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Mexico

HRDAG and our partners Data Cívica and the Iberoamericana University created a machine-learning model to predict which counties (municipios) in Mexico have the highest probability of unreported hidden graves. The predictions help advocates to bring public attention and government resources to search for the disappeared in the places where they are most likely to be found. Context For more than ten years, Mexican authorities have been discovering hidden graves (fosas clandestinas). The casualties are attributed broadly—and sometimes inaccurately—to the country’s “drug war,” but the motivations and perpetrators behind the mass murders ...

Learning the Hard Way at the ICTY: Statistical Evidence of Human Rights Violations in an Adversarial Information Environment.

Amelia Hoover Green. In Collective Violence and International Criminal Justice: An Interdisciplinary Approach, ed. Alette Smeulers, Antwerp, Belgium. © 2010 Intersentia. All rights reserved. [Link coming soon]

Fourth CLS Story

THis story might be about Racial Justice Act work with San Francisco Public Defender’s Office

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 ...

Kristian Lum in Bloomberg

The interview poses questions about Lum's focus on artificial intelligence and its impact on predictive policing and sentencing programs.

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.

Nonprofits Are Taking a Wide-Eyed Look at What Data Could Do

In this story about how data are transforming the nonprofit world, Patrick Ball is quoted. Here's an excerpt: "Data can have a profound impact on certain problems, but nonprofits are kidding themselves if they think the data techniques used by corporations can be applied wholesale to social problems," says Patrick Ball, head of the nonprofit Human Rights Data Analysis Group. Companies, he says, maintain complete data sets. A business knows every product it made last year, when it sold, and to whom. Charities, he says, are a different story. "If you're looking at poverty or trafficking or homicide, we don't have all the data, and we're not going to," ...

Scanning Documents to Uncover Police Violence

Administrative paperwork generated by police departments can hold evidence of police violence, but can present unique challenges for data processing.

HRDAG Welcomes New Staff, Interns and Fellow

HRDAG is delighted to announce five additions to our team: one new staff member, three summer interns, and one fellow.

Evaluation of the Database of the Kosovo Memory Book

Jule Krüger and Patrick Ball (2014). An analysis accompanying the release of the Kosovo Memory Book. December 10, 2014. © 2014 HRDAG. Creative Commons BY-NC-SA.

Team Page

Featured Video

Kristian Lum, lead statistician at HRDAG | Predictive Policing: Bias In, Bias Out | 56 mins

Stay informed about our work

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Rapid response: Civilian deaths from weapons used in the Syrian conflict

Megan Price, Anita Gohdes, Jay D. Aronson, and Christopher McNaboe. 2015. BMJ (29 September): 351. doi: http://dx.doi.org/10.1136/bmj.h4736. © The BMJ Publishing Group Ltd. All rights reserved. Open access.

Low-risk population size estimates in the presence of capture heterogeneity

James Johndrow, Kristian Lum and Daniel Manrique-Vallier (2019). Low-risk population size estimates in the presence of capture heterogeneity. Biometrika, asy065, 22 January 2019. © 2019 Biometrika Trust. https://doi.org/10.1093/biomet/asy065

James Johndrow, Kristian Lum and Daniel Manrique-Vallier (2019). Low-risk population size estimates in the presence of capture heterogeneity. Biometrika, asy065, 22 January 2019. © 2019 Biometrika Trust. https://doi.org/10.1093/biomet/asy065

Using Statistics to Assess Lethal Violence in Civil and Inter-State War

Patrick Ball and Megan Price (2019). Using Statistics to Assess Lethal Violence in Civil and Inter-State War. Annual Review of Statistics and Its Application, Volume 6. 7 March 2019. © 2019 Annual Reviews. All rights reserved. https://doi.org/10.1146/annurev-statistics-030718-105222.

Patrick Ball and Megan Price (2019). Using Statistics to Assess Lethal Violence in Civil and Inter-State War. Annual Review of Statistics and Its Application. 7 March 2019. © 2019 Annual Reviews. All rights reserved. https://doi.org/10.1146/annurev-statistics-030718-105222.

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.

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 69, Issue 4, pages 1022–1032, December 2013. © 2013, The International Biometric Society. DOI: 10.1111/biom.12089.

The Atrocity Archives

Courts and police departments are turning to AI to reduce bias, but some argue it’ll make the problem worse

Kristian Lum: “The historical over-policing of minority communities has led to a disproportionate number of crimes being recorded by the police in those locations. Historical over-policing is then passed through the algorithm to justify the over-policing of those communities.”

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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