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Update of Iraq and Syria Data in New Paper

This week The Statistical Journal of the IAOS published a new(ish) paper by Megan Price and Patrick Ball. The open-access paper, Selection bias and the statistical patterns of mortality in conflict, is a revisiting and updating of both the Iraq and Syria examples used in an earlier paper, Big Data, Selection Bias, and the Statistical Patterns of Mortality in Conflict, which was published last year inThe SAIS Review of International Affairs (JHU Press, 2014). HRDAG believes that the concerns highlighted by these examples are important for a wide variety of audiences, including both the foreign policy readers reached by The SAIS Review and the ...

HRDAG Names New Board Members Julie Broome and Frank Schulenburg

We are pleased to announce that HRDAG will be supported by two additions to our Advisory Board, Julie Broome and Frank Schulenburg. We’ve worked with Julie for many years, getting to know her when she was Director of Programmes at The Sigrid Rausing Trust. She is now the Director of London-based Ariadne, a network of European funders and philanthropists. She worked at the Trust for seven years, most notably Head of Human Rights, before becoming Director of Programmes in 2014. Before joining the Trust she was Programme Director at the CEELI Institute in Prague, where she was responsible for conducting rule of law-related trainings for judges and ...

Get Involved/Donate

Donating to HRDAG Thank you for your interest in making a donation to the Human Rights Data Analysis Group to help us use science to support our partners in the human rights world. You can make a donation by credit card on the Community Partners® Network for Good page. HRDAG is a "project of Community Partners," and right below  the section on payment information, you'll be able to select "Human Rights Data Analysis Group" from a drop-down menu. (On most browsers, if you use this link, HRDAG will be pre-selected on the drop-down menu.) This transaction will appear on your credit card statement as "Network for Good." If you donate by check, ...

Coming soon: HRDAG 2019 Year-End Review

The online version of the 2019 Year-End Review will appear in January 2020.            

Tech Note – using LLMs for structured info extraction

This post introduces the methodology of the Innocence Discovery Lab, a collaboration between IPNO and HRDAG.

HRDAG contributes to textbook Counting Civilian Casualties

Next week, on June 11, Oxford University Press officially puts Counting Civilian Casualties: An Introduction to Recording and Estimating Nonmilitary Deaths in Conflict on the market. This textbook, edited by Taylor B. Seybolt, Jay D. Aronson, and Baruch Fischhoff, responds to the increasing concern for civilians in conflict and aims to promote scientific dialogue by highlighting the strengths and weaknesses of the most commonly used casualty recording and estimation techniques. HRDAG is very well represented here, as our colleagues have co-authored four chapters, and Nicholas Jewell, who sits on our Science Committee, has co-authored a fifth. ...

The Atrocity Archives

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.”

Privacy Policy

Mailing List Subscription We use Mailchimp to help us keep track of community members who want to stay informed about what HRDAG is doing and thinking. If you self-subscribe to our list, we will never share your contact information. We will never subscribe anyone who does not explicitly agree to a subscription.  Over the course of a year, we mail quarterly letters and fundraising letters, as well as one or two updates as events demand. If, during the course of a fundraising campaign, you make a donation, we will do our best to remove you from the remainder of fundraising mailings that year. We may use your contact information to invite you to ...

Our Copyright Policy

We have specified "Some Rights Reserved" on our website, instead of the more conventional "All Rights Reserved." This is because some of our web content is covered by a Creative Commons license, which means that it may be copied and even re-purposed, with some stipulations. We have made this decision because HRDAG wants to contribute to the digital commons, defined by Creative Commons as "a pool of content that can be copied, distributed, edited, remixed, and built upon, all within the boundaries of copyright law." Our Creative Commons License We are using the Attribution-NonCommercial-ShareAlike license, also known as the BY-NC-SA license. Here is ...

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.

Sierra Leone Statistical Appendix

Richard Conibere, Jana Asher, Kristen Cibella, Jana Dudukovic, Rafe Kaplan, and Patrick Ball. Sierra Leone Statistical Appendix, A Report by the Benetech Human Rights Data Analysis Group and the American Bar Association Central European and Eurasian Law Initiative to the Truth and Reconciliation Commission. October 5, 2004.

Weapons of Math Destruction

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.

Descriptive Statistics From Statements to the Liberian Truth and Reconciliation Commission

Kristen Cibelli, Amelia Hoover, and Jule Krüger (2009). “Descriptive Statistics From Statements to the Liberian Truth and Reconciliation Commission,” a Report by the Human Rights Data Analysis Group at Benetech and Annex to the Final Report of the Truth and Reconciliation Commission of Liberia. Palo Alto, California. Benetech.

Quantifying Police Misconduct in Louisiana

HRDAG contributes to the project by helping to classify, filter, extract, and standardize the records so that they can be useful in the database.

Patrick Ball on the Perils of Misusing Human Rights Data

The Panic Button: High-Tech Protection for Human Rights Investigators

Benetech Scientists Publish Analysis of Indirect Sampling Methods in the Journal of the American Medical Association

Analyze This!

Death Toll In Syria Jumps To Nearly 93,000

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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