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AI for Human Rights
From the article: “Price described the touchstone of her organization as being a tension between how truth is simultaneously discovered and obscured. HRDAG is at the intersection of this tension; they are consistently participating in science’s progressive uncovering of what is true, but they are accustomed to working in spaces where this truth is denied. Of the many responsibilities HRDAG holds in its work is that of “speaking truth to power,” said Price, “and if that’s what you’re doing, you have to know that your truth stands up to adversarial environments.”
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Liberian Truth and Reconciliation Commission Data
In July 2009, The Human Rights Data Analysis Group concluded a three-year project with the Liberian Truth and Reconciliation Commission to help clarify Liberia’s violent history and hold perpetrators of human rights abuses accountable for their actions. In the course of this work, HRDAG analyzed more than 17,000 victim and witness statements collected by the Liberian Truth and Reconciliation Commission and compiled the data into a report entitled “Descriptive Statistics From Statements to the Liberian Truth and Reconciliation Commission.”
Liberian TRC data and the accompanying data dictionary
anonymized-statgivers.csv contains information ...
Record Linkage and Other Statistical Models for Quantifying Conflict Casualties in Syria
How do we know how many people have been killed in Syria? The hard answer is we don't. In this talk, presented at Strata, Megan Price addresses how HRDAG uses random forests, multiple systems estimation, and various Python and R packages to estimate conflict casualties.
STRATA
February 13, 2014
Santa Clara, California
Link to 10-minute talk on youtube
Back to Talks
Europe
Kosovo
Covid-19 Research and Resources
HRDAG is identifying and interpreting the best science we can find to shed light on the global crisis brought on by the novel coronavirus, about which we still know so little. Right now, most of the data on the virus SARS-CoV-2 and Covid-19, the condition caused by the virus, are incomplete and unrepresentative, which means that there is a great deal of uncertainty. But making sense of imperfect datasets is what we do. HRDAG is contributing to a better understanding with explainers, essays, and original research, and we are highlighting trustworthy resources for those who want to dig deeper.
Papers and articles by HRDAG
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