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Happy Hacking

From my first introduction to the HRDAG community at the annual retreat it was clear to me that mentorship is an organizational priority and that the contributions of interns are valued. Much of my first couple weeks as a summer intern at HRDAG were spent familiarizing myself with Patrick’s paradigm for principled data processing. At the same time, I was learning the skills and tricks (bash, make, vim, git) that promote an effortless programming workflow, a pursuit that Patrick calls “sharpening the saw” (just like in programming, you can cut down a tree with a dull blade, but your life will be much easier if you take the time to sharpen ...

Patrick Ball wins the Karl E. Peace Award

Patrick Ball won the Karl E. Peace Award for Outstanding Statistical Contributions for the Betterment of Society at the 2018 Joint Statistical Meeting.

New publication in BIOMETRIKA

New paper in Biometrika, co-authored by HRDAG's Kristian Lum and James Johndrow: Theoretical limits of microclustering in record linkage.

Skoll World Forum 2018

Illuminating Data's Dark Side: Big data create conveniences, but we must consider who designs these tools, who benefits from them, and who is left out of the equation.

Reflections: A Meaningful Partnership between HRDAG and Benetech

I joined the Benetech Human Rights Program at essentially the same time that HRDAG did, coming to Benetech from years of analyzing data for large companies in the transportation, hospitality and retail industries. But the data that HRDAG dealt with was not like the data I was familiar with, and I was fascinated to learn about how they used the data to determine "who did what to whom." Although some of the methodologies were similar to what I had experience with in the for-profit sector, the goals and beneficiaries of the analyses were very different. At Benetech, I was initially predominantly focused on product management for Martus, a free ...

Always Learning

The data science field is always changing, which means that I'll always be learning.

Building Capacity in Colombia: Truth and Reconciliation

The datasets contributed by 30+ organizations do a wonderful job of tallying the violence that was observed—but they don’t account for the violence that nobody witnessed or documented.

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.

Report on Measures of Fairness in NYC Risk Assessment Tool

The report tries to answer the question of whether a particular risk assessment model reinforces racial inequalities in the criminal justice system.

Killings of Social Movement Leaders in Colombia

Using multiple system estimation, we estimate the total population of social movement leaders killed in Colombia during 2018.

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?

How Many People Will Get Covid-19?

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

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.

Stay informed about our work

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HRDAG’s Year in Review: 2020

In 2020, HRDAG provided clarity on issues related to the pandemic, police misconduct, and more.

HRDAG Names New Board Member William Isaac

William Isaac joins HRDAG's Advisory Board, bringing expertise in fairness and artificial intelligence.

Donate with Cryptocurrency

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 ...

Donate with Cryptocurrency

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 ...

Uncovering Police Violence in Chicago: A collaboration between HRDAG and Invisible Institute

In 2014 and again in 2020, the Invisible Institute, a Chicago grassroots organization, won lawsuits that granted them access to decades of complaints of misconduct by Chicago police officers. The collection contains hundreds of thousands of pages of allegation forms, memos, various police administrative forms, interviews and testimonies, pictures, and even embedded audio files. The Institute published scanned images on the Citizens Police Data Project, and is using them for a project with HRDAG known as Beneath the Surface, which is a detailed investigation into gender-based violence by Chicago Police. Image: David Peters Often, gender-b...

Weapons of Math Destruction

Weapons of Math Destruction: invisible, ubiquitous algorithms are ruining millions of lives. Excerpt:

As Patrick once explained to me, you can train an algorithm to predict someone’s height from their weight, but if your whole training set comes from a grade three class, and anyone who’s self-conscious about their weight is allowed to skip the exercise, your model will predict that most people are about four feet tall. The problem isn’t the algorithm, it’s the training data and the lack of correction when the model produces erroneous conclusions.


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.

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