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Making the Case. Investigating Large Scale Human Rights Violations Using Information Systems and Data Analysis
Patrick Ball, Herbert F. Spirer, and Louise Spirer, eds. Making the Case. Investigating Large Scale Human Rights Violations Using Information Systems and Data Analysis . © 2000 American Association for the Advancement of Science. All rights reserved. Reprinted with permission. [full text] [intro] [chapters 1 2 3 4 5 67 8 9 10 11 12]
Different Convenience Samples, Different Stories: The Case of Sierra Leone.
Anita Gohdes. “Different Convenience Samples, Different Stories: The Case of Sierra Leone.” Benetech. 2010. © 2010 Benetech. Creative Commons BY-NC-SA.
Collecting Sensitive Human Rights Data in the Field: A Case Study from Amritsar, India.
Romesh Silva and Jasmine Marwaha. “Collecting Sensitive Human Rights Data in the Field: A Case Study from Amritsar, India.” In JSM Proceedings, Social Statistics Section. Alexandria, VA. © 2011 American Statistical Association. All rights reserved.
Where Stats and Rights Thrive Together
Momentous Verdict against Hissène Habré
War and Illness Could Kill 85,000 Gazans in 6 Months
HRDAG director of research Patrick Ball is quoted in this New York Times article about a paper that models death tolls in Gaza.
Gaza death toll 40% higher than official number, Lancet study finds
“Patrick Ball, a statistician at the US-based Human Rights Data Analysis Group not involved in the research, has used capture-recapture methods to estimate death tolls for conflicts in Guatemala, Kosovo, Peru and Colombia.
Ball told AFP the well-tested technique had been used for centuries and that the researchers had reached “a good estimate” for Gaza.”
Big Data Predictive Analytics Comes to Academic and Nonprofit Institutions to Fuel Innovation
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
In 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.