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Patrick Ball is kicking himself for a decision he made almost 25 years ago. “I was clever, but I wasn’t smart,” he says ruefully, as he considers the labyrinth of tables and ASCII-encoded keystrings he used to design a database of human rights violations for the pioneering Salvadoran non-governmental Human Rights Commission (CDHES). Now I’m sitting in his office in San Francisco’s Mission District watching over his shoulder, and trying to keep up, as he bangs out code to decipher the priceless data contained in these old files. Created in 1991 and 1992, during the last days of El Salvador’s internal armed conflict, the files detail ...
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 ...
In this story, Guerrini discusses the impact of HRDAG’s work in Guatemala, especially the trials of General José Efraín Ríos Montt and Colonel Héctor Bol de la Cruz, as well as work in El Salvador, Syria, Kosovo, and Timor-Leste. Multiple systems estimation and the perils of using raw data to draw conclusions are also addressed.
Megan Price and Patrick Ball are quoted, especially in regard to how to use raw data.
“From our perspective,” Price says, “the solution to that is both to stay very close to the data, to be very conservative in your interpretation of it and to be very clear about where the data came from, how it was collected, what its limitations might be, and to a certain extent to be skeptical about it, to ask yourself questions like, ‘What is missing from this data?’ and ‘How might that missing information change these conclusions that I’m trying to draw?’”
In this free, downloadable report, Mike Barlow of O’Reilly Media cites several examples of how data and the work of data scientists have made a measurable impact on organizations such as DataKind, a group that connects socially minded data scientists with organizations working to address critical humanitarian issues. HRDAG—and executive director Megan Price—is one of the first organizations whose work is mentioned.
Collecting and Protecting Human Rights Data in Guatemala (1991-2013)
In 1996, a peace accord brokered by the United Nations ended 36 years of internal armed conflict in Guatemala. During the hostilities, non-governmental organizations asked for technical support from the scientific community in the project to gather the experiences of witnesses and victims in databases.
From 1993 to 1999 Dr. Patrick Ball, then at the American Association for the Advancement of Science (AAAS), worked with the International Center for Human Rights Research in Guatemala (CIIDH) to collect and organize evidence of more than 43,000 human rights violations. The ...
Estimates of Killings and Disappearances in Casanare
Casanare is a large, rural department or state in Colombia that includes 19 municipalities and a population of almost 300,000 inhabitants. Located in the foothills of the Andes and on the eastern plains, Casanare has a history of violence. Multiple armed groups have operated in Casanare including paramilitaries, guerillas and the Colombian military. Many Casanare citizens have suffered violent deaths and disappearances.
But how many people have been killed or disappeared? For reasons of policy, accountability and historical clarification, this question deserves a valid answer. In February ...
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 ...
The need to establish the truth around events is central to goals of transitional justice, particularly securing accountability, establishing legitimate and effective justice mechanisms, and laying the foundations for a peaceful society.
Documentation to provide verifiable and widely accepted accounts of such events is a critical component of establishing this truth, or the multiple truths that may exist for a population. It is difficult to overstate the important role of documentation in transitional justice efforts. If some of what follows sounds familiar, echoing points of previous posts, it is no coincidence. Documentation, in a word, is the ...
The primer addresses what pretrial risk assessment is and what the research supports.
We aim to produce code that is clear, replicatable across machines and operating systems, and that leaves an easy-to-follow audit trail.
Identifiers being sequential could make possible estimations of the population of detained children.
Tools like Compas allegedly help judges predict future criminal activities and eliminate bias. HRDAG and partners showed how the tools recycle bias.
“If you’re not careful, you risk automating the exact same biases these programs are supposed to eliminate,” says Kristian Lum, the lead statistician at the San Francisco-based, non-profit Human Rights Data Analysis Group (HRDAG). Last year, Lum and a co-author showed that PredPol, a program for police departments that predicts hotspots where future crime might occur, could potentially get stuck in a feedback loop of over-policing majority black and brown neighbourhoods. The program was “learning” from previous crime reports. For Samuel Sinyangwe, a justice activist and policy researcher, this kind of approach is “especially nefarious” because police can say: “We’re not being biased, we’re just doing what the math tells us.” And the public perception might be that the algorithms are impartial.
If you’d like to stay informed about HRDAG events, blogposts, and news, connect with us on Twitter, Facebook or through our RSS feed. We also have a LinkedIn page.
You may contact us directly via email at info @ hrdag.org.
A note for persons in search of assistance with specific human rights cases: We are very sorry for your troubles and your suffering; however, HRDAG does not take on casework. If you need help with a human rights case, you might consider requesting it from the International Committee of the Red Cross (www.icrc.org).
Photo: U.S. National Archives
In Washington State, some law enforcement officers illegally tip off ICE and CBP for civil immigration arrests. HRDAG helped identify where the problematic practices occurred.
IPFS is a peer-to-peer storage network that promotes the resiliency, immutability, and auditability of data. This README explains code written to shepherd the files from janky external USB drives to IPFS.
IN THE FACE OF TYRANNY
Taking a Stand as Data Scientists
As human rights data analysts, we center our moral understanding on the values of the
“I was always a math nerd. My mother has a polaroid of me in the fourth grade with my science fair project … . It was the history of mathematics. In college, I was a math major for a year and then switched to statistics.
I always wanted to work in social justice. I was raised by hippies, went to protests when I was young. I always felt I had an obligation to make the world a little bit better.”
Help HRDAG use data science to work for justice, accountability, and human rights. We are nonpartisan and nonprofit, but we are not neutral; we are always on the side of human rights.
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We are a team of experts in machine learning, applied and mathematical statistics, computer science, demography, and social science, and ...
In 1984, as a fresh PhD, I heard Richard Savage give his presidential address at the Joint Statistical Meetings in Philadelphia. He called it "Hard/Soft Problems" and made a big pitch for statisticians to get involved in human rights data analysis. It was inspirational, and I was immediately sold. I started working with the American Statistical Association's Committee on Scientific Freedom and Human Rights (now chaired by HRDAG's own Megan Price). Over time, a growing set of statisticians became involved, initially in letter-writing campaigns to help dissident statisticians (and other quantitative academics—economists seemed to have a particular ...
