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How We Choose Projects

For more than 20 years, HRDAG has been carving out a niche in the international human rights movement. We know what we’re good at and what we’re not qualified to do. We know what quantitative questions we think are important for the community, and we know what we like to do. These preferences guide us as we consider whether to take on a project. We’re scientists, so our priorities will come as no surprise. We like to stick to science (not ideology), avoid advocacy, answer quantifiable questions, and increase our scientific understanding. While we have no hard-and-fast rules about what projects to take on, we organize our deliberation ...

Welcoming a New Board Member

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. ...

Mortality in the DDS Prisons in Chad, 1985–1988

Patrick Ball (2014). Human Rights Data Analysis Group. August 22, 2014. © 2014 HRDAG. Creative Commons BY-NC-SA.

Using Data to Reveal Human Rights Abuses

Profile touching on HRDAG’s work on the trial and conviction of Hissène Habré, its US Policing Project, data integrity, data archaeology and more.

Accountability at home and abroad

  Dear friends, Our spirits were really on the ground on Wednesday, but they lifted at the board meeting we had at the Human Rights Data Analysis Group on Thursday. Executive Director Megan Price, Director of Research Patrick Ball, and the Board drafted these thoughts which we'd like to share with you. For more than twenty-five years, we have held heads of state accountable for human rights violations. We support our partners and advocates in the human rights field. They collect data which we analyze using technical and scientific expertise. Those scientific results bring clarity to human rights violence and support the fight for justice. ...

Letter from the Executive Director

Dear Friends, This has been quite a year, and I don’t just mean the recent political events in the United States, Europe and the Middle East. Thanks to your ongoing support, HRDAG has a number of accomplishments to be proud of this year: Patrick’s testimony in the trial of Hissene Habré for crimes against humanity was cited by the judges three times in their determination of guilt. We launched a book describing ten years of collaborative work with the Historic Archive of the National Police in Guatemala. We contributed quantitative analyses to Amnesty International’s report on deaths in Syrian custody, and published an ...

Where Stats and Rights Thrive Together

Everyone I had the pleasure of interacting with enriched my summer in some way.

HRDAG and #GivingTuesday 2018

Will you help HRDAG advance human rights?

Update on Work in Guatemala and the AHPN

HRDAG has sampled and analyzed documents at Guatemala's AHPN and has testified against war criminals based on that analysis.

La estadística de mortalidad del conflicto en Perú

En ese artículo respondemos a una crítica del estudio de mortalidad que realizamos para la Comisión de la Verdad y Reconciliación en 2003.

HRDAG Retreat 2022

A week in the California redwoods amongst a hodgepodge of people united by their passion for using quantitative analysis to combat injustice.

Letter from Alejandro Valencia Villa

Alejandro Valencia Villa is a Former Commissioner of the Colombian Truth Commission. (Letter in English, and letter in Spanish.) Introduction One of the most obvious and most difficult questions to answer when analyzing an armed conflict is determining the number of victims. In a conflict like Colombia’s, prolonged and with complex characteristics due to the different nature of the armed actors and because they committed a great variety and quantity of human rights violations and breaches of humanitarian law, the challenge is even greater. As if this were not enough, Colombia also had a large number of records of these violations and infract...

How public involvement can improve the science of AI

Proceedings of the National Academy of Sciences of the United States of America

As AI systems from decision-making algorithms to generative AI are deployed more widely, computer scientists and social scientists alike are being called on to provide trustworthy quantitative evaluations of AI safety and reliability. These calls have included demands from affected parties to be given a seat at the table of AI evaluation. What, if anything, can public involvement add to the science of AI? In this perspective, we summarize the sociotechnical challenge of evaluating AI systems, which often adapt to multiple layers of social context that shape their outcomes. We then offer guidance for improving the science of AI by engaging lived-experience experts in the design, data collection, and interpretation of scientific evaluations.

Nathan Matias and Megan Price (2025). How public involvement can improve the science of AI. Proceedings of the National Academy of Sciences of the United States of America, Vol. 122, No. 48. 14 November, 2025. © 2025 National Academy of Sciences. https://doi.org/10.1073/pnas.2421111122

Watch Now: What is a structural zero?

“If we wait for data to be perfect, we’ll be waiting forever.” Statistician Maria Gargiulo explains how researchers use multiple systems estimation to measure hidden victims of armed conflict and political violence.

verdata: An R package for analyzing data from the Truth Commission in Colombia

The Journal of Open Source Software

The data compiled by the joint JEP-CEV-HRDAG project are publicly available from the Departamento Administrativo Nacional de Estadística (DANE). The data published by DANE is available in a format that may not be familiar to researchers who have not previously worked with statistical imputation methods. Recognizing this, verdata was created to support researchers in responsibly and correctly using the data despite the potential unfamiliarity of its structure. Researchers can use verdata to verify that the data files they are using in their analyses have not been altered, to replicate the main findings of the technical appendix, and to design new analyses of the conflict in Colombia.

Creative Commons Attribution 4.0 International License.

Maria Gargiulo, María Julia Durán, Paula Andrea Amado, and Patrick Ball (2024). verdata: An R package for analyzing data from the Truth Commission in Colombia. The Journal of Open Source Software. 6 January, 2024. 9(93), 5844, https://doi.org/10.21105/joss.05844. Creative Commons Attribution 4.0 International License.

Innocence Discovery Lab – Harnessing large language models to surface data buried in wrongful conviction case documents

The Wrongful Conviction Law Review

The recent advent of commercial artificial intelligence (AI), especially in natural language processing (NLP), introduces transformative possibilities for wrongful conviction research. NLP, a pivotal branch of AI that forms the basis for Large Language Models (LLMs), enables computers to interpret human language with a nuanced understanding. This technological advancement is particularly valuable for analyzing the complex language found in case documents associated with wrongful convictions. This paper explores the effectiveness of LLMs in analyzing and extracting data from case documents collected by the Innocence Project New Orleans and the National Registry of Exonerations. The diverse and comprehensive nature of these datasets makes them ideal for assessing the capabilities of LLMs. The findings of this study advance our understanding of how LLMs can be utilized to make wrongful conviction case documents easily accessible by automating the extraction of relevant data.

Creative Commons Attribution 4.0 International License.

Ayyub Ibrahim, Huy Dao, and Tarak Shah (2024). Innocence Discovery Lab – Harnessing Large Language Models to Surface Data Buried in Wrongful Conviction Case Documents. The Wrongful Conviction Law Review 5 (1):103-25. 31 May, 2024. https://doi.org/10.29173/wclawr112. ©  2024 Ayyub Ibrahim, Huy Dao, Tarak Shah.

The use of unstructured data to study police use of force

CHANCE magazine

The challenges and opportunities researchers face when working with unstructured data are hardly new. This article defines unstructured data as data that is not organized according to pre-existing schemas or structures for the sake of statistical analysis. Unstructured data poses a unique challenge for researchers focused on police and policing. The article discusses a definition of unstructured data and two of the primary challenges faced when working with such data, namely information extraction and classification problems. Two case studies are used to illuminate the challenges.

Tarak Shah, Cristian Allen, Ayyub Ibrahim, Harlan Kefalas, and Bavo Stevens (2024). The Use of Unstructured Data to Study Police Use of Force. 5 December, 2024. CHANCE, 37 (4), 18–23. © The American Statistical Association (ASA) and Taylor & Francis Group 2024. https://doi.org/10.1080/09332480.2024.2434437

Shots fired: Can technology really keep us safe from gunfire?

Significance

An expensive American gunshot detection system claims it’s necessary because humans don’t always call the police to report gunfire. But opponents say it’s fatally flawed. To investigate, Bailey Passmore and Larry Barrett analysed data on emergencies within the city of Chicago.

Bailey Passmore and Larry Barrett (2025). Shots fired: Can technology really keep us safe from gunfire? Significance, Volume 22, Issue 4, July 2025, Pages 34–37. 27 May 2025. © Royal Statistical Society 2025. https://doi.org/10.1093/jrssig/qmaf042

Dictatorships create a lot of data

Structural Zero Issue 01 Jun 03, 2025 Part One of Our Three Part “Gathering the Data” Series As a statistician, I spend most days trying to wrangle and analyze massive data sets. The specific data I deal with is documentation of human rights violations. My job is to make sense of data that I know is incomplete and answer questions about the past using statistical analysis and scientific reasoning. But where does this data come from? How was it generated, and how do human rights advocates and researchers access it and secure it? To kick off our new newsletter Structural Zero, I’ll be writing a ...

Yes, Your Dataset is Probably Biased

As statisticians, we bring skepticism to every dataset and every conclusion. When we make conclusions about a research topic, we offer up our evidence, reasoning, and calculations for review. Most importantly, we talk about the degree of confidence we have in our findings and how we can use scientific models to improve that confidence. 

Our work has been used by truth commissions, international criminal tribunals, and non-governmental human rights organizations. We have worked with partners on projects on five continents.

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