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HRDAG’s core values all have a connection to Scott Weikart, 1951–2023.
2021 Rafto Prize Videos
.ugb-8203b62 .ugb-video-popup__wrapper{height:460px !important;background-color:#000000;background-image:url(https://hrdag.org/wp-content/uploads/2022/12/Screen-Shot-2022-12-09-at-3.41.30-PM.png)}.ugb-8203b62 .ugb-video-popup__wrapper:before{background-color:#000000;opacity:0.3}.ugb-8203b62 .ugb-video-popup__wrapper:hover:before{opacity:0.6}.ugb-8203b62 .ugb-block-title{color:#ffffff}.ugb-8203b62 .ugb-block-description{color:#ffffff}@media screen and (max-width:768px){.ugb-8203b62 .ugb-video-popup__wrapper{height:208px !important}}The Rafto Prize 2021 | Rafto Foundation Rafto Foundation | HRDAG team | 2021 | 4 min
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Identifiers being sequential could make possible estimations of the population of detained children.
This rigorous estimate shows that 1-2 percent of the country’s population was killed or disappeared during the civil war.
The World According to Artificial Intelligence: Targeted by Algorithm (Part 1)
The Big Picture: The World According to AI explores how artificial intelligence is being used today, and what it means to those on its receiving end.
Patrick Ball is interviewed: “Machine learning is pretty good at finding elements out of a huge pool of non-elements… But we’ll get a lot of false positives along the way.”
HRDAG has sampled and analyzed documents at Guatemala's AHPN and has testified against war criminals based on that analysis.
Ball, a statistician, has spent the last two decades finding ways to make the silence speak. He helped pioneer the use of formal statistical modeling, and, later, machine learning—tools more often used for e-commerce or digital marketing—to measure human rights violations that weren’t recorded. In Guatemala, his analysis helped convict former dictator General Efraín Ríos Montt of genocide in 2013. It was the first time a former head of state was found guilty of the crime in his own country.
There may have been more undocumented World War II-era Korean "comfort women" than known.
Shemika Lamare has joined the HRDAG team as our new data science fellow.
Earlier this month, HRDAG and the Historic Archive of the National Police (AHPN) of Guatemala launched a book that represents a long-time collaboration between the two organizations. The book, “Una mirada al AHPN a partir de un studio de cuantitativo,” is, as the title states, a look at the Archive’s datasets via a quantitative study. Book authors are HRDAG executive director Megan Price and AHPN colleague Carolina López, with translations by Beatriz Vejarano. The book is available in Spanish and forthcoming in English.
The book explains how HRDAG and the Archive worked together over a decade to gain insight into the police activities that ...
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 ...
HRDAG’s analysis and expertise continues to deepen the national conversation about police violence and criminal justice reform in the United States. In 2015 we began by considering undocumented victims of police violence, relying on the same methodological approach we’ve tested internationally for decades. Shortly after, we examined “predictive policing” software, and demonstrated the ways that racial bias is baked into the algorithms. Following our partners’ lead, we next considered the impact of bail, and found that setting bail increases the likelihood of a defendant being found guilty. We then broadened our investigations to examine ...
How might we learn what we don’t know? HRDAG associate Christine Grillo hits the wayback machine and recalls her first exposure to People Against Bad Things, ideas about bias and correlation versus causation, and truth.
The first time I met anyone at HRDAG, I was a journalist. It was 2006. I was working on a story about a graduate student at Carnegie Mellon who’d collaborated with the organization on a survey in Sierra Leone, and I contacted Patrick Ball to discuss the work. At the time, I found him challenging.
But I thought his work—trying to estimate how many people were killed, or, in that study, otherwise injured, during wars—was fascinating. Over the next few years, I got to know other researchers working on similar questions. In 2008, as the war in Iraq ramped up, I spoke with epidemiologists from Johns Hopkins University, the World Health Organiz...
“Patrick Ball, HRDAG’s Director of Research and the statistician behind the code, explained that the Random Forest classifier was able to predict with 100% accuracy which counties that would go on to have mass graves found in them in 2014 by using the model against data from 2013. The model also predicted the counties that did not have mass hidden graves found in them, but that show a high likelihood of the possibility. This prediction aspect of the model is the part that holds the most potential for future research.”
For more than 10 years, and with regularity, Mexican authorities have been discovering mass graves, known as fosas clandestinas, in which hundreds of bodies and piles of bones have been found. The casualties are attributed broadly to the country’s “drug war,” although the motivations and perpetrators behind the mass murders are often unknown.
Recently, HRDAG collaborated with two partners in Mexico—Data Cívica and Programa de Derechos Humanos of the Universidad Iberoamericana—to model the probability of identifying a hidden grave in each county (municipio). The model uses an set of independent variables and data about graves from 2013 ...
Kristian Lum and William Isaac (2016). To predict and serve? Significance. October 10, 2016. © 2016 The Royal Statistical Society.
Kristian Lum and William Isaac (2016). To predict and serve? Significance. October 10, 2016. © 2016 The Royal Statistical Society.
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 ...
Daniel Guzmán, Tamy Guberek, Amelia Hoover, and Patrick Ball (2007). “Missing People in Casanare.” Benetech. Also available in Spanish – “Los Desaparecidos de Casanare.”
