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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.
Multiple Systems Estimation: Stratification and Estimation
<< Previous post, MSE: The Matching Process
Q10. What is stratification?
Q11. [In depth] How do HRDAG analysts approach stratification, and why is it important?
Q12. How does MSE find the total number of violations?
Q13. [In depth] What are the assumptions of two-system MSE (capture-recapture)? Why are they not necessary with three or more systems?
Q14. What statistical model(s) does HRDAG typically use to calculate MSE estimates? (more…)
Measuring the Mortality Consequences of Armed Conflict in Amritsar, India: A New Approach to the Indirect Sampling of Conflict-Related Mortality
Romesh Silva and Jeff Klingner. “Measuring the Mortality Consequences of Armed Conflict in Amritsar, India: A New Approach to the Indirect Sampling of Conflict-Related Mortality.” Poster presented at the Population Association of America 2011 Annual Meeting. © 2011 Benetech. Creative Commons BY-NC-SA.
Drug-Related Killings in the Philippines
HRDAG analysis shows that the government figures are a gross underestimation of the drug-related killings in the Philippines.
HRDAG is hiring – technical lead
If this could be you, let us know. Also, please feel free to pass on this link to great people.
Job Title. Technical lead with a hacker's heart
Location. A cool office in SOMA, San Francisco. You need to be on-site with us.
What we do. The Human Rights Data Analysis Group (HRDAG) develops statistical techniques to measure human rights atrocities. Our work helps bring dictators to justice through data analysis of human rights atrocities around the world. Over more than 20 years, our small team has developed technology and statistical techniques to take disjoint, incomplete, and inaccurate information from conflict zones and process it to identify ...
Guatemala 1993-1999 – Using MSE to Estimate the Number of Deaths
Propelled by the impact of data analysis in El Salvador, Patrick Ball applied his WDWTW model to human rights information in other countries. Throughout the 1990’s, Ball worked at the American Association for the Advancement of Science (AAAS) analyzing large-scale human rights violations in Ethiopia, South Africa, Haiti and Guatemala. Together with senior scientific colleagues, including statistician Dr. Herb Spirer, Ball developed new methods for analyzing state-sanctioned violence. This chapter documents how the research expanded when a group of nongovernmental organizations in Guatemala asked the scientific community to gather and analyze ...
RustConf 2019, and systems programming as a data scientist
It could make sense to use Rust as a data journalist for in-browser computations, and other thoughts from RustConf.
Estimating the Number of SARS-CoV-2 Infections and the Impact of Mitigation Policies in the United States
James Johndrow, Patrick Ball, Maria Gargiulo, and Kristian Lum. (2020). Estimating the Number of SARS-CoV-2 Infections and the Impact of Mitigation Policies in the United States. Harvard Data Science Review. 24 November, 2020. © The Authors, 2020, CC BY 4.0. https://doi.org/10.1162/99608f92.7679a1ed
James Johndrow, Patrick Ball, Maria Gargiulo, and Kristian Lum. (2020). Estimating the Number of SARS-CoV-2 Infections and the Impact of Mitigation Policies in the United States. Harvard Data Science Review. 24 November, 2020. © The Authors, 2020, CC BY 4.0. https://doi.org/10.1162/99608f92.7679a1ed
Our Story
Dec 10, 1991
HRDAG is born when Patrick Ball begins database design at the Human Rights Office of the Salvadoran Lutheran Church. The work soon moves to the non-governmental Human Rights Commission (CDHES). The database analysis identified the 100 worst officers in the Salvadoran military — who were forced to resign as part of the peace process.
1994
Patrick publishes A Definit...
How Data Analysis Confirmed the Bias in a Family Screening Tool
In Pittsburgh, children were at risk of being separated from their disabled parents, and the algorithm used to assist with decisions looked suspicious. HRDAG joined the ACLU to learn why.
Reflections: Challenging Tasks and Meticulous Defenders
I have made it my personal objective to amplify HRDAG's message of being extra careful and scientifically rigorous with human rights data.
The Day We Fight Back
Today, February 11, is the day of national protests against the National Security Administration.
The critical threat is mass surveillance. In the words of The Day We Fight Back, “Together we will push back against powers that seek to observe, collect, and analyze our every digital action. Together, we will make it clear that such behavior is not compatible with democratic governance. Together, if we persist, we will win this fight.” (more…)
Patrick Ball Honored as New ASA Fellow
We’re very happy to announce that our executive director, Patrick Ball, has been elected as a Fellow of the American Statistical Association (ASA), as announced by ASA President Nathaniel Schenker. Patrick is one of 63 new ASA Fellows to be honored this year in a ceremony at the Joint Statistical Meetings, which will take place this August 5 in Boston, Massachusetts. (more…)
Training with HRDAG: Rules for Organizing Data and More
I had the pleasure of working with Patrick Ball at the HRDAG office in San Francisco for a week during summer 2016. I knew Patrick from two workshops he previously hosted at the University of Washington’s Centre for Human Rights (UWCHR). The workshops were indispensable to us at UWCHR as we worked to publish a number of datasets on human rights violations during the El Salvador Civil War. The training was all the more helpful because the HRDAG team was so familiar with the data. As part of an impressive career which took him from Ethiopia and Kosovo to Haiti and El Salvador among others, Patrick himself had worked on gathering and analysing ...
Sri Lanka
Ten years after the war ended in Sri Lanka, we still don’t know to the nearest ten thousand how many people perished. The estimates for the death toll for the last five months of the war alone vary between 7000 and 147,000. In 2011, the UN said it thought approximately 40,000 civilians had died; then in 2012 an internal UN report estimated it was at least 70,000. Population data from World Bank and UN sources indicated that more than 100,000 Tamils living in the conflict areas in the north have not returned home after the war.
HRDAG has provided technical assistance to a broad range of non-governmental human rights organizations in Sri ...
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]
Frequently Asked Questions
Multiple Systems Estimation
What is MSE?
What do you mean by statistical inference?
What is an overlap, and how do we know when lists overlap?
How does MSE find the total number of violations?
How was MSE originally developed?
How does the Benetech Human Rights Program use MSE?
1. What is MSE?
A: Multiple Systems Estimation, or MSE, is a family of techniques for statistical inference. MSE uses the overlaps between several incomplete lists of human rights violations to determine the total number of violations.
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2. What do you mean by statistical inference?
A: ...