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Learning to Learn: Reflections on My Time at HRDAG
Foundation of Human Rights Statistics in Sierra Leone
Richard Conibere (2004). Foundation of Human Rights Statistics in Sierra Leone (abstr.), Joint Statistical Meetings. Toronto, Canada.
Donate with Cryptocurrency
Hat-Tip from Guatemala Judges on HRDAG Evidence
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.
Tech Note – improving LLM-driven info extraction
HRDAG and the Trial of José Efraín Ríos Montt
Casanare, Colombia
Cuentas y mediciones de la criminalidad y de la violencia
Exploración y análisis de los datas para comprender la realidad. Patrick Ball y Michael Reed Hurtado. 2015. Forensis 16, no. 1 (July): 529-545. © 2015 Instituto Nacional de Medicina Legal y Ciencias Forenses (República de Colombia).
Historic verdict in Guatemala—Gen.Efraín Ríos Montt found guilty
Using Data and Statistics to Bring Down Dictators
In this story, Guerrini discusses the impact of HRDAG’s work in Guatemala, especially the trials of General José Efraín Ríos Montt and Colonel Héctor Bol de la Cruz, as well as work in El Salvador, Syria, Kosovo, and Timor-Leste. Multiple systems estimation and the perils of using raw data to draw conclusions are also addressed.
Megan Price and Patrick Ball are quoted, especially in regard to how to use raw data.
“From our perspective,” Price says, “the solution to that is both to stay very close to the data, to be very conservative in your interpretation of it and to be very clear about where the data came from, how it was collected, what its limitations might be, and to a certain extent to be skeptical about it, to ask yourself questions like, ‘What is missing from this data?’ and ‘How might that missing information change these conclusions that I’m trying to draw?’”
HRDAG Welcomes Two New Scholars
First Things First: Assessing Data Quality Before Model Quality.
Anita Gohdes and Megan Price (2013). Journal of Conflict Resolution, Volume 57 Issue 6 December 2013. © 2013 Journal of Conflict Resolution. All rights reserved. Reprinted with permission of SAGE. [online abstract]DOI: 10.1177/0022002712459708.
In Syria, Uncovering the Truth Behind a Number
Huffington Post Politics writer Matt Easton interviews Patrick Ball, executive director of HRDAG, about the latest enumeration of killings in Syria. As selection bias is increasing, it becomes harder to see it: we have the “appearance of perfect knowledge, when in fact the shape of that knowledge has not changed that much,” says Patrick. “Technology is not a substitute for science.”
New Report Raises Questions Over CPD’s Approach to Missing Persons Cases
In this video, Trina Reynolds-Tyler of Invisible Institute talks about her work with HRDAG on the missing persons project in Chicago and Beneath the Surface.
HRDAG’s Year in Review: 2022
Gaza: Why is it so hard to establish the death toll?
HRDAG director of research Patrick Ball is quoted in this Nature article about how body counts are a crude measure of the war’s impact and more reliable estimates will take time to compile.
“El reto de la estadística es encontrar lo escondido”: experto en manejo de datos sobre el conflicto
In this interview with Colombian newspaper El Espectador, Patrick Ball is quoted as saying “la gente que no conoce de álgebra nunca debería hacer estadísticas” (people who don’t know algebra should never do statistics).
