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“Surmortalité carcérale” sous Habré

Le statisticien américain Patrick Ball, expert au procès de Hissène Habré, a déclaré vendredi que le taux de mortalité d’opposants tchadiens présumés dans les prisons du régime Habré était encore pire que celui des prisonniers de guerre américains dans les camps japonais.


Inside the Difficult, Dangerous Work of Tallying the ISIS Death Toll

HRDAG executive director Megan Price is interviewed by Mother Jones. An excerpt: “Violence can be hidden,” says Price. “ISIS has its own agenda. Sometimes that agenda is served by making public things they’ve done, and I have to assume, sometimes it’s served by hiding things they’ve done.”


Predictive policing violates more than it protects

William Isaac and Kristian Lum. Predictive policing violates more than it protects. USA Today. December 2, 2016. © USA Today.

William Isaac and Kristian Lum. Predictive policing violates more than it protects. USA Today. December 2, 2016. © USA Today.


The Data Scientist Helping to Create Ethical Robots

Kristian Lum is focusing on artificial intelligence and the controversial use of predictive policing and sentencing programs.

What’s the relationship between statistics and AI and machine learning?

AI seems to be a sort of catchall for predictive modeling and computer modeling. There was this great tweet that said something like, “It’s AI when you’re trying to raise money, ML when you’re trying to hire developers, and statistics when you’re actually doing it.” I thought that was pretty accurate.


Palantir Has Secretly Been Using New Orleans to Test Its Predictive Policing Technology

One of the researchers, a Michigan State PhD candidate named William Isaac, had not previously heard of New Orleans’ partnership with Palantir, but he recognized the data-mapping model at the heart of the program. “I think the data they’re using, there are serious questions about its predictive power. We’ve seen very little about its ability to forecast violent crime,” Isaac said.


Reflections: The G in HRDAG is the Real Fuel

It took me a while to realize I had become part of the HRDAG incubator—at least that’s what it felt like to me—for young data analysts who wanted to use statistical knowledge to make a real impact on human rights debates.

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.


Mapping Mexico’s hidden graves

When Patrick Ball was introduced to Ibero’s database, the director of research at the Human Rights Data Analysis Group in San Francisco, California, saw an opportunity to turn the data into a predictive model. Ball, who has used similar models to document human rights violations from Syria to Guatemala, soon invited Data Cívica, a Mexico City–based nonprofit that creates tools for analyzing data, to join the project.


Experts Greet Kosovo Memory Book

On Wednesday, February 4, in Pristina, international experts praised the Humanitarian Law Centre’s database on victims of the Kosovo conflict, the Kosovo Memory Book. HRDAG executive director Patrick Ball is quoted in the article that appeared in Balkan Transitional Justice.


The ghost in the machine

“Every kind of classification system – human or machine – has several kinds of errors it might make,” [Patrick Ball] says. “To frame that in a machine learning context, what kind of error do we want the machine to make?” HRDAG’s work on predictive policing shows that “predictive policing” finds patterns in police records, not patterns in occurrence of crime.


5 Questions for Kristian Lum

Kristian Lum discusses the challenges of getting accurate data from conflict zones, as well as her concerns about predictive policing if law enforcement gets it wrong.


Data-driven crime prediction fails to erase human bias

Work by HRDAG researchers Kristian Lum and William Isaac is cited in this article about the Policing Project: “While this bias knows no color or socioeconomic class, Lum and her HRDAG colleague William Isaac demonstrate that it can lead to policing that unfairly targets minorities and those living in poorer neighborhoods.”


What happens when you look at crime by the numbers

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.”


Estimating the human toll in Syria

Megan Price (2017). Estimating the human toll in Syria. Nature. 8 February 2017. © 2017 Macmillan Publishers Limited, part of Springer Nature. All rights reserved. Nature Human Behaviour. ISSN 2397-3374.


Amnesty International Reports Organized Murder Of Detainees In Syrian Prison

100x100nprReports of torture and disappearances in Syria are not new. But the Amnesty International report says the magnitude and severity of abuse has “increased drastically” since 2011. Citing the Human Rights Data Analysis Group, the report says “at least 17,723 people were killed in government custody between March 2011 and December 2015, an average of 300 deaths each month.”


Counting Casualties in Syria

Today the United Nations Office of the High Commissioner for Human Rights (OHCHR) released a report prepared by me and my colleagues describing the current state of reported killings in the Syrian Arab Republic from the beginning of the conflict in March 2011 through April 2013.  (UN news release here.) This report is an update of work we published in January 2013.  This updated analysis includes records from eight data sources documenting a total of 92,901 reported killings. Our analysis begins with 263,055 total records reported by the eight data sources that include sufficient identifying information (name, date, and location*) to conduct ...

Multiple Systems Estimation: Collection, Cleaning and Canonicalization of Data

<< Previous post: MSE: The Basics Q3. What are the steps in an MSE analysis? Q4. What does data collection look like in the human rights context? What kind of data do you collect? Q5. [In depth] Do you include unnamed or anonymous victims in the matching process? Q6. What do you mean by "cleaning" and "canonicalization?" Q7. [In depth] What are some of the challenges of canonicalization? (more…)

HRDAG at Strata Conference 2014

Last Thursday, HRDAG co-founder and director of research Megan Price presented at Strata, the conference for data scientists and people who work with "big data." In her talk, she addressed the question of how we can know the actual number of conflict casualties in Syrian. Her short answer was, "We don't know." The longer answer was that we have a very good idea of how many conflict casualties have been reported, by several documentation groups, and that we're working on analyzing (more…)

Multiple Systems Estimation: The Basics

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. In this blogpost, and four more to follow, I’ll answer both conceptual and practical questions about this important method. (In posts to follow, questions that refer to specific statistical procedures or debates will be marked, "In depth.") (more…)

Claudia Carolina López Taks

Field Consultant Carolina Lopéz has worked with the Archivo Histórico de la Policía Nacional (AHPN) in Guatemala for eight years, and is currently a member of the Archive  Technical Coordination team. A professional working within the social sciences, she prefers using alternative research on past practices to develop an understanding of the present. Her work consists primarily of monitoring and creating strategies to systematize, track and create process controls. She also has thorough knowledge of management of historical archive documents. Since 2006, Carolina has worked in quantitative research at the AHPN with HRDAG team members Patrick ...

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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