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Pulling Back the Curtain on LLMs & Policing Data
Structural Zero Issue 04
September 30, 2025
Artificial intelligence is transforming how we work with information. At HRDAG, that changes how I do my job every day. My most recent project was using LLMs to explore and parse vast quantities of data about police abuses in California.
In this newsletter, I’ll pull back the curtain on that work. I’ll describe how a diverse coalition gathered more than a million pages of documents about police misconduct in California and how LLMs helped us make sense of them in ways that wouldn’t have been possible before the advent of this technology.
In addition to understanding my work, I hope that this ...
Liberia
In July 2009, The Human Rights Data Analysis Group (HRDAG) concluded a three-year project with the Liberian Truth and Reconciliation Commission to help clarify Liberia's violent history and hold perpetrators of human rights abuses accountable for their actions. (This work was conducted by HRDAG while with Benetech.)
In the course of this work, HRDAG analyzed more than 17,000 victim and witness statements collected by the Liberian Truth and Reconciliation Commission and compiled the data into a report entitled "Descriptive Statistics From Statements to the Liberian Truth and Reconciliation Commission." The report is included as an annex to the final ...
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 ...
How we go about estimating casualties in Syria—Part 1
I spent the two weeks over Easter working with Patrick and Megan in San Francisco, trying to figure out a strategy of how best to estimate the number of casualties the Syrian civil war has claimed in the past two years. In January, HRDAG published a report on the number of fully identified casualties reported in the Syrian Arab Republic between March 2011 and November 2012. The number of de-duplicated records of killings for this period was 59,648, a number that is likely to be an undercount since we know that many incidences of lethal violence in conflict go unreported, and that the unreported cases are not missing at random. (more…)
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 ...
Herb Spirer, 1925 – 2018
Herb led and mentored a generation of statisticians working in human rights.
Primer to Inform Discussions about Bail Reform
The primer addresses what pretrial risk assessment is and what the research supports.
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.
.Rproj Considered Harmful
We aim to produce code that is clear, replicatable across machines and operating systems, and that leaves an easy-to-follow audit trail.
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.
Identifiers of Detained Children Have Implications for Data Security and Estimation
Identifiers being sequential could make possible estimations of the population of detained children.
Can the Armed Conflict Become Part of Colombia’s History?
Paula Amado and María Juliana Durán Fedullo reflect on how the Truth Commission may change Colombia’s history, finally officially acknowledging the 50-year conflict and its casualties, and reckoning with who did what to whom.
How Data Analysis Confirmed the Bias in a Family Screening Tool
In Pittsburgh …
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.
How Pretrial Risk Assessment Tools Perpetuate Unfairness
Tools like Compas allegedly help judges predict future criminal activities and eliminate bias. HRDAG and partners showed how the tools recycle bias.
Cifra de líderes sociales asesinados es más alta: Dejusticia
Contrario a lo que se puede pensar, los datos oficiales sobre líderes sociales asesinados no necesariamente corresponden a la realidad y podría haber mucha mayor victimización en las regiones golpeadas por este flagelo, según el más reciente informe del Centro de Estudios de Justicia, Derecho y Sociedad (Dejusticia) en colaboración con el Human Rights Data Analysis Group.
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.
Layers of Bias: A Unified Approach for Understanding Problems With Risk Assessment
Laurel Eckhouse, Kristian Lum, Cynthia Conti-Cook and Julie Ciccolini (2018). Layers of Bias: A Unified Approach for Understanding Problems With Risk Assessment. Criminal Justice and Behavior. November 23, 2018. © 2018 Sage Journals. All rights reserved. https://doi.org/10.1177/0093854818811379
Laurel Eckhouse, Kristian Lum, Cynthia Conti-Cook and Julie Ciccolini (2018). Layers of Bias: A Unified Approach for Understanding Problems With Risk Assessment. Criminal Justice and Behavior. November 23, 2018. © 2018 Sage Journals. All rights reserved. https://doi.org/10.1177/0093854818811379
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
Reality and risk: A refutation of S. Rendón’s analysis of the Peruvian Truth and Reconciliation Commission’s conflict mortality study
Daniel Manrique-Vallier and Patrick Ball (2019). Reality and risk: A refutation of S. Rendón’s analysis of the Peruvian Truth and Reconciliation Commission’s conflict mortality study. Research & Politics, 22 March 2019. © Sage Journals. https://doi.org/10.1177/2053168019835628
Daniel Manrique-Vallier and Patrick Ball (2019). Reality and risk: A refutation of S. Rendón’s analysis of the Peruvian Truth and Reconciliation Commission’s conflict mortality study. Research & Politics, 22 March 2019. © Sage Journals. https://doi.org/10.1177/2053168019835628