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The UDHR Turns 70

We're thinking about how rigorous analysis can fortify debates about components of our criminal justice system such as cash bail, pretrial risk assessment and fairness in general.

Multiple Systems Estimation: Stratification and Estimation

<< Previous post, MSE: The Matching Process Q10. What is stratification? Q11. [In depth] How do HRDAG analysts approach stratification, and why is it important? Q12. How does MSE find the total number of violations? Q13. [In depth] What are the assumptions of two-system MSE (capture-recapture)? Why are they not necessary with three or more systems? Q14. What statistical model(s) does HRDAG typically use to calculate MSE estimates? (more…)

When Data Doesn’t Tell the Whole Story

This blog is a part of International Justice Monitor’s technology for truth series, which focuses on the use of technology for evidence and features views from key proponents in the field. As highlighted by other posts in this series, emerging technology is increasing the amount and type of information available, in some contexts, to criminal and other investigations. Much of what is produced by these emerging technologies (Facebook posts, tweets, YouTube videos, text messages) falls in the category we refer to as “found” data. By “found” data we mean data not generated for a specific investigation, but instead, that is generated for ...

Multiple Systems Estimation: Collection, Cleaning and Canonicalization of Data

<< Previous post: MSE: The Basics Q3. What are the steps in an MSE analysis? Q4. What does data collection look like in the human rights context? What kind of data do you collect? Q5. [In depth] Do you include unnamed or anonymous victims in the matching process? Q6. What do you mean by "cleaning" and "canonicalization?" Q7. [In depth] What are some of the challenges of canonicalization? (more…)

Here’s how an AI tool may flag parents with disabilities

HRDAG contributed to work by the ACLU showing that a predictive tool used to guide responses to alleged child neglect may forever flag parents with disabilities. “These predictors have the effect of casting permanent suspicion and offer no means of recourse for families marked by these indicators,” according to the analysis from researchers at the ACLU and the nonprofit Human Rights Data Analysis Group. “They are forever seen as riskier to their children.”


Data-driven crime prediction fails to erase human bias

Work by HRDAG researchers Kristian Lum and William Isaac is cited in this article about the Policing Project: “While this bias knows no color or socioeconomic class, Lum and her HRDAG colleague William Isaac demonstrate that it can lead to policing that unfairly targets minorities and those living in poorer neighborhoods.”


Press Release, Timor-Leste, November 2006

Palo Alto, CA, November 12, 2006 –The Benetech® Initiative congratulates the Commission for Reception, Truth and Reconciliation (CAVR) and the Timorese people for the official release of the CAVR's final report Chega! in Australia today. The 2,500 page report uncovers previously unknown findings about past human rights abuses in Timor-Leste between 1974 and 1999. In particular, the report uncovers widespread and systematic human rights violations in Timor-Leste during the period 1974-1999. Benetech's statistical analysis establishes that at least 102,800 (+/- 11,000) Timorese died as a result of the conflict. Approximately 18,600 (+/- 1000) ...

Liberia 2009 – Coding Testimony to Determine Accountability for War Crimes

In July 2009, HRDAG concluded a three-year project with the Liberian Truth and Reconciliation Commission (TRC) to help clarify Liberia’s violent history and hold perpetrators accountable. A military coup in 1979 sparked 24 years of civil war in Liberia where warring factions subjected civilians to severe human rights abuses. The TRC sought to determine whether these violations represented a systematic pattern or policy. This chapter describes how HRDAG developed a statistical analysis of the more than 17,000 victim and witness statements collected by the TRC and applied Ball’s “Who Did What To Whom?” methodology. HRDAG scientist Kristen ...

100 Women in AI Ethics

We live in very challenging times. The pervasiveness of bias in AI algorithms and autonomous “killer” robots looming on the horizon, all necessitate an open discussion and immediate action to address the perils of unchecked AI. The decisions we make today will determine the fate of future generations. Please follow these amazing women and support their work so we can make faster meaningful progress towards a world with safe, beneficial AI that will help and not hurt the future of humanity.

53. Kristian Lum @kldivergence


Open Source Summit 2018

On October 23, 2018, Patrick Ball keynoted at the Open Source Summit in Edinburgh, Scotland.

SermonNew death toll estimated in Syrian civil war

Kevin Uhrmacher of the Washington Post prepared a graph that illustrates reported deaths over time, by number of organizations reporting the deaths.


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.”


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

James Johndrow, Patrick Ball, Maria Gargiulo, and Kristian Lum. (2020). Estimating the Number of SARS-CoV-2 Infections and the Impact of Mitigation Policies in the United States. Harvard Data Science Review. 24 November, 2020. © The Authors, 2020, CC BY 4.0. https://doi.org/10.1162/99608f92.7679a1ed

James Johndrow, Patrick Ball, Maria Gargiulo, and Kristian Lum. (2020). Estimating the Number of SARS-CoV-2 Infections and the Impact of Mitigation Policies in the United States. Harvard Data Science Review. 24 November, 2020. © The Authors, 2020, CC BY 4.0. https://doi.org/10.1162/99608f92.7679a1ed


BJS Report on Arrest-Related Deaths: True Number Likely Much Greater

(This post is co-authored by Patrick Ball and Kristian Lum.) Today the Bureau of Justice Statistics (BJS) released a report on their effort to document “all deaths that occur during the process of arrest in the United States.” The analysis estimates that the Arrest-Related Deaths (ARD) program covers only 34-49% of these deaths. A parallel program by the FBI (the Supplementary Homicide Reports, SHR) is estimated to cover approximately the same proportion of deaths. Even taking into consideration both programs, 28% of all police homicides remain unreported. In order to estimate the total number of homicides that appear on neither the ARD or ...

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.


New Research on Civilian Deaths and Disappearances in El Salvador

This rigorous estimate shows that 1-2 percent of the country’s population was killed or disappeared during the civil war.

Primer to Inform Discussions about Bail Reform

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

Guatemala 1993-1999 – Using MSE to Estimate the Number of Deaths

Propelled by the impact of data analysis in El Salvador, Patrick Ball applied his WDWTW model to human rights information in other countries. Throughout the 1990’s, Ball worked at the American Association for the Advancement of Science (AAAS) analyzing large-scale human rights violations in Ethiopia, South Africa, Haiti and Guatemala. Together with senior scientific colleagues, including statistician Dr. Herb Spirer, Ball developed new methods for analyzing state-sanctioned violence. This chapter documents how the research expanded when a group of nongovernmental organizations in Guatemala asked the scientific community to gather and analyze ...

Kosovo Data – Killings, Migrations and More

Much of the debate about the March–June 1999 war between NATO and Yugoslavia turned on how many people left their homes in particular places and at certain times. Solid information about the flow of refugees out of Kosovo has helped investigators to link patterns in the flow to patterns of NATO bombing, Yugoslav strategic plans for "cleansing" Kosovo, and Yugoslav and irregular troop deployments. At its heart, the debate was about whether refugees left their homes fleeing NATO attacks and fighting between the KLA and Yugoslav forces, or whether they left their homes after being threatened, assaulted, and robbed by Yugoslav police, army, and irregu...

Police Violence in Puerto Rico: Flooded with Data

Kilómetro Cero is making a comparison of police killings in Puerto Rico and police killings in the non-territorial United States, and HRDAG is helping to organize the data.

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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