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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.
HRDAG and #GivingTuesday 2017
Uncovering Police Violence in Chicago: A collaboration between HRDAG and Invisible Institute
HRDAG Retreat 2018
Pretrial Risk Assessment Tools
Sarah L. Desmarais and Evan M. Lowder (2019). Pretrial Risk Assessment Tools: A Primer for Judges, Prosecutors, and Defense Attorneys. Safety and Justice Challenge, February 2019. © 2019 Safety and Justice Challenge. <<HRDAG’s Kristian Lum and Tarak Shah served as Project Members and made significant contributions to the primer.>>
Civil War in Syria: The Internet as a Weapon of War
Suddeutsche Zeitung writer Hakan Tanriverdi interviews HRDAG affiliate Anita Gohdes and writes about her work on the Syrian casualty enumeration project for the UN Office of the High Commissioner for Human Rights. This article, “Bürgerkrieg in Syrien: Das Internet als Kriegswaffe,” is in German.
El Salvador
How Predictive Policing Reinforces Bias
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.
The World According to Artificial Intelligence (Part 2)
The World According to Artificial Intelligence – The Bias in the Machine (Part 2)
Artificial intelligence might be a technological revolution unlike any other, transforming our homes, our work, our lives; but for many – the poor, minority groups, the people deemed to be expendable – their picture remains the same.
Patrick Ball is interviewed: “The question should be, Who bears the cost when a system is wrong?”
Reflections on Data Science for Real-World Problems
Cifra de líderes sociales asesinados es más alta: Dejusticia
Contrario a lo que se puede pensar, los datos oficiales sobre líderes sociales asesinados no necesariamente corresponden a la realidad y podría haber mucha mayor victimización en las regiones golpeadas por este flagelo, según el más reciente informe del Centro de Estudios de Justicia, Derecho y Sociedad (Dejusticia) en colaboración con el Human Rights Data Analysis Group.
Judges in Habré Trial Cite HRDAG Analysis
A better statistical estimation of known Syrian war victims
Researchers from Rice University and Duke University are using the tools of statistics and data science in collaboration with Human Rights Data Analysis Group (HRDAG) to accurately and efficiently estimate the number of identified victims killed in the Syrian civil war.
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Using records from four databases of people killed in the Syrian war, Chen, Duke statistician and machine learning expert Rebecca Steorts and Rice computer scientist Anshumali Shrivastava estimated there were 191,874 unique individuals documented from March 2011 to April 2014. That’s very close to the estimate of 191,369 compiled in 2014 by HRDAG, a nonprofit that helps build scientifically defensible, evidence-based arguments of human rights violations.
Open Source Summit 2018
HRDAG’s Year End Review: 2019
Timor-Leste Op-Ed
There may have been 14 undocumented Korean “comfort women” in Palembang, Indonesia
Patrick Ball, Ethan Hee-Seok Shin and Hyerin Yang (2018). There may have been 14 undocumented Korean “comfort women” in Palembang, Indonesia. Human Rights Data Analysis Group. 26 December 2018.© 2018 HRDAG. Creative Commons.