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Low-risk population size estimates in the presence of capture heterogeneity
James Johndrow, Kristian Lum and Daniel Manrique-Vallier (2019). Low-risk population size estimates in the presence of capture heterogeneity. Biometrika, asy065, 22 January 2019. © 2019 Biometrika Trust. https://doi.org/10.1093/biomet/asy065
Setting the Record Straight on Predictive Policing and Race
William Isaac and Kristian Lum (2018). Setting the Record Straight on Predictive Policing and Race. In Justice Today. 3 January 2018. © 2018 In Justice Today / Medium.
Limitations of mitigating judicial bias with machine learning
Kristian Lum (2017). Limitations of mitigating judicial bias with machine learning. Nature. 26 June 2017. © 2017 Macmillan Publishers Limited, part of Springer Nature. All rights reserved. Nature Human Behavior. DOI 10.1038/s41562-017-0141.
Theoretical limits of microclustering for record linkage
John E Johndrow, Kristian Lum and D B Dunson (2018). Theoretical limits of microclustering for record linkage. Biometrika. 19 March 2018. © 2018 Oxford University Press. DOI 10.1093/biomet/asy003.
A Comparison of Marginal and Conditional Models for Capture–Recapture Data with Application to Human Rights Violations Data
Shira Mitchell, Al Ozonoff, Alan Zaslavsky, Bethany Hedt-Gauthier, Kristian Lum and Brent Coull (2013). A Comparison of Marginal and Conditional Models for Capture-Recapture Data with Application to Human Rights Violations Data. Biometrics, Volume 69, Issue 4, pages 1022–1032, December 2013. © 2013, The International Biometric Society. DOI: 10.1111/biom.12089.
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.
Hunting for Mexico’s mass graves with machine learning
“The model uses obvious predictor variables, Ball says, such as whether or not a drug lab has been busted in that county, or if the county borders the United States, or the ocean, but also includes less-obvious predictor variables such as the percentage of the county that is mountainous, the presence of highways, and the academic results of primary and secondary school students in the county.”
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.”
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.”
Welcoming Our New Data Scientist
HRDAG Welcomes New Staff, Interns and Fellow
Los asesinatos de líderes sociales que quedan fuera de las cuentas
Una investigación de Dejusticia y Human Rights Data Analysis Group concluyó que hay un subconteo en los asesinatos de líderes sociales en Colombia. Es decir, que el aumento de estos crímenes en 2016 y 2017 podría ser incluso mayor al reportado por las organizaciones y por las cifras oficiales.
Predictive policing tools send cops to poor/black neighborhoods
In this post, Cory Doctorow writes about the Significance article co-authored by Kristian Lum and William Isaac.
Trips to and from Guatemala
Selection Bias and the Statistical Patterns of Mortality in Conflict.
Megan Price and Patrick Ball. 2015. Statistical Journal of the IAOS 31: 263–272. doi: 10.3233/SJI-150899. © IOS Press and the authors. All rights reserved. Creative Commons BY-NC-SA.
Calculations for the Greater Good
As executive director of the Human Rights Data Analysis Group, Megan Price uses statistics to shine the light on human rights abuses.
El problema del asesinato a líderes es más grave de lo que se piensa
Una investigación de Dejusticia y Human Rights Data Analysis Group asegura que en Colombia hay un subregistro de los asesinatos de líderes sociales que se han perpetrado en Colombia. Al analizar las diferentes cifras de homicidios que han publicado diversas organizaciones desde 2016, se llegó a la conclusión que la problemática es mayor de lo que se cree.