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About HRDAG

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 Comparison of Marginal and Conditional Models for Capture–Recapture Data with Application to Human Rights Violations Data

Shira Mitchell, Al Ozonoff, Alan Zaslavsky, Bethany Hedt-Gauthier, Kristian Lum and Brent Coull (2013). A Comparison of Marginal and Conditional Models for Capture-Recapture Data with Application to Human Rights Violations Data. Biometrics, Volume 69, Issue 4, pages 1022–1032, December 2013. © 2013, The International Biometric Society. DOI: 10.1111/biom.12089.

Shira Mitchell, Al Ozonoff, Alan Zaslavsky, Bethany Hedt-Gauthier, Kristian Lum and Brent Coull (2013). A Comparison of Marginal and Conditional Models for Capture-Recapture Data with Application to Human Rights Violations Data. Biometrics, Volume 69Issue 4pages 1022–1032December 2013. © 2013, The International Biometric Society. DOI: 10.1111/biom.12089.


HRDAG and #GivingTuesday 2017

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USA

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 many social movement leaders have been killed in Colombia? An estimate and analysis

As the war between the guerrillas, the Army, and paramilitary groups in Colombia winds down, violence against social movement leaders has intensified. Using data from six organizations, this report estimates the total number of social movement leaders killed in 2016 and 2017. The perpetrators of the killings are not reported in the data or in the report. In the report, we observe that together, the monitoring organizations documented 160 killings in 2016, and we estimate a total population of 166 deaths.[1] In 2017, there were 172 documented killings, and we estimate a total of 185 deaths.[2] From this, we conclude that the number of killings is ...

HRDAG Wins the Rafto Prize

The Rafto Foundation, an international human rights organization, has bestowed the 2021 Rafto Prize to HRDAG for its distinguished work defending human rights and democracy.

HRDAG Names New Board Member Margot Gerritsen

Margot is a professor in the Department of Energy Resources Engineering at Stanford University, interested in computer simulation and mathematical analysis of engineering processes.

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...

Contact Us

You may contact us via info @ hrdag.org or use this form. Would you like to receive our newsletter? Great! Please sign up here. Find us on Mastodon Follow HRDAG on Mastodon. Employment with HRDAG Please keep in touch by signing up for our newsletters and following us on Twitter @hrdag or Mastodon. If you do not see a job listed here, please do not send your CV or résumé, as we do not file or save them, and we will only have to send you a sad “no thank you” letter. Volunteering with HRDAG Are you interested in volunteering your time to the Human Rights Data Analysis Group? We’re very flattered—but at this time we’re ...

Innocence Discovery Lab – Harnessing Large Language Models to Surface Data Buried in Wrongful Conviction Case Documents

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. https://doi.org/10.29173/wclawr112. 31 May, 2024. Copyright (c) 2024 Ayyub Ibrahim, Huy Dao, Tarak Shah. 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. https://doi.org/10.29173/wclawr112. 31 May, 2024. Copyright (c) 2024 Ayyub Ibrahim, Huy Dao, Tarak Shah. Creative Commons Attribution 4.0 International License.


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

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.

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.


How Predictive Policing Reinforces Bias

Algorithmic tools like PredPol were supposed to reduce bias. But HRDAG has found that racial bias is baked into the data used to train the tools.

Rise of the racist robots – how AI is learning all our worst impulses

“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.


Learning a Modular, Auditable and Reproducible Workflow

The modular nature of the workflow and use of Git allowed us to work on different parts of the project from across the country.

Primer to Inform Discussions about Bail Reform

The primer addresses what pretrial risk assessment is and what the research supports.

How we make sure that nobody is counted twice: A peek into HRDAG's record de-duplication

HRDAG is currently evaluating the quality and completeness of the Kosovo Memory Book of the Humanitarian Law Center (HLC) in Belgrade, Serbia. The objective of the Kosovo Memory Book (KMB) is to commemorate every single person who fell victim to armed conflict in Kosovo from 1998 to 2000, either through death or disappearance. While building and reviewing their database, one of the things that HLC has to do is “record linkage,” a process also known as “matching.” Matching determines whether two records are the same people (“a match”) or different people (“a non-match”). Matching helps to identify whether two existing records refer ...

HRDAG’s Year in Review: 2020

In 2020, HRDAG provided clarity on issues related to the pandemic, police misconduct, and more.

How Review of Police Data Verified Neglect of Missing Black Women

Sloppy recordkeeping by Chicago police has compromised missing persons cases. HRDAG is working with Pulitzer Prize-winning Invisible Institute to find justice for the missing.

How Many People Will Get Covid-19?

HRDAG has authored two articles in Significance that add depth to discussions around infection rates.

Casanare, Colombia

Text in English [popup citation="Tamy Guberek, Daniel Guzmán, Megan Price, Kristian Lum and Patrick Ball. (2010). Benetech/Human Rights Data Analysis Group database of lethal violence in Casanare."] Estimaciones de Homicidios y Desapariciones en Casanare Casanare es un departamento extenso y rural de Colombia con 19 municipios y una población de casi 300.000 habitantes. Ubicado entre las faldas de los Andes y las planicies orientales, Casanare tiene una larga historia de violencia. Diversos grupos armados han hecho presencia en Casanare, entre ellos paramilitares, guerrillas y el ejército colombiano. Muchos habitantes del Casanare han sido vícti...

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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