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The data science field is always changing, which means that I'll always be learning.
In 2020, HRDAG provided clarity on issues related to the pandemic, police misconduct, and more.
The data on killings in Kosovo are in four files. All of the files are comma-delimited ASCII. The fields in each file are described below.
If you use these data on Kosovo killings, please cite them with the following citation, as well as this note:
“These are convenience sample data, and as such they are not a statistically representative sample of events in this conflict. These data do not support conclusions about patterns, trends, or other substantive comparisons (such as over time, space, ethnicity, age, etc.).”
Patrick Ball, Wendy Betts, Fritz Scheuren, Jana Dudukovich, and Jana Asher. (2002). AAAS/ABA-CEELI/Human Rights Data ...
I had the pleasure of working with Patrick Ball at the HRDAG office in San Francisco for a week during summer 2016. I knew Patrick from two workshops he previously hosted at the University of Washington’s Centre for Human Rights (UWCHR). The workshops were indispensable to us at UWCHR as we worked to publish a number of datasets on human rights violations during the El Salvador Civil War. The training was all the more helpful because the HRDAG team was so familiar with the data. As part of an impressive career which took him from Ethiopia and Kosovo to Haiti and El Salvador among others, Patrick himself had worked on gathering and analysing ...
This post describes how we organize our work over ten years, twenty analysts, dozens of countries, and hundreds of projects: we start with a task. A task is a single chunk of work, a quantum of workflow. Each task is self-contained and self-documenting; I'll talk about these ideas at length below. We try to keep each task as small as possible, which makes it easy to understand what the task is doing, and how to test whether the results are correct.
In the example I'll describe here, I'm going to describe work from our Syria database matching project, which includes about 100 tasks. I'll start with the first thing we do with files we receive ...
Patrick Ball and Michael Reed Hurtado. 2016. El registro y la medición de la criminalidad. El problema de los datos faltantes y el uso de la ciencia para producir estimaciones en relación con el homicidio en Colombia, demostrado a partir de un ejemplo: el departamento de Antioquia (2003-2011). Revista Criminalidad, 58 (1): 9-23.
Patrick Ball and Michael Reed Hurtado. 2016. El registro y la medición de la criminalidad. El problema de los datos faltantes y el uso de la ciencia para producir estimaciones en relación con el homicidio en Colombia, demostrado a partir de un ejemplo: el departamento de Antioquia (2003-2011). Revista Criminalidad, 58 (1): 9-23. Criminality registration and measurement. The problem of missing data, and the use of science to produce estimations relating to homicide in Colombia, as demonstrated with an example from one of its administrative and political divisions: the Department of Antioquia (2003-2011).
“Usually, the thing you’re trying to predict in a lot of these cases is something like rearrest,” Lum said. “So even if we are perfectly able to predict that, we’re still left with the problem that the human or systemic or institutional biases are generating biased arrests. And so, you still have to contextualize even your 100 percent accuracy with is the data really measuring what you think it’s measuring? Is the data itself generated by a fair process?”
HRDAG Director of Research Patrick Ball, in agreement with Lum, argued that it’s perhaps more practical to move it away from bias at the individual level and instead call it bias at the institutional or structural level. If a police department, for example, is convinced it needs to police one neighborhood more than another, it’s not as relevant if that officer is a racist individual, he said.
Excerpt:
Data scientists are programmers who ignore probability but like pretty graphs, said Patrick Ball, a statistician and human rights advocate who cofounded the Human Rights Data Analysis Group.
“Data is broken,” Ball said. “Anyone who thinks they’re going to use big data to solve a problem is already on the path to fantasy land.”
Weapons of Math Destruction: invisible, ubiquitous algorithms are ruining millions of lives. Excerpt:
As Patrick once explained to me, you can train an algorithm to predict someone’s height from their weight, but if your whole training set comes from a grade three class, and anyone who’s self-conscious about their weight is allowed to skip the exercise, your model will predict that most people are about four feet tall. The problem isn’t the algorithm, it’s the training data and the lack of correction when the model produces erroneous conclusions.
Issues surrounding policing in the United States are at the forefront of our national attention. Among these is the use of “predictive policing,” which is the application of statistical or machine learning models to police data, with the goal of predicting where or by whom crime will be committed in the future. Today Significance magazine published an article on this topic that I co-authored with William Isaac. Significance has kindly made this article open access (free!) for all of October. In the article we demonstrate the mechanism by which the use of predictive policing software may amplify the biases that already pervade our criminal ...
Kristian Lum’s work on the HRDAG Policing Project is referred to here: “In fact, Lum argues, it’s not clear how well this model worked at depicting the situation in Oakland. Those data on drug crimes were biased, she now reports. The problem was not deliberate, she says. Rather, data collectors just missed some criminals and crime sites. So data on them never made it into her model.”
New paper in Biometrika, co-authored by HRDAG's Kristian Lum and James Johndrow: Theoretical limits of microclustering in record linkage.
Patrick Ball won the Karl E. Peace Award for Outstanding Statistical Contributions for the Betterment of Society at the 2018 Joint Statistical Meeting.
HRDAG’s analysis and expertise continues to deepen the national conversation about police violence and criminal justice reform in the United States. In 2015 we began by considering undocumented victims of police violence, relying on the same methodological approach we’ve tested internationally for decades. Shortly after, we examined “predictive policing” software, and demonstrated the ways that racial bias is baked into the algorithms. Following our partners’ lead, we next considered the impact of bail, and found that setting bail increases the likelihood of a defendant being found guilty. We then broadened our investigations to examine ...
If you'd like to support HRDAG in this project, please consider making a donation via Our Donate page.
Over the last year, HRDAG has deepened the national conversation about homicides by police, predictive policing software, and the role that bail plays in the criminal justice system. Our studies describe how the racial bias inherent in police practice becomes data input to predictive policing tools. In another project, we are shining light on the iniquities of bail decisions.
TEAM
Click each team member's photo for full bio. Here's the team on Twitter.
Examining the Impact of Bail
When a defendant is detained before trial, she will face ...
Illuminating Data's Dark Side: Big data create conveniences, but we must consider who designs these tools, who benefits from them, and who is left out of the equation.
From time to time, we issue our own scientific reports that focus on the statistical aspects of the data analysis we have done in support of our partners. These reports are non-partisan, and they leave the work of advocacy to our partners.
You can search our publications by keyword or by year.
We are non-partisan—we do not take sides in political or military conflicts, nor do we advocate any particular political party or government policy. However, we are not neutral: we are always in favor of human rights. We support the protections established in the Universal Declaration of Human Rights, the International Covenant on Civil and Political Rights, and other international human rights treaties and instruments.
To speak with the researchers at HRDAG, please fill out the form below.
You can search our Press Room by keyword or by year.
HRDAG has been fortunate to have a long and exciting history that has taken us around the world to analyze data related to human rights violations. Along the way, we have met wonderful people, worked with amazing organizations and been a part of an amazing advancement of science through data analysis.
This page highlights key moments in our history.
