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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.
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.
Theoretical limits of microclustering for record linkage
James 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.
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.
Disrupt San Francisco TechCrunch 2018
On September 7, 2018, Kristian Lum and Patrick Ball participated in a panel at Disrupt San Francisco by TechCrunch. The talk was titled "Dismantling Algorithmic Bias." Brian Brackeen of Kairos was part of the panel as well, and the talk was moderated by TechCrunch reporter Megan Rose Dickey.
From the TechCrunch website, "Disrupt is a 3-day conference focused on breaking technology news and developments with big-name thought leaders who are making waves in the industry."
Video of the talk is available here, and Megan Rose Dickey's coverage is here.
Using Statistics to Assess Lethal Violence in Civil and Inter-State War
Patrick Ball and Megan Price (2019). Using Statistics to Assess Lethal Violence in Civil and Inter-State War. Annual Review of Statistics and Its Application, Volume 6. 7 March 2019. © 2019 Annual Reviews. All rights reserved. https://doi.org/10.1146/annurev-statistics-030718-105222.
Patrick Ball and Megan Price (2019). Using Statistics to Assess Lethal Violence in Civil and Inter-State War. Annual Review of Statistics and Its Application. 7 March 2019. © 2019 Annual Reviews. All rights reserved. https://doi.org/10.1146/annurev-statistics-030718-105222.
Welcoming Our 2019 Data Science Fellow
We’re pleased to announce that Camille Fassett has joined our team as our new data science fellow.
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.
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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.
Megan Price Elected Board Member of Tor Project
Today The Tor Project announced that it has elected a new Board of Directors, and among them is HRDAG executive director Megan Price. The Tor Project is a nonprofit advocacy group that promotes online privacy and provides software that helps users opt out of online tracking.
Megan and Patrick have long maintained that encryption and privacy are essential for enabling human rights work. Patrick's ideas are described in Monday's FedScoop story about encryption, human rights, and the U.S. State Department.
“Human rights groups depend on strong cryptography in order to hold governments accountable," says Patrick. "HRDAG depends on local human ...
Epidemiology has theories. We should study them.
With so many dashboards and shiny visualizations, how can an interested non-technical reader find good science among the noise?
When Data Doesn’t Tell the Whole Story
This blog is a part of International Justice Monitor’s technology for truth series, which focuses on the use of technology for evidence and features views from key proponents in the field.
As highlighted by other posts in this series, emerging technology is increasing the amount and type of information available, in some contexts, to criminal and other investigations. Much of what is produced by these emerging technologies (Facebook posts, tweets, YouTube videos, text messages) falls in the category we refer to as “found” data. By “found” data we mean data not generated for a specific investigation, but instead, that is generated for ...
How We Choose Projects
For more than 20 years, HRDAG has been carving out a niche in the international human rights movement. We know what we’re good at and what we’re not qualified to do. We know what quantitative questions we think are important for the community, and we know what we like to do. These preferences guide us as we consider whether to take on a project. We’re scientists, so our priorities will come as no surprise. We like to stick to science (not ideology), avoid advocacy, answer quantifiable questions, and increase our scientific understanding.
While we have no hard-and-fast rules about what projects to take on, we organize our deliberation ...
Reflections: Pivotal Moments in Freetown
The summer of 2002 in Washington, DC, was steamy and hot, which is how I remember my introduction to HRDAG. I had begun working with them, while they were still at AAAS, in the late spring, learning all about their core concepts: duplicate reporting and MSE, controlled vocabularies, inter-rater reliability, data models and more. The days were long, with a second shift more often than not running late into the evening. In addition to all the learning, I also helped with matching for the Chad project – that is, identifying multiple records of the same violation – back when matching was done by hand. But it was not long after I arrived in Washington ...
The story of one document inside the AHPN
The beginnings are crucial in every step—as critical as the beginning of sound, life, hope, and justice. Here are some first steps from the AHPN (Archivo Histórico de la Policía Nacional).
This is the story of Oficio Number COC/207-laov, a document that at first appears uninteresting. But this is not just any oficio*. This is one of the many documents that helped bring to trial the people responsible for the disappearance of Edgar Fernando García. A father, husband, son, and student, García was, like many people today, interested in changing his community for the better. (more…)
Matching the Libro Amarillo to Historical Human Rights Datasets in El Salvador
Patrick Ball (2014). A memo accompanying the release of The Yellow Book. August 20, 2014. © 2014 HRDAG. Creative Commons BY-NC-SA.[pdf español]
Human Rights and the Decentralized Web
Our partners were eager to learn and talk about emerging decentralized technology.
Data Mining for Good: CJA Drink + Think
At the Center for Justice and Accountability's happy hour, "Drink and Think," Patrick Ball spoke about "Data Mining for Good." The talk included a discussion of how HRDAG brings human rights abusers to justice through data analysis, and HRDAG's work conducting quantitative analysis for truth commissions, NGOs, the UN and other partners. The event was held at Eventbrite. More photos are below.
The Center for Justice and Accountability
Young Professionals' Committee for Human Rights
September 16, 2014
San Francisco, California
Link to CJA event page
Back to Talks
All photos © 2014 Carter Brooks.
Letter from the Executive Director
Dear Friends,
This has been quite a year, and I don’t just mean the recent political events in the United States, Europe and the Middle East.
Thanks to your ongoing support, HRDAG has a number of accomplishments to be proud of this year:
Patrick’s testimony in the trial of Hissene Habré for crimes against humanity was cited by the judges three times in their determination of guilt.
We launched a book describing ten years of collaborative work with the Historic Archive of the National Police in Guatemala.
We contributed quantitative analyses to Amnesty International’s report on deaths in Syrian custody, and published an ...
Predictive Policing Reinforces Police Bias
Issues surrounding policing in the United States are at the forefront of our national attention. Among these is the use of “predictive policing,” which is the application of statistical or machine learning models to police data, with the goal of predicting where or by whom crime will be committed in the future. Today Significance magazine published an article on this topic that I co-authored with William Isaac. Significance has kindly made this article open access (free!) for all of October. In the article we demonstrate the mechanism by which the use of predictive policing software may amplify the biases that already pervade our criminal ...
Learning to Learn: Reflections on My Time at HRDAG
So much of what I learned at HRDAG was intangible, and I'm grateful to have been able to go deep.
The UDHR Turns 70
We're thinking about how rigorous analysis can fortify debates about components of our criminal justice system such as cash bail, pretrial risk assessment and fairness in general.