"https://ijcai.org/proceedings/2018/","year":2018,"location":"Stockholm","dates":"13-19 July 2018","editors":"Jérôme Lang","isbn":"978-0-9992411-2-7","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2018"},"section":"Doctoral Consortium","track":"Doctoral Consortium","number":840,"pages":{"first":5793,"last":5794},"keywords":["Machine Learning: Machine Learning","Multidisciplinary Topics and Applications: AI and Social Sciences","Combinatorial & Heuristic Search: Combinatorial search/optimisation"],"videos":[],"references":[{"position":1,"raw":"[Wilder et al., 2017] Bryan Wilder, Amulya Yadav, Nicole Immorlica, Eric Rice, and Milind Tambe. Uncharted but not uninfluenced: Influence maximization with an uncer- tain network. In AAMAS, 2017.","title":"Uncharted but not uninfluenced: Influence maximization with an uncertain network","authors":"Bryan Wilder, Amulya Yadav, Nicole Immorlica, Eric Rice, Milind Tambe","year":"2017","venue":"AAMAS","doi":null,"url":null,"internal_url":null},{"position":2,"raw":"[Wilder et al., 2018a] Bryan Wilder, Nicole Immorlica, Eric Rice, and Milind Tambe. Maximizing influence in an un- known social network. In AAAI, 2018.","title":"Maximizing influence in an unknown social network","authors":"Wilder","year":"2018","venue":"AAAI","doi":null,"url":null,"internal_url":null},{"position":3,"raw":"[Wilder et al., 2018b] Bryan Wilder, Laura Onasch-Vera, Ju- liana Hudson, Jose Luna, Nicole Wilson, Robin Petering, Darlene Woo, Milind Tambe, and Eric Rice. End-to-end influence maximization in the field. In AAMAS, 2018.","title":"End-to-end influence maximization in the field","authors":"Wilder","year":"2018","venue":"AAMAS","doi":null,"url":null,"internal_url":null},{"position":4,"raw":"[Wilder et al., 2018c] Bryan Wilder, Han Ching Ou, Kayla de la Haye, and Milind Tambe. Optimizing network struc- ture for preventative health. In AAMAS, 2018.","title":"Optimizing network structure for preventative health","authors":"Wilder","year":"2018","venue":"AAMAS","doi":null,"url":null,"internal_url":null},{"position":5,"raw":"[Wilder et al., 2018d] Bryan Wilder, Sze-Chuan Suen, and Milind Tambe. Preventing infectious disease in dynamic populations under uncertainty. In AAAI, 2018.","title":"Preventing infectious disease in dynamic populations under uncertainty","authors":"Wilder","year":"2018","venue":"AAAI","doi":null,"url":null,"internal_url":null},{"position":6,"raw":"[Wilder, 2018a] Bryan Wilder. Equilibrium computation and robust optimization in zero sum games with submodular structure. In AAAI, 2018.","title":"Equilibrium computation and robust optimization in zero sum games with submodular structure","authors":"Bryan Wilder, Wilder","year":"2018","venue":"AAAI","doi":null,"url":null,"internal_url":null},{"position":7,"raw":"[Wilder, 2018b] Bryan Wilder. Risk-sensitive submodular optimization. In AAAI, 2018.","title":"Risk-sensitive submodular optimization","authors":"Bryan Wilder, Wilder","year":"2018","venue":"AAAI","doi":null,"url":null,"internal_url":null},{"position":8,"raw":"[Yadav et al., 2017] Amulya Yadav, Bryan Wilder, Eric Rice, Robin Petering, Jaih Craddock, Amanda Yoshioka- Maxwell, Mary Hemler, Laura Onasch-Vera, Milind Tambe, and Darlene Woo. Influence maximization in the field: The arduous journey from emerging to deployed ap- plication. In AAMAS, 2017.","title":"Influence maximization in the field: The arduous journey from emerging to deployed application","authors":"Amulya Yadav, Bryan Wilder, Eric Rice, Robin Petering, Jaih Craddock, Amanda Yoshioka-Maxwell, Mary Hemler, Laura Onasch-Vera, Milind Tambe, Darlene Woo","year":"2017","venue":"AAMAS","doi":null,"url":null,"internal_url":null}],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}