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The Allegheny Family Screening Tool’s Overestimation of Utility and Risk

Anjana Samant, Noam Shemtov, Kath Xu, Sophie Beiers, Marissa Gerchick, Ana Gutierrez, Aaron Horowitz, Tobi Jegede, Tarak Shah (2023). The Allegheny Family Screening Tool’s Overestimation of Utility and Risk. Logic(s). 13 December, 2023. Issue 20.

Anjana Samant, Noam Shemtov, Kath Xu, Sophie Beiers, Marissa Gerchick, Ana Gutierrez, Aaron Horowitz, Tobi Jegede, Tarak Shah (2023). The Allegheny Family Screening Tool’s Overestimation of Utility and Risk. Logic(s). 13 December, 2023. Issue 20.


Featured Video

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

Podcast: Dr. Patrick Ball on Using Statistics to Uncover Truth

Dr. Patrick Ball recently visited the Plutopia News Network podcast for a wide-ranging, inspiring conversation about his work for the Human Rights Data Analysis Group. Patrick spoke about how he first discovered human rights work during his time in El Salvador with the Peace Brigades International.  That led to his ongoing work as a statistician and computer programmer working to assess and analyze human rights violations. He also unpacked some common statistical techniques used by researchers at Human Rights Data Analysis Group, such as multiple systems estimation, which uses multiple different datasets to gain insights into the data we don't ...

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Preliminary Statistical Analysis of Documentation of Killings in the Syrian Arab Republic.

Megan Price, Jeff Klingner, and Patrick Ball (2013). The Benetech Human Rights Program, commissioned by the United Nations Office of the High Commissioner for Human Rights (OHCHR). January 2, 2013. © 2013 HRDAG. Creative Commons BY-NC-SA.


Statistics and Slobodan

Patrick Ball and Jana Asher (2002). “Statistics and Slobodan: Using Data Analysis and Statistics in the War Crimes Trial of Former President Milosevic.” Chance, vol. 15, No. 4, 2002. Reprinted with permission ofChance. © 2002 American Statistical Association. All rights reserved.


Technical Memo for Amnesty International Report on Deaths in Detention

Megan Price, Anita Gohdes and Patrick Ball (2016). Human Rights Data Analysis Group, commissioned by Amnesty International. August 17, 2016. © 2016 HRDAG. Creative Commons BY-NC-SA.


Uncertainty in COVID Fatality Rates

In this Granta article, HRDAG explains that neither the infectiousness nor the deadliness of the disease is set in stone.

Welcoming Our New Statistician

Maria Gargiulo has joined HRDAG as a Statistician.

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.

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]


Quantifying Injustice

“In 2016, two researchers, the statistician Kristian Lum and the political scientist William Isaac, set out to measure the bias in predictive policing algorithms. They chose as their example a program called PredPol.  … Lum and Isaac faced a conundrum: if official data on crimes is biased, how can you test a crime prediction model? To solve this technique, they turned to a technique used in statistics and machine learning called the synthetic population.”


At Toronto’s Tamil Fest, human rights group seeks data on Sri Lanka’s civil war casualties

Earlier this year, the Canadian Tamil Congress connected with HRDAG to bring its campaign to Toronto’s annual Tamil Fest, one of the largest gatherings of Canada’s Sri Lankan diaspora.

Ravichandradeva, along with a few other volunteers, spent the weekend speaking with festival-goers in Scarborough about the project and encouraging them to come forward with information about deceased or missing loved ones and friends.

“The idea is to collect thorough, scientifically rigorous numbers on the total casualties in the war and present them as a non-partisan, independent organization,” said Michelle Dukich, a data consultant with HRDAG.


Data Mining for Good: CJA Drink + Think

At the Center for Justice and Accountability's happy hour, "Drink and Think," Patrick Ball spoke about "Data Mining for Good." The talk included a discussion of how HRDAG brings human rights abusers to justice through data analysis, and HRDAG's work conducting quantitative analysis for truth commissions, NGOs, the UN and other partners. The event was held at Eventbrite. More photos are below. The Center for Justice and Accountability Young Professionals' Committee for Human Rights September 16, 2014 San Francisco, California Link to CJA event page Back to Talks   All photos © 2014 Carter Brooks.

Estimating the Number of SARS-CoV-2 Infections and the Impact of Mitigation Policies

This Harvard Data Science Review article uses the least unreliable source of pandemic data: reported deaths.

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.


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.


Limitations of mitigating judicial bias with machine learning

Kristian Lum (2017). Limitations of mitigating judicial bias with machine learning. Nature. 26 June 2017. © 2017 Macmillan Publishers Limited, part of Springer Nature. All rights reserved. Nature Human Behavior. DOI 10.1038/s41562-017-0141. .

Kristian Lum (2017). Limitations of mitigating judicial bias with machine learning. Nature. 26 June 2017. © 2017 Macmillan Publishers Limited, part of Springer Nature. All rights reserved. Nature Human Behavior. DOI 10.1038/s41562-017-0141.


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 heterogeneityBiometrika, asy065, 22 January 2019. © 2019 Biometrika Trust. https://doi.org/10.1093/biomet/asy065


A Model to Estimate SARS-CoV-2-Positive Americans

We’ve built a model for estimating the true number of positives, using what we have determined to be the most reliable datasets—deaths.

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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