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The Limits of Observation for Understanding Mass Violence.

Megan Price and Patrick Ball. 2015. Canadian Journal of Law and Society / Revue Canadienne Droit et Société volume 30 issue 2 (June): 1-21. doi:10.1017/cls.2015.24. © Cambridge University Press. All rights reserved. Restricted access.

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.


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Patrick Ball on the Perils of Misusing Human Rights Data


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To Combat Human Rights Abuses, California Company Looks to Computer Code


Martus – Paramilitary Protection for Activists


Analyze This!


Death Numbers


Condenan a 40 años de cárcel a dos ex policías


Calculating Body Counts


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Data Dive Reveals 15,000 New Victims of Syria War


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Syrian Death Toll Reaches 60,000, Says UN Rights Agency


60,000 Dead in Syria? Why the Death Toll is Likely Even Higher


Tech for Truth


In Syrian Conflict, Real-Time Evidence Of Violations


Our work has been used by truth commissions, international criminal tribunals, and non-governmental human rights organizations. We have worked with partners on projects on five continents.

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