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The Limits of Observation for Understanding Mass Violence.

Megan Price and Patrick Ball. 2015. Canadian Journal of Law and Society / Revue Canadienne Droit et Société volume 30 issue 2 (June): 1-21. doi:10.1017/cls.2015.24. © Cambridge University Press. All rights reserved. Restricted access.

Using Machine Learning to Help Human Rights Investigators Sift Massive Datasets

How we built a model to search hundreds of thousands of text messages from the perpetrators of a human rights crime.

Why top funders back this small human rights organization with a global reach

Eric Sears, a director at the MacArthur Foundation who leads the grantmaker’s Technology in the Public Interest program, worked at Human Rights First and Amnesty International before joining MacArthur, and has been following HRDAG’s work for years. … One of HRDAG’s strengths is the long relationships it maintains with partners around the globe. “HRDAG is notable in that it really develops deep relationships and partnerships and trust with organizations and actors in different parts of the world,” Sears said. “I think they’re unique in the sense that they don’t parachute into a situation and do a project and leave. They tend to stick with organizations and with issues over the long term, and continually help build cases around evidence and documentation to ensure that when the day comes, when accountability is possible, the facts and the evidence are there.”


RustConf 2019, and systems programming as a data scientist

It could make sense to use Rust as a data journalist for in-browser computations, and other thoughts from RustConf.

La importancia de la estadística

Patrick Ball (2018). La importancia de la estadística. Ibero. La revista de la universidad Iberoamericana. August-September 2018. © 2018 Universidad Iberoamericana Ciudad de México. Pp. 50-51.

Patrick Ball (2018). La importancia de la estadística. Ibero. La revista de la universidad Iberoamericana. August-September 2018. © 2018 Universidad Iberoamericana Ciudad de México. Pp. 50-51.


Always Learning

The data science field is always changing, which means that I'll always be learning.

Learning to Learn: Reflections on My Time at HRDAG

So much of what I learned at HRDAG was intangible, and I'm grateful to have been able to go deep.

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.

Guatemalan Ex-Cops Get 40 Years for Labor Leader’s Slaying


Former Leader of Guatemala Is Guilty of Genocide Against Mayan Group


Reflections: Growing and Learning in Guatemala

As a woman, mother and sociologist who is curious about the patterns of our political past in Guatemala, I feel privileged to know and work with the HRDAG team. Collaborating and learning from people like Patrick, Megan, Suzanne, Beatriz and Tamy has been an invaluable gift. I have discovered many things, both human and academic. For example, I’ve learned new ways of seeing what seemed everyday and simple, to discover that not only do the social sciences and statistics work hand in hand, but that they are critical for understanding Guatemala’s reality. Twenty years ago, on 29 December, 1996, Guatemala made history by signing the Guatemala Peace ...

HRDAG and AHPN Launch Book Detailing Collaboration

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 ...

Theoretical limits of microclustering for record linkage

James E Johndrow, Kristian Lum and D B Dunson (2018). Theoretical limits of microclustering for record linkage. Biometrika. 19 March 2018. © 2018 Oxford University Press. DOI 10.1093/biomet/asy003.

John E Johndrow, Kristian Lum and D B Dunson (2018). Theoretical limits of microclustering for record linkage. Biometrika. 19 March 2018. © 2018 Oxford University Press. DOI 10.1093/biomet/asy003.


Pretrial Risk Assessment Tools

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.>>


Epidemiology has theories. We should study them.

With so many dashboards and shiny visualizations, how can an interested non-technical reader find good science among the noise?

Measures of Fairness for New York City’s Supervised Release Risk Assessment Tool

Kristian Lum and Tarak Shah (2019). Measures of Fairness for New York City's Supervised Release Risk Assessment Tool. Human Rights Data Analysis Group. 1 October 2019. © HRDAG 2019.

Kristian Lum and Tarak Shah (2019). Measures of Fairness for New York City’s Supervised Release Risk Assessment Tool. Human Rights Data Analysis Group. 1 October 2019. © HRDAG 2019.


Crean sistema para predecir fosas clandestinas en México

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.


Violence in Blue: The 2020 Update

HRDAG has refreshed a 2016 Granta article about homicides committed by police in the United States.

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 Day by Day: Quantitative Research at the AHPN

Working at the Historic Archive of the National Police (AHPN) of Guatemala, there are many skills I learned on the job. My many years of work on the team that studies the recovered documents have been like a custom-made course in how to do quantitative research. The Archive documents I study are the result of 36 years of creation during civil war (1960 to 1996). Many of these documents are simply administrative—but we are able to use them to understand patterns that occurred during the conflict, to get a sense of what mattered to the National Police and what didn’t. Our quantitative research shows us the Police behavior in broad strokes. ...

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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