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Welcome!
As of today, the Human Rights Data Analysis Group (HRDAG) is an independent* non-profit! It's been a long time coming, and we're delighted to have gotten to this point. HRDAG is a non-profit, non-partisan organization that applies rigorous science to the analysis of human rights violations around the world; for more information, see our About Us page.
Benetech has spun out the scientific and statistical part of the Human Rights Program to HRDAG. The spinout includes (as staff) me -- Patrick Ball -- and Dr Megan Price, as well as our many part-time scientific and field consultants (a list is here). The software and technology component of our work -- ...
Learning to Learn: Reflections on My Time at HRDAG
So much of what I learned at HRDAG was intangible, and I'm grateful to have been able to go deep.
Yezidi Activists Teach HRDAG about Human Rights – updated
UPDATE (21 Dec 2014): Juan Cole is reporting that the Kurdish militia (the peshmerga) have retaken Shingal (also known as Sinjar) mountain where many Yezidi people have been trapped since 3 August 2014. They are now moving to liberate other Yezidi towns south of the mountain. The Yezidi people trapped on the mountain are now free. There is no word yet on the thousands of Yezidi people enslaved by ISIS.
ORIGINAL (19 Nov 2014): Farhad (not his real name) got the call from ISIS on his personal cell phone just after lunch: we have your sister, and we will give her back if you pay us $6000, plus $1500 for the driver.
Carrying little more than his ...
Connect with HRDAG
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
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 ...
Rise of the racist robots – how AI is learning all our worst impulses
“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.
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.
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.
New Research Shows Community Engagement Improves the Validity and Reliability of Artificial Intelligence
AI is transforming the way scientists analyze complex data.
Partners
How we work with partners is how we relate to the whole human rights community. We work with human rights advocates and defenders to support their goals by complementing their substantive expertise with our technical expertise. To date, partners have included truth commissions, international criminal tribunals, United Nations missions, and non-governmental human rights organizations on five continents.
Here are a few stories that illustrate how we work with our partners:
HRDAG partner stories:
Quantifying Police Misconduct in Louisiana (2023)
Scraping for Pattern: Protecting Immigrant Rights in Washington State (2022)
Police Violence ...
Core Concepts
Inaccurate statistics can damage the credibility of human rights claims—and that's why we strive to ensure that statistics about human rights violations are generated with as much rigor and are as scientifically accurate as possible.
But, what are the pitfalls leading to inaccuracy—when, where, and how do data become compromised? How are patterns biased by having only partial data? And what are the best scientific methods for collecting, managing, processing and analyzing data?
Here are the data pitfalls that HRDAG has identified, as well as some of our approaches for meeting these challenges. We believe that human rights researchers must take ...
Frequently Asked Questions
Multiple Systems Estimation
What is MSE?
What do you mean by statistical inference?
What is an overlap, and how do we know when lists overlap?
How does MSE find the total number of violations?
How was MSE originally developed?
How does the Benetech Human Rights Program use MSE?
1. What is MSE?
A: Multiple Systems Estimation, or MSE, is a family of techniques for statistical inference. MSE uses the overlaps between several incomplete lists of human rights violations to determine the total number of violations.
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2. What do you mean by statistical inference?
A: ...
Datasets available for research
Over the last few years, we've tried to make the data organized in our projects publicly accessible. We have encouraged our partners to publish the data at the completion of the project. We continue to believe it is important to offer access to the data used in our projects for the sake of transparency as well as to encourage further research and analysis. However, we are increasingly concerned about how raw data are used. Data collected by what we can observe is what statisticians call a convenience sample, which is subject to selection bias.
We're keeping these datasets available for researchers who want to use them for simulation or estimation ...