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USA

.hrdag-algo-button { margin-bottom: 25px; a { border-radius: 18px; background-color: #4f81ed; padding: 8px 18px; text-decoration: none; color: white; border: 1px solid transparent; } a:hover { color: #4f81ed; border: 1px solid #4f81ed; background-color: transparent; } } HRDAG’s analysis and expertise continues to deepen the national conversation about police violence and criminal legal 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 ...

Mexico

HRDAG and our partners Data Cívica and the Iberoamericana University created a machine-learning model to predict which counties (municipios) in Mexico have the highest probability of unreported hidden graves. The predictions help advocates to bring public attention and government resources to search for the disappeared in the places where they are most likely to be found. Context For more than ten years, Mexican authorities have been discovering hidden graves (fosas clandestinas). The casualties are attributed broadly—and sometimes inaccurately—to the country’s “drug war,” but the motivations and perpetrators behind the mass murders ...

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.


Celebrating Women in Statistics

kristian lum headshot 2018In her work on statistical issues in criminal justice, Lum has studied uses of predictive policing—machine learning models to predict who will commit future crime or where it will occur. In her work, she has demonstrated that if the training data encodes historical patterns of racially disparate enforcement, predictions from software trained with this data will reinforce and—in some cases—amplify this bias. She also currently works on statistical issues related to criminal “risk assessment” models used to inform judicial decision-making. As part of this thread, she has developed statistical methods for removing sensitive information from training data, guaranteeing “fair” predictions with respect to sensitive variables such as race and gender. Lum is active in the fairness, accountability, and transparency (FAT) community and serves on the steering committee of FAT, a conference that brings together researchers and practitioners interested in fairness, accountability, and transparency in socio-technical systems.


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.


Megan Price: Life-Long ‘Math Nerd’ Finds Career in Social Justice

“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.”


5 Humanitarian FOSS Projects to Watch

Dave Neary described “5 Humanitarian FOSS Projects to Watch,” listing HRDAG’s work on police homicides in the U.S. and other human rights abuses in other countries.


Using Data to Reveal Human Rights Abuses

Profile touching on HRDAG’s work on the trial and conviction of Hissène Habré, its US Policing Project, data integrity, data archaeology and more.


Sous la dictature d’Hissène Habré, le ridicule tuait

Patrick Ball, un expert en statistiques engagé par les Chambres africaines extraordinaires, a conclu que la « mortalité dans les prisons de la DDS fut substantiellement plus élevée que celles des pires contextes du XXe siècle de prisonniers de guerre ».


How Do We Know the Death Toll in Syria Is Accurate?


Tech for Truth


Benetech Celebrates Milestone; Human Rights Data Analysis Group Transitioning into Independent Organization


In Syrian Conflict, Real-Time Evidence Of Violations


60,000 Dead in Syria? Why the Death Toll is Likely Even Higher


Direct procès Habré: le taux de mortalité dans les centres de détention, au menu des débats

Statisticien, Patrick Ball est à la barre ce vendredi matin. L’expert est entendu sur le taux de mortalité dans les centres de détention au Tchad sous Habré. Désigné par la chambre d’accusation, il dira avoir axé ses travaux sur des témoignages, des données venant des victimes et des documents de la DDS (Direction de la Documentation et de la Sécurité).


Counting the Dead in Syria


Por qué los datos casan con la hipótesis de que hubo genocidio


Guatemala: Why We Cannot Turn Away


Carnegie Mellon Partners With Human Rights Data Analysis Group To Improve Syrian Casualty Reporting


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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