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This week, we join our friends and colleagues in feeling horrified by the violence in Charlottesville, Virginia. As we have for the past 26 years, we stand with the victims of violence and support human rights and dignity for all. We spend our careers observing and documenting mass political violence across the world. The demands by the so-called “alt-right” to normalize racism and social exclusion are all too familiar to us.
At HRDAG, our work is always guided by the Universal Declaration of Human Rights (UDHR). We reaffirm our commitment to these principles, in particular that the “recognition of the inherent dignity and of the equal and ...
In this free, downloadable report, Mike Barlow of O’Reilly Media cites several examples of how data and the work of data scientists have made a measurable impact on organizations such as DataKind, a group that connects socially minded data scientists with organizations working to address critical humanitarian issues. HRDAG—and executive director Megan Price—is one of the first organizations whose work is mentioned.
THis story might be about Racial Justice Act work with San Francisco Public Defender’s Office
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.
One of the researchers, a Michigan State PhD candidate named William Isaac, had not previously heard of New Orleans’ partnership with Palantir, but he recognized the data-mapping model at the heart of the program. “I think the data they’re using, there are serious questions about its predictive power. We’ve seen very little about its ability to forecast violent crime,” Isaac said.
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.
“In 2016, two researchers, the statistician Kristian Lum and the political scientist William Isaac, set out to measure the bias in predictive policing algorithms. They chose as their example a program called PredPol. … Lum and Isaac faced a conundrum: if official data on crimes is biased, how can you test a crime prediction model? To solve this technique, they turned to a technique used in statistics and machine learning called the synthetic population.”
In our work, we merge many databases to figure out how many people have been killed in violent conflict. Merging is a lot harder than you might think.
Many of the database records refer to the same people--the records are duplicated. We want to identify and link all the records that refer to the same victims so that each victim is counted only once, and so that we can use the structure of overlapping records to do multiple systems estimation.
Merging records that refer to the same person is called entity resolution, database deduplication, or record linkage. For definitive overviews of the field, see Scheuren, Herzog, and Winkler, Data Quality ...
What is a controlled vocabulary?
A controlled vocabulary provides the ability to transform information that has been collected on violations, victims, and perpetrators into a countable set of data categories. It is important that this process be done without discarding relevant information and without misrepresenting the collected information.
Why is it necessary?
The data collected about human rights violations originates from a wide range of information sources – legal case files, newspaper articles, e-mails, faxes, letters, phone conversations, testimonies, interviews, radio and television programs, video clips, and photos. This wide range of ...
As of today, the Human Rights Data Analysis Group (HRDAG) is an independent* non-profit! It's been a long time coming, and we're delighted to have gotten to this point. HRDAG is a non-profit, non-partisan organization that applies rigorous science to the analysis of human rights violations around the world; for more information, see our About Us page.
Benetech has spun out the scientific and statistical part of the Human Rights Program to HRDAG. The spinout includes (as staff) me -- Patrick Ball -- and Dr Megan Price, as well as our many part-time scientific and field consultants (a list is here). The software and technology component of our work -- ...
Working at the Historic Archive of the National Police (AHPN) of Guatemala, there are many skills I learned on the job. My many years of work on the team that studies the recovered documents have been like a custom-made course in how to do quantitative research.
The Archive documents I study are the result of 36 years of creation during civil war (1960 to 1996). Many of these documents are simply administrative—but we are able to use them to understand patterns that occurred during the conflict, to get a sense of what mattered to the National Police and what didn’t. Our quantitative research shows us the Police behavior in broad strokes. ...
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The Rafto Foundation, an international human rights organization, has bestowed the 2021 Rafto Prize to HRDAG for its distinguished work defending human rights and democracy.
Sloppy recordkeeping by Chicago police has compromised missing persons cases. HRDAG is working with Pulitzer Prize-winning Invisible Institute to find justice for the missing.
The modular nature of the workflow and use of Git allowed us to work on different parts of the project from across the country.
Help HRDAG use data science to work for justice, accountability, and human rights. We are nonpartisan and nonprofit, but we are not neutral; we are always on the side of human rights.
Cryptocurrency donations to 501(c)3 charities receive the same tax treatment as stocks. Your donation is a non-taxable event, meaning you do not owe capital gains tax on the appreciated amount and can deduct it on your taxes. This makes Bitcoin and other cryptocurrency donations one of the most tax efficient ways to support us.
We are a team of experts in machine learning, applied and mathematical statistics, computer science, demography, and social science, and ...
This is a story about pretrial risk assessment.
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.
HRDAG associate Miguel Cruz has an epiphany. All those data he’s drowning in? Each datapoint is a personal tragedy, a story both dark and urgent, and he’s privileged to have access.
