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Patrick Ball (2016). The case against a golden key. Foreign Affairs. September 14, 2016. ©2016 Council on Foreign Relations, Inc. All Rights Reserved.
Patrick Ball (2016). The case against a golden key. Foreign Affairs. September 14, 2016. ©2016 Council on Foreign Relations, Inc. All Rights Reserved.
HRDAG’s funding comes from private, international donors: the John D. and Catherine T. MacArthur Foundation, Open Society Foundations, an anonymous U.S.-based private foundation, Ford Foundation, The National Endowment for Democracy and individual donors. This funding supports both specific projects, as well as our scientific work generally in human rights data analysis.
For the entirety of its existence, HRDAG has been a project of non-profit organizations, first at the American Association for the Advancement of Science (AAAS), and then at Benetech, a non-profit Silicon Valley technology company. In February 2013, HRDAG became ...
As of today, the Human Rights Data Analysis Group (HRDAG) is an independent* non-profit! It's been a long time coming, and we're delighted to have gotten to this point. HRDAG is a non-profit, non-partisan organization that applies rigorous science to the analysis of human rights violations around the world; for more information, see our About Us page.
Benetech has spun out the scientific and statistical part of the Human Rights Program to HRDAG. The spinout includes (as staff) me -- Patrick Ball -- and Dr Megan Price, as well as our many part-time scientific and field consultants (a list is here). The software and technology component of our work -- ...
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.
“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.
In 2014 and again in 2020, the Invisible Institute, a Chicago grassroots organization, won lawsuits that granted them access to decades of complaints of misconduct by Chicago police officers. The collection contains hundreds of thousands of pages of allegation forms, memos, various police administrative forms, interviews and testimonies, pictures, and even embedded audio files. The Institute published scanned images on the Citizens Police Data Project, and is using them for a project with HRDAG known as Beneath the Surface, which is a detailed investigation into gender-based violence by Chicago Police.
Image: David Peters
Often, gender-b...
Sarah L. Desmarais and Evan M. Lowder (2019). Pretrial Risk Assessment Tools: A Primer for Judges, Prosecutors, and Defense Attorneys. Safety and Justice Challenge, February 2019. © 2019 Safety and Justice Challenge. <<HRDAG's Kristian Lum and Tarak Shah served as Project Members and made contributions to the primer.>>
Sarah L. Desmarais and Evan M. Lowder (2019). Pretrial Risk Assessment Tools: A Primer for Judges, Prosecutors, and Defense Attorneys. Safety and Justice Challenge, February 2019. © 2019 Safety and Justice Challenge. <<HRDAG’s Kristian Lum and Tarak Shah served as Project Members and made significant contributions to the primer.>>
HRDAG is helping the Invisible Institute turn their windfall of raw data about police misconduct into data that can be analyzed.
Por ello, Human Rights Data Analysis Group (HRDAG), el Programa de Derechos Humanos de la Universidad Iberoamericana (UIA) y Data Cívica, realizan un análisis estadístico construido a partir de una variable en la que se identifican fosas clandestinas a partir de búsquedas automatizadas en medios locales y nacionales, y usando datos geográficos y sociodemográficos.
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...
“The model uses obvious predictor variables, Ball says, such as whether or not a drug lab has been busted in that county, or if the county borders the United States, or the ocean, but also includes less-obvious predictor variables such as the percentage of the county that is mountainous, the presence of highways, and the academic results of primary and secondary school students in the county.”
El modelo “puede distinguir entre los municipios en que vamos a encontrar fosas clandestinas, y en los que es improbable que vayamos a encontrar estas fosas”, explicó Patrick Ball, estadístico estadounidense que colabora con el Programa de Derechos Humanos de la Universidad Iberoamericana de la Ciudad de México.
Illuminating Data's Dark Side: Big data create conveniences, but we must consider who designs these tools, who benefits from them, and who is left out of the equation.
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 ...
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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Everyone I had the pleasure of interacting with enriched my summer in some way.
For years I have been engaged in a quantitative study at Guatemala’s Historic Archive of the National Police, or AHPN. (See the blogposts below.) In this study coders collect data on sheets of paper according to criteria established and explained in manuals. But when collecting data, there’s always room for human error—this is why the validity of the study hinges on verifying that coders use the correct criteria.
It is important to mention that the mainstay of coding is the use of a controlled vocabulary. A controlled vocabulary gives analysts a framework, or frame of reference, when converting qualitative information into categories ...
Last week Forensis, the Colombian National Institute of Forensic Medicine’s flagship publication, published the first of our analyses of homicide patterns in Colombia. Authored by HRDAG executive director Patrick Ball and UN colleague Michael Reed Hurtado, “Cuentas y mediciones de la criminalidad y de la violencia” (pages 529-545) explores, as the title suggests, the quality of “truth” contained within crime registries. Citing the problem of partial data, missing data, and inherent design bias, Patrick and Michael write that no register, official or unofficial, can present a true reflection of what has really happened.
This publication...
I spent last weekend in Istanbul at an excellent conference organized by the Syrian Center for Political and Strategic Studies (SCPSS). The conference included numerous non-governmental organizations (NGOs) from Syria as well as international human rights researchers and advocates. Families of victims told their stories, data collection groups discussed the challenges, and need, to document violations, transitional justice experts worried about infrastructure such as the police force and judicial system, and local leaders pledged to work together for peace.
I was invited to speak about HRDAG's recent report examining killings in Syria documented by ...
