661 results for search: %E3%80%8C%ED%98%84%EB%AA%85%ED%95%9C%20%ED%8F%B0%ED%8C%85%E3%80%8D%20O6O~5OO~%C6%BC469%20%2049%EC%82%B4%EB%82%A8%EC%84%B1%EC%84%B9%ED%8C%8C%EB%8D%B0%EC%9D%B4%ED%8C%85%2049%EC%82%B4%EB%82%A8%EC%84%B1%EC%84%B9%ED%8C%8C%EB%8F%99%EC%95%84%EB%A6%AC%E2%98%9C49%EC%82%B4%EB%82%A8%EC%84%B1%EC%84%B9%ED%8C%8C%EB%8F%99%ED%98%B8%ED%9A%8C%E2%96%9349%EC%82%B4%EB%82%A8%EC%84%B1%EC%84%B9%ED%8C%8C%EB%A7%8C%EB%82%A8%E2%93%A5%E3%82%89%E5%BF%A6hybridity/feed/content/colombia/SV-report_2011-04-26.pdf

Karl E. Peace Award Recognizes Work of Patrick Ball

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 …

Team Page

Big Data Predictive Analytics Comes to Academic and Nonprofit Institutions to Fuel Innovation

"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

Predictive policing violates more than it protects

William Isaac and Kristian Lum. Predictive policing violates more than it protects. USA Today. December 2, 2016. © USA Today.

William Isaac and Kristian Lum. Predictive policing violates more than it protects. USA Today. December 2, 2016. © USA Today.

Documents of war: Understanding the Syrian Conflict

Megan Price, Anita Gohdes, and Patrick Ball. 2015. Significance 12, no. 2 (April): 14–19. doi: 10.1111/j.1740-9713.2015.00811.x. © 2015 The Royal Statistical Society. All rights reserved. [online abstract]

Quantifying Injustice

“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.”

The True Dangers of AI are Closer Than We Think

William Isaac is quoted.

How Many People Will Get Covid-19?

HRDAG has authored two articles in Significance that add depth to discussions around infection rates.

A Model to Estimate SARS-CoV-2-Positive Americans

We’ve built a model for estimating the true number of positives, using what we have determined to be the most reliable datasets—deaths.

Overbooking’s Impact on Pre-Trial Risk Assessment Tools

How do police officer booking decisions affect tools relied upon by judges?

Fourth CLS Story

THis story might be about Racial Justice Act work with San Francisco Public Defender’s Office

HRDAG Offers New R Package – dga

Much of the work we do at HRDAG involves estimating the number of undocumented deaths using a statistical technique called multiple systems estimation (MSE, described in more detail here). One of our goals is to make this class of methods more broadly available to human rights researchers. In particular, we are finding that Bayesian approaches are extremely valuable for MSE. Accordingly, we are pleased to offer a new R package called dga (“decomposable graphs approach”) that performs Bayesian model averaging for MSE. The main function in this package implements a model created by David Madigan and Jeremy York. This model was designed to ...

Nonprofits Are Taking a Wide-Eyed Look at What Data Could Do

In this story about how data are transforming the nonprofit world, Patrick Ball is quoted. Here's an excerpt: "Data can have a profound impact on certain problems, but nonprofits are kidding themselves if they think the data techniques used by corporations can be applied wholesale to social problems," says Patrick Ball, head of the nonprofit Human Rights Data Analysis Group. Companies, he says, maintain complete data sets. A business knows every product it made last year, when it sold, and to whom. Charities, he says, are a different story. "If you're looking at poverty or trafficking or homicide, we don't have all the data, and we're not going to," ...

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 ...

Coming soon: HRDAG 2019 Year-End Review

The online version of the 2019 Year-End Review will appear in January 2020.            

Guatemala CIIDH Data

Welcome to the web data resource for the International Center for Human Rights Research (Centro Internacional para Investigaciones en Derechos Humanos, or CIIDH). Here you will find raw data on human rights violations in Guatemala during the period 1960-1996. You're welcome to use it for your own statistical analyses. ASCII delimited (csv) Resource Information Data Dictionary Value Labels File Structure (Variables) These files are between 300-700 kilobytes. The data are stored in a zipped compression format. For an explanation of how the data are structured and what the variables represent, see the data dictionary. If you use ...

HRDAG contributes to textbook Counting Civilian Casualties

Next week, on June 11, Oxford University Press officially puts Counting Civilian Casualties: An Introduction to Recording and Estimating Nonmilitary Deaths in Conflict on the market. This textbook, edited by Taylor B. Seybolt, Jay D. Aronson, and Baruch Fischhoff, responds to the increasing concern for civilians in conflict and aims to promote scientific dialogue by highlighting the strengths and weaknesses of the most commonly used casualty recording and estimation techniques. HRDAG is very well represented here, as our colleagues have co-authored four chapters, and Nicholas Jewell, who sits on our Science Committee, has co-authored a fifth. ...

Historic verdict in Guatemala—Gen.Efraín Ríos Montt found guilty

I've been working with various projects in Guatemala to document mass violence since 1993, so in 2011, when Claudia Paz y Paz asked me to revisit the analysis I did for the Commission for Historical Clarification examining the differential mortality rates due to homicide for indigenous and non-indigenous people in the Ixil region, I was delighted. We have far better data processing and statistical methods than we had in 1998, plus much more data. I think the resulting analysis is a conservative lower bound on total homicides of indigenous people. (more…)

La misión de contar muertos

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.

Our work has been used by truth commissions, international criminal tribunals, and non-governmental human rights organizations. We have worked with partners on projects on five continents.

Donate

HRDAG

Selected projects

Stay informed about our work

©2024 Human Rights Data Analysis Group. Some rights reserved.
HRDAG is a non-profit project of Community Partners®
Privacy Policy