674 results for search: %EA%B4%91%EA%B3%A0%EB%AC%B8%EC%9D%98%E2%96%B7%E0%B4%A0%E2%9D%B6%E0%B4%A0%E3%85%A1%E2%9D%BD%E2%9D%BD%E2%9D%BC%E2%9D%BB%E3%85%A1%E2%9D%BD%E2%9D%BC%E2%9D%BC%E2%9D%BD%E2%96%B7%EA%B8%B0%EA%B3%84%EB%A9%B4%EA%B0%90%EC%84%B1%EB%A7%88%EC%82%AC%EC%A7%80%E3%81%8D%EA%B4%91%EA%B3%A0%E2%94%AE%EB%AC%B8%EC%9D%98%E2%86%82%EA%B8%B0%EA%B3%84%EB%A9%B4%E7%9C%98%EA%B0%90%EC%84%B1%EB%A7%88%EC%82%AC%EC%A7%80%E5%A6%B8emendatory/feed/rss2/press-release-chad-2010jan
The True Dangers of AI are Closer Than We Think
William Isaac is quoted.
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.
Perú
At Toronto’s Tamil Fest, human rights group seeks data on Sri Lanka’s civil war casualties
Earlier this year, the Canadian Tamil Congress connected with HRDAG to bring its campaign to Toronto’s annual Tamil Fest, one of the largest gatherings of Canada’s Sri Lankan diaspora.
Ravichandradeva, along with a few other volunteers, spent the weekend speaking with festival-goers in Scarborough about the project and encouraging them to come forward with information about deceased or missing loved ones and friends.
“The idea is to collect thorough, scientifically rigorous numbers on the total casualties in the war and present them as a non-partisan, independent organization,” said Michelle Dukich, a data consultant with HRDAG.
Data Mining for Good: CJA Drink + Think
Liberian Truth and Reconciliation Commission Data
Reflections: A Simple Plan
HRDAG Retreat 2022
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.
Guatemala CIIDH Data
HRDAG Welcomes New Staff, Interns and Fellow
Casanare, Colombia
Justice Unknown, Justice Unsatisfied? Bosnian NGOs Speak about the International Criminal Tribunal for the Former Yugoslavia.
Kristen Cibelli and Tamy Guberek. “Justice Unknown, Justice Unsatisfied? Bosnian NGOs Speak about the International Criminal Tribunal for the Former Yugoslavia.” A project of Education and Public Inquiry and International Citizenship at Tufts University. December, 2000.
HRDAG at Strata Conference 2014
Layers of Bias: A Unified Approach for Understanding Problems With Risk Assessment
Laurel Eckhouse, Kristian Lum, Cynthia Conti-Cook and Julie Ciccolini (2018). Layers of Bias: A Unified Approach for Understanding Problems With Risk Assessment. Criminal Justice and Behavior. November 23, 2018. © 2018 Sage Journals. All rights reserved. https://doi.org/10.1177/0093854818811379
Big data may be reinforcing racial bias in the criminal justice system
Laurel Eckhouse (2017). Big data may be reinforcing racial bias in the criminal justice system. Washington Post. 10 February 2017. © 2017 Washington Post.
Who Did What to Whom? Planning and Implementing a Large Scale Human Rights Data Project
Patrick Ball. Who Did What to Whom? Planning and Implementing a Large Scale Human Rights Data Project. © 1996 American Association for the Advancement of Science.