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HRDAG Names New Board Members Julie Broome and Frank Schulenburg
Get Involved/Donate
How We Choose Projects
Liberia 2009 – Coding Testimony to Determine Accountability for War Crimes
Coming soon: HRDAG 2019 Year-End Review
Syria 2012 – Modeling Multiple Datasets in an Ongoing Conflict
Violent Deaths and Enforced Disappearances During the Counterinsurgency in Punjab, India: A Preliminary Quantitative Analysis
Romesh Silva, Jasmine Marwaha and Jeff Klingner. “Violent Deaths and Enforced Disappearances During the Counterinsurgency in Punjab, India: A Preliminary Quantitative Analysis,” A Joint Report by Benetech’s Human Rights Data Analysis Group & Ensaaf, Inc. January, 2009.
How many people are going to die from COVID-19?
Patrick Ball, Kristian Lum, Tarak Shah and Megan Price (2020). How many people are going to die from COVID-19? Granta. 14 March 2020. © Granta Publications 2020.
Measuring Elusive Populations with Bayesian Model Averaging for Multiple Systems Estimation: A Case Study on Lethal Violations in Casanare, 1998-2007
Kristian Lum, Megan Price, Tamy Guberek, and Patrick Ball. “Measuring Elusive Populations with Bayesian Model Averaging for Multiple Systems Estimation: A Case Study on Lethal Violations in Casanare, 1998-2007,” Statistics, Politics, and Policy. 1(1) 2010. All rights reserved.
How do epidemiologists know how many people will get Covid-19?
Patrick Ball (2020). How do epidemiologists know how many people will get Covid-19? Significance. 09 April 2020. © 2020 The Royal Statistical Society.
How much faith can we place in coronavirus antibody tests?
Megan Price, Morgan Agnew, and David Peters (2020). How much faith can we place in coronavirus antibody tests? Granta. 28 April 2020. © Granta Publications 2020.
Why Just Counting the Dead in Syria Won’t Bring Them Justice
Patrick Ball (2016). Why Just Counting the Dead in Syria Won’t Bring Them Justice. Foreign Policy. October 19, 2016. © 2016 Foreign Policy.
Data-driven development needs both social and computer scientists
Excerpt:
Data scientists are programmers who ignore probability but like pretty graphs, said Patrick Ball, a statistician and human rights advocate who cofounded the Human Rights Data Analysis Group.
“Data is broken,” Ball said. “Anyone who thinks they’re going to use big data to solve a problem is already on the path to fantasy land.”
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.
Primer to Inform Discussions about Bail Reform
Learning a Modular, Auditable and Reproducible Workflow
Hunting for Mexico’s mass graves with machine learning
“The model uses obvious predictor variables, Ball says, such as whether or not a drug lab has been busted in that county, or if the county borders the United States, or the ocean, but also includes less-obvious predictor variables such as the percentage of the county that is mountainous, the presence of highways, and the academic results of primary and secondary school students in the county.”