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About HRDAG
HRDAG at Strata Conference 2014
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.
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
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How Structuring Data Unburies Critical Louisiana Police Misconduct Data
Data Science Symposium at Vanderbilt
Weapons of Math Destruction
Weapons of Math Destruction: invisible, ubiquitous algorithms are ruining millions of lives. Excerpt:
As Patrick once explained to me, you can train an algorithm to predict someone’s height from their weight, but if your whole training set comes from a grade three class, and anyone who’s self-conscious about their weight is allowed to skip the exercise, your model will predict that most people are about four feet tall. The problem isn’t the algorithm, it’s the training data and the lack of correction when the model produces erroneous conclusions.
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.
PredPol amplifies racially biased policing
HRDAG associate William Isaac is quoted in this article about how predictive policing algorithms such as PredPol exacerbate the problem of racial bias in policing.
“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).
Momentous Verdict against Hissène Habré
The Data Scientist Helping to Create Ethical Robots
Kristian Lum is focusing on artificial intelligence and the controversial use of predictive policing and sentencing programs.
What’s the relationship between statistics and AI and machine learning?
AI seems to be a sort of catchall for predictive modeling and computer modeling. There was this great tweet that said something like, “It’s AI when you’re trying to raise money, ML when you’re trying to hire developers, and statistics when you’re actually doing it.” I thought that was pretty accurate.
Download: Megan Price
Executive director Megan Price is interviewed in The New York Times’ Sunday Review, as part of a series known as “Download,” which features a biosketch of “Influencers and their interests.”
Data-driven development needs both social and computer scientists
Excerpt:
Data scientists are programmers who ignore probability but like pretty graphs, said Patrick Ball, a statistician and human rights advocate who cofounded the Human Rights Data Analysis Group.
“Data is broken,” Ball said. “Anyone who thinks they’re going to use big data to solve a problem is already on the path to fantasy land.”
One Better
The University of Michigan College of Literature, Science and the Arts profiled Patrick Ball in its fall 2016 issue of the alumni magazine. Here’s an excerpt:
Ball believes doing this laborious, difficult work makes the world a more just place because it leads to accountability.
“My part is a specific, narrow piece, which just happens to fit with the skills I have,” he says. “I don’t think that what we do is in any way the best or most important part of human rights activism. Sometimes, we are just a footnote—but we are a really good footnote.”