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How we built a model to search hundreds of thousands of text messages from the perpetrators of a human rights crime.
We are non-partisan—we do not take sides in political or military conflicts, nor do we advocate any particular political party or government policy. However, we are not neutral: we are always in favor of human rights. We support the protections established in the Universal Declaration of Human Rights, the International Covenant on Civil and Political Rights, and other international human rights treaties and instruments.
A special announcement from the HRDAG Advisory Board:
Beginning officially on December 1, HRDAG is changing leadership. After nearly three years as Executive Director, Patrick Ball will become the new Director of Research. Megan Price will be the new Executive Director.
Patrick has spent more than 25 years working at the intersection of human rights and statistical science. Over that time, he has finely honed statistical methodology for quantifying mass killings. Now he is excited about the chance to go deeper into research for HRDAG and develop additional approaches for new problems. In his new role, Patrick will focus more on technical coding ...
Everyone I had the pleasure of interacting with enriched my summer in some way.
Today we’re very pleased to hear of the verdict finding Hissène Habré guilty of crimes against humanity. Habré, president of Chad from 1982 to 1990, has been sentenced to life in prison in Dakar, Senegal, where he was tried. He is the first former head of state to be tried and found guilty of crimes against humanity in one country (Chad) by the courts of another country (Senegal). Here’s more on the verdict from The Guardian.
The verdict resonates especially with HRDAG because of our role in the trial. In September 2015, director of research Patrick Ball testified as an expert witness about the very high rates of prison mortality in ...
Megan Price and Patrick Ball (2014). SAIS Review of International Affairs © 2014 The Johns Hopkins University Press. This article first appeared in SAIS Review, Volume 34, Issue 1, Winter-Spring 2014, pages 9-20. All rights reserved.
Carolina López, Beatriz Vejarano, and Megan Price. 2016. Human Rights Data Analysis Group. © 2016 HRDAG.Creative Commons BY-NC-SA.
"Revolution Analytics will allow HRDAG to handle bigger data sets and leverage the power of R to accomplish this goal and uncover the truth." Director of Research Megan Price is quoted.
REVOLUTION ANALYTICS
Press release
February 4, 2014
Link to press release
Back to Press Room
As we get ready to begin our fourth year as an independent nonprofit, we are, as always, indebted to our Advisory Board and to our funders for their support and vision. We’re finishing up a busy year that took us to Dakar (for the trial of former Chadian dictator Hissène Habré), Pristina (for the release of the Kosovo Memory Book), Colombia (for work on a book about the Guatemalan Police Archives), and kept us busy here at home working on police violence statistics. But one of our biggest victories has been to score a new, talented, wise Advisory Board member—Michael Bear Kleinman, whom we first met when he was working with Humanity United.
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In her work on statistical issues in criminal justice, Lum has studied uses of predictive policing—machine learning models to predict who will commit future crime or where it will occur. In her work, she has demonstrated that if the training data encodes historical patterns of racially disparate enforcement, predictions from software trained with this data will reinforce and—in some cases—amplify this bias. She also currently works on statistical issues related to criminal “risk assessment” models used to inform judicial decision-making. As part of this thread, she has developed statistical methods for removing sensitive information from training data, guaranteeing “fair” predictions with respect to sensitive variables such as race and gender. Lum is active in the fairness, accountability, and transparency (FAT) community and serves on the steering committee of FAT, a conference that brings together researchers and practitioners interested in fairness, accountability, and transparency in socio-technical systems.
One of the researchers, a Michigan State PhD candidate named William Isaac, had not previously heard of New Orleans’ partnership with Palantir, but he recognized the data-mapping model at the heart of the program. “I think the data they’re using, there are serious questions about its predictive power. We’ve seen very little about its ability to forecast violent crime,” Isaac said.
Today Amnesty International released “‘It breaks the human’: Torture, disease and death in Syria’s prisons ,” a report detailing the conditions and mortality in Syrian prisons from 2011 to 2015, including data analysis conducted by HRDAG.
The report provides harrowing accounts of ill treatment of detainees in Syrian prisons since the conflict erupted in March 2011, and publishes HRDAG’s estimate of the number of killings that occurred inside the prisons.
To accompany the report, HRDAG has released a technical memo that explains the methodology, sources, and implications of the findings. The HRDAG team used data from four ...
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 ...
Violence against women in all its forms is a human rights violation. Most of our HRDAG colleagues are women, and for us, unfortunately, recent campaigns such as #metoo are unsurprising.
In this
Granta article, HRDAG explains that neither the infectiousness nor the deadliness of the disease is set in stone.
HRDAG and our partners Data Cívica and the Iberoamericana University created a machine-learning model to predict which counties (municipios) in Mexico have the highest probability of unreported hidden graves. The predictions help advocates to bring public attention and government resources to search for the disappeared in the places where they are most likely to be found.
Context
For more than ten years, Mexican authorities have been discovering hidden graves (fosas clandestinas). The casualties are attributed broadly—and sometimes inaccurately—to the country’s “drug war,” but the motivations and perpetrators behind the mass murders ...
THis story might be about Racial Justice Act work with San Francisco Public Defender’s Office
