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In this afternoon "Lightning Talk" at RightsCon 2014, Megan Price spoke about the importance of using models to adjust for variability when reporting human rights violations and mentioned innovative tools that can be used for tracking abuses.
RIGHTSCON
March 4, 2014
San Francisco, California
Link to RightsCon program
Back to Talks
"Revolution Analytics will allow HRDAG to handle bigger data sets and leverage the power of R to accomplish this goal and uncover the truth." Director of Research Megan Price is quoted.
REVOLUTION ANALYTICS
Press release
February 4, 2014
Link to press release
Back to Press Room
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 her work on statistical issues in criminal justice, Lum has studied uses of predictive policing—machine learning models to predict who will commit future crime or where it will occur. In her work, she has demonstrated that if the training data encodes historical patterns of racially disparate enforcement, predictions from software trained with this data will reinforce and—in some cases—amplify this bias. She also currently works on statistical issues related to criminal “risk assessment” models used to inform judicial decision-making. As part of this thread, she has developed statistical methods for removing sensitive information from training data, guaranteeing “fair” predictions with respect to sensitive variables such as race and gender. Lum is active in the fairness, accountability, and transparency (FAT) community and serves on the steering committee of FAT, a conference that brings together researchers and practitioners interested in fairness, accountability, and transparency in socio-technical systems.
Today Amnesty International released “‘It breaks the human’: Torture, disease and death in Syria’s prisons ,” a report detailing the conditions and mortality in Syrian prisons from 2011 to 2015, including data analysis conducted by HRDAG.
The report provides harrowing accounts of ill treatment of detainees in Syrian prisons since the conflict erupted in March 2011, and publishes HRDAG’s estimate of the number of killings that occurred inside the prisons.
To accompany the report, HRDAG has released a technical memo that explains the methodology, sources, and implications of the findings. The HRDAG team used data from four ...
The American Statistical Association’s 2018 Karl E. Peace Award for Outstanding Statistical Contributions for the Betterment of Society recently recognized the work of leading human rights mathematician Patrick Ball of the Human Rights Data Analysis Group (HRDAG). The award is presented annually to statisticians whose exemplary statistical research is matched by the impact their work has had on the lives of people.
Established by the family of Karl E. Peace in honor of his work for the good of society, the award—announced at the Joint Statistical Meetings—is bestowed upon distinguished individual(s) who have made substantial contributions to the statistical profession, contributions that have led in direct ways to improving the human condition. Recipients will have demonstrated through their accomplishments their commitment to service for the greater good.”
This year, Ball became the 10th recipient of the award. Read more …
Megan Price, Anita Gohdes and Patrick Ball (2016). Human Rights Data Analysis Group, commissioned by Amnesty International. August 17, 2016. © 2016 HRDAG. Creative Commons BY-NC-SA.
Megan Price (2022). Beautiful game, ugly truth? Significance, 19: 18-21. December 2022. © The Royal Statistical Society. https://doi.org/10.1111/1740-9713.01702
Megan Price (2022). Beautiful game, ugly truth? Significance, 19: 18-21. December 2022. © The Royal Statistical Society. https://doi.org/10.1111/1740-9713.01702
Patrick Ball and Jana Asher (2002). “Statistics and Slobodan: Using Data Analysis and Statistics in the War Crimes Trial of Former President Milosevic.” Chance, vol. 15, No. 4, 2002. Reprinted with permission ofChance. © 2002 American Statistical Association. All rights reserved.
Anjana Samant, Noam Shemtov, Kath Xu, Sophie Beiers, Marissa Gerchick, Ana Gutierrez, Aaron Horowitz, Tobi Jegede, Tarak Shah (2023). The Allegheny Family Screening Tool’s Overestimation of Utility and Risk. Logic(s). 13 December, 2023. Issue 20.
Anjana Samant, Noam Shemtov, Kath Xu, Sophie Beiers, Marissa Gerchick, Ana Gutierrez, Aaron Horowitz, Tobi Jegede, Tarak Shah (2023). The Allegheny Family Screening Tool’s Overestimation of Utility and Risk. Logic(s). 13 December, 2023. Issue 20.
Today is a very special day for all of us at HRDAG. This is, of course, the 68th anniversary of the Universal Declaration of Human Rights—but this day also marks our 25th year of using statistical science to support the advancement of human rights.
It started 25 years ago, in December 1991, in San Salvador, when Patrick Ball was invited to work with the Salvadoran Lutheran Church to design a database to keep track of human rights abuses committed by the military in El Salvador. That work soon migrated to the NGO Human Rights Commission (CDHES). Fueled by thin beer and pupusas, Patrick dove into the deep world of data from human rights testimonies, ...
As we get ready to begin our fourth year as an independent nonprofit, we are, as always, indebted to our Advisory Board and to our funders for their support and vision. We’re finishing up a busy year that took us to Dakar (for the trial of former Chadian dictator Hissène Habré), Pristina (for the release of the Kosovo Memory Book), Colombia (for work on a book about the Guatemalan Police Archives), and kept us busy here at home working on police violence statistics. But one of our biggest victories has been to score a new, talented, wise Advisory Board member—Michael Bear Kleinman, whom we first met when he was working with Humanity United.
...
Everyone I had the pleasure of interacting with enriched my summer in some way.
Maria Gargiulo has joined HRDAG as a Statistician.
HRDAG and our partners Data Cívica and the Iberoamericana University created a machine-learning model to predict which counties (municipios) in Mexico have the highest probability of unreported hidden graves. The predictions help advocates to bring public attention and government resources to search for the disappeared in the places where they are most likely to be found.
Context
For more than ten years, Mexican authorities have been discovering hidden graves (fosas clandestinas). The casualties are attributed broadly—and sometimes inaccurately—to the country’s “drug war,” but the motivations and perpetrators behind the mass murders ...
THis story might be about Racial Justice Act work with San Francisco Public Defender’s Office
As a woman, mother and sociologist who is curious about the patterns of our political past in Guatemala, I feel privileged to know and work with the HRDAG team. Collaborating and learning from people like Patrick, Megan, Suzanne, Beatriz and Tamy has been an invaluable gift. I have discovered many things, both human and academic. For example, I’ve learned new ways of seeing what seemed everyday and simple, to discover that not only do the social sciences and statistics work hand in hand, but that they are critical for understanding Guatemala’s reality.
Twenty years ago, on 29 December, 1996, Guatemala made history by signing the Guatemala Peace ...
Margot is a professor in the Department of Energy Resources Engineering at Stanford University, interested in computer simulation and mathematical analysis of engineering processes.
