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Reflections: Challenging Tasks and Meticulous Defenders
The World According to Artificial Intelligence (Part 1)
The World According to Artificial Intelligence: Targeted by Algorithm (Part 1)
The Big Picture: The World According to AI explores how artificial intelligence is being used today, and what it means to those on its receiving end.
Patrick Ball is interviewed: “Machine learning is pretty good at finding elements out of a huge pool of non-elements… But we’ll get a lot of false positives along the way.”
New publication in BIOMETRIKA
Casanare, Colombia
To predict and serve?
Kristian Lum and William Isaac (2016). To predict and serve? Significance. October 10, 2016. © 2016 The Royal Statistical Society.
Pretrial Risk Assessment Tools
Sarah L. Desmarais and Evan M. Lowder (2019). Pretrial Risk Assessment Tools: A Primer for Judges, Prosecutors, and Defense Attorneys. Safety and Justice Challenge, February 2019. © 2019 Safety and Justice Challenge. <<HRDAG’s Kristian Lum and Tarak Shah served as Project Members and made significant contributions to the primer.>>
The Art and Science of Coding AHPN Documents
Full Updated Statistical Analysis of Documentation of Killings in the Syrian Arab Republic
Price, Megan, Jeff Klingner, Anas Qtiesh, and Patrick Ball. 2013. Commissioned by the United Nations Office of the High Commissioner for Human Rights (OHCHR). Human Rights Data Analysis Group (June 13). © 2013 HRDAG. Creative Commons BY-NC-SA. [pdf via UN]
Updated Statistical Analysis of Documentation of Killings in the Syrian Arab Republic
Megan Price, Anita Gohdes, and Patrick Ball (2014). Human Rights Data Analysis Group, commissioned by the United Nations Office of the High Commissioner for Human Rights (OHCHR). August 22, 2014. © 2014 HRDAG. Creative Commons BY-NC-SA.
Reflections on Data Science for Real-World Problems
Training with HRDAG: Rules for Organizing Data and More
Focus on Good Science, not Scientists
Learning to Learn: Reflections on My Time at HRDAG
Counting Casualties in Syria
Unbiased algorithms can still be problematic
“Usually, the thing you’re trying to predict in a lot of these cases is something like rearrest,” Lum said. “So even if we are perfectly able to predict that, we’re still left with the problem that the human or systemic or institutional biases are generating biased arrests. And so, you still have to contextualize even your 100 percent accuracy with is the data really measuring what you think it’s measuring? Is the data itself generated by a fair process?”
HRDAG Director of Research Patrick Ball, in agreement with Lum, argued that it’s perhaps more practical to move it away from bias at the individual level and instead call it bias at the institutional or structural level. If a police department, for example, is convinced it needs to police one neighborhood more than another, it’s not as relevant if that officer is a racist individual, he said.