The same machine-learning methods used to learn about customers, improve speech recognition, and identify cat faces can also be applied to questions about conflict violence. Megan Price demonstrates how machine-learning methods help us determine what we know, and what we don’t, about the ongoing conflict in Syria. Megan then explains why these methods can be crucial to better understand patterns of violence, enabling better policy decisions, resource allocation, and ultimately, accountability and justice.
As the executive director at the Human Rights Data Analysis Group, Megan Price designs strategies and methods for statistical analysis of human rights data for projects in a variety of locations including Guatemala, Colombia, and Syria. Megan’s work in Guatemala includes serving as the lead statistician, since 2009, on a project in which she analyzes documents from the National Police Archive; she has also contributed analyses submitted as evidence in two court cases in Guatemala. Her work in Syria includes serving as the lead statistician and author on two recent reports, commissioned by the Office of the United Nations High Commissioner of Human Rights (OHCHR), on documented deaths in that country. Megan is a research fellow at the Carnegie Mellon University Center for Human Rights Science. She earned her PhD in biostatistics and a certificate in human rights from the Rollins School of Public Health at Emory University. Megan also holds an MS and BS in statistics from Case Western Reserve University.
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