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From 2010 to 2012, a series of reports by HRDAG researchers applied new statistical methodologies to investigate deaths and missing people in Colombia. A 2010 report released by HRDAG scientists Tamy Guberek, Daniel Guzmán, Megan Price, Kristian Lum, and Patrick Ball documented patterns of violence in the Colombian state of Casanare. HRDAG researchers used MSE to analyze killings and disappearances recorded in 15 datasets provided by judicial, government, security, forensic and civil society organizations. Matching cases that appeared in more than one dataset, HRDAG statisticians modeled the process by which violations were recorded and estimated the ...
Patrick Ball expanded his use of multiple systems estimation (MSE) to clarify the history of a deadly conflict in Kosovo. The violence began in 1989 when Serbian President Slobodan Milošević revoked Kosovo's autonomous status within the Republic of Serbia triggering fighting between Kosovar Albanians and the Yugoslav government. Allegations of widespread and systematic human rights violations were made against Serbian forces and NATO intervened to repel Serb forces from Kosovo. Ball and Scheuren gathered data from Albanian border crossings and other sources in the region. They used this information to examine the claim by the Yugoslav government ...
Amelia Hoover Green and Patrick Ball (2019). Civilian killings and disappearances during civil war in El Salvador (1980–1992). Demographic Research, 1 October 2019. © 2019 Demographic Research. DOI: 10.4054/DemRes.2019.41.27
Amelia Hoover Green and Patrick Ball (2019). Civilian killings and disappearances during civil war in El Salvador (1980–1992). Demographic Research, 1 October 2019. © 2019 Demographic Research. DOI: 10.4054/DemRes.2019.41.27
Tamy Guberek and Margaret Hedstrom (2017). On or off the record? Detecting patterns of silence about death in Guatemala’s National Police Archive. Archival Science. 9 February 2017. © Springer. DOI 10.1007/s10502-017-9274-3.
Tamy Guberek and Margaret Hedstrom (2017). On or off the record? Detecting patterns of silence about death in Guatemala’s National Police Archive. Archival Science. 9 February 2017. © Springer. DOI 10.1007/s10502-017-9274-3.
Nick Cumming-Bruce of the New York Times writes about the UN Office of the High Commissioner of Human Right's release of HRDAG's third report on reported killings in the Syrian conflict.
From the article:
In its third report on Syria commissioned by the United Nations, the Human Rights Data Analysis Group identified 191,369 deaths from the start of the conflict in March 2011 to April 2014, more than double the 92,901 deaths cited in their last report, which covered the first two years of the conflict.
“Tragically, it is probably an underestimate of the real total number of people killed during the first three years of this murderous conflict,” ...
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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Today The Tor Project announced that it has elected a new Board of Directors, and among them is HRDAG executive director Megan Price. The Tor Project is a nonprofit advocacy group that promotes online privacy and provides software that helps users opt out of online tracking.
Megan and Patrick have long maintained that encryption and privacy are essential for enabling human rights work. Patrick's ideas are described in Monday's FedScoop story about encryption, human rights, and the U.S. State Department.
“Human rights groups depend on strong cryptography in order to hold governments accountable," says Patrick. "HRDAG depends on local human ...
The coding, from my perspective, is the heart of the project. I say this, because the coding team has the responsibility of selecting documents according to the random sample, recording the documents’ contents, and applying the criteria to convert that content into an entry in a quantitative database. Not to mention the fact that this team has the privilege of being in direct contact with the documents.
At present, because of advanced organizational processes, not everyone has a chance to hold an original document in their hands. The quantitative study had many advantages in this regard; since we started work in parallel with the archival ...
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 ...
Everyone I had the pleasure of interacting with enriched my summer in some way.
On October 23, 2018, Patrick Ball keynoted at the Open Source Summit in Edinburgh, Scotland.
Valentina Rozo Ángel has worked with HRDAG and the Colombian Truth Commission to acknowledge victims of the 50-year conflict who are not visible or easily counted.
Patrick Ball won the Karl E. Peace Award for Outstanding Statistical Contributions for the Betterment of Society at the 2018 Joint Statistical Meeting.
How we work with partners is how we relate to the whole human rights community. We work with human rights advocates and defenders to support their goals by complementing their substantive expertise with our technical expertise. To date, partners have included truth commissions, international criminal tribunals, United Nations missions, and non-governmental human rights organizations on five continents.
Here are a few stories that illustrate how we work with our partners:
HRDAG partner stories:
Quantifying Police Misconduct in Louisiana (2023)
Scraping for Pattern: Protecting Immigrant Rights in Washington State (2022)
Police Violence ...
Given a positive test result, what is the probability that an individual has antibodies? This HRDAG-authored
Granta article explains the science.
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.
“Kristian Lum… organized a workshop together with Elizabeth Bender, a staff attorney for the NY Legal Aid Society and former public defender, and Terrence Wilkerson, an innocent man who had been arrested and could not afford bail. Together, they shared first hand experience about the obstacles and inefficiencies that occur in the legal system, providing valuable context to the debate around COMPAS.”
“Usually, the thing you’re trying to predict in a lot of these cases is something like rearrest,” Lum said. “So even if we are perfectly able to predict that, we’re still left with the problem that the human or systemic or institutional biases are generating biased arrests. And so, you still have to contextualize even your 100 percent accuracy with is the data really measuring what you think it’s measuring? Is the data itself generated by a fair process?”
HRDAG Director of Research Patrick Ball, in agreement with Lum, argued that it’s perhaps more practical to move it away from bias at the individual level and instead call it bias at the institutional or structural level. If a police department, for example, is convinced it needs to police one neighborhood more than another, it’s not as relevant if that officer is a racist individual, he said.
At HRDAG, we worry about what we don't know. Specifically, we worry about how we can use statistical techniques to estimate homicides that are not observed by human rights groups. Based on what we've seen studying many conflicts over the last 25 years, what we don't know is often quite different from what we do know.
The technique we use most often to estimate what we don't know is called "multiple systems estimation." In this medium-technical post, I explain how to organize data and use three R packages to estimate unobserved events.
Click here for Computing Multiple Systems Estimation in R.
“If you’re not careful, you risk automating the exact same biases these programs are supposed to eliminate,” says Kristian Lum, the lead statistician at the San Francisco-based, non-profit Human Rights Data Analysis Group (HRDAG). Last year, Lum and a co-author showed that PredPol, a program for police departments that predicts hotspots where future crime might occur, could potentially get stuck in a feedback loop of over-policing majority black and brown neighbourhoods. The program was “learning” from previous crime reports. For Samuel Sinyangwe, a justice activist and policy researcher, this kind of approach is “especially nefarious” because police can say: “We’re not being biased, we’re just doing what the math tells us.” And the public perception might be that the algorithms are impartial.
