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Lancet Study Estimates Gaza Death Toll 40% Higher Than Recorded
“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 has been used for centuries and that the researchers had reached “a good estimate” for Gaza.”
Overbooking’s Impact on Pre-Trial Risk Assessment Tools
Learning to Learn: Reflections on My Time at HRDAG
Predictive Policing Reinforces Police Bias
Reflections on Data Science for Real-World Problems
Patrick Ball Honored as New ASA Fellow
Timor-Leste Op-Ed
Quantifying Police Misconduct in Louisiana
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.
Quantifying Injustice
“In 2016, two researchers, the statistician Kristian Lum and the political scientist William Isaac, set out to measure the bias in predictive policing algorithms. They chose as their example a program called PredPol. … Lum and Isaac faced a conundrum: if official data on crimes is biased, how can you test a crime prediction model? To solve this technique, they turned to a technique used in statistics and machine learning called the synthetic population.”
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.
Press Release, Timor-Leste, February 2006
Learning Day by Day: Quantitative Research at the AHPN
How Data Processing Uncovers Misconduct in Use of Force in Puerto Rico
New results for the identification of municipalities with clandestine graves in Mexico
HRDAG Wins the Rafto Prize
Can the Armed Conflict Become Part of Colombia’s History?
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.
Learning a Modular, Auditable and Reproducible Workflow
Syria’s celebrations muted by evidence of torture in Assad’s notorious prisons
The Human Rights Data Analysis Group, an independent scientific human rights organization based in San Francisco, has counted at least 17,723 people killed in Syrian custody from 2011 to 2015 — around 300 every week — almost certainly a vast undercount, it says.