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HRDAG Names New Board Member Margot Gerritsen

Margot is a professor in the Department of Energy Resources Engineering at Stanford University, interested in computer simulation and mathematical analysis of engineering processes.

Kristian Lum in Bloomberg

The interview poses questions about Lum's focus on artificial intelligence and its impact on predictive policing and sentencing programs.

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 ...

Reflections: It Began In Bogotá

It was July of 2006, I’d spent five years working at a local human rights NGO in Bogotá, and I had reached retirement age. But then a whole new world opened up for me to discover. Tamy Guberek, then HRDAG Latin America coordinator, whom I had met at the NGO, approached me about becoming part of the HRDAG Colombia team as a research/administrative assistant. Over a cup of suitably Colombian coffee, the deal was quickly "signed.” My responsibilities ranged from fundraising to translations, from support in data gathering for estimates on homicides and disappearances in various regions of Colombia to editorial support to different Benetech-HRDAG ...

Reflections: HRDAG Was Born in Washington

I began working with HRDAG in the summer of 2001 before it was ever even called HRDAG. In fact, not intended as a boast, I think I’m responsible for coming up with the name. After contracting with Dr. Patrick Ball for a time writing the Analyzer data management platform, I left New York City and joined him in Washington, DC, at AAAS in 2002. Soon after starting, Patrick decided to establish an identity for this new team, consisting mainly of myself, Miguel Cruz and a handful of field relationships. We discussed what to name it briefly in the AAAS Science & Policy break room, which at the time, being in the mind of unclever descriptive naming ...

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," ...

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A Definition of Database Design Standards for Human Rights Agencies.

/wp-content/uploads/2013/01/Definition_of_Database_Design_Standards_1994.pdf

Patrick Ball. “A Definition of Database Design Standards for Human Rights Agencies.” © 1994 American Association for the Advancement of Science. [pdf]


Death rate in Habre jails higher than for Japanese POWs, trial told

Patrick Ball of the California-based Human Rights Data Analysis Group said he had calculated the mortality rate of political prisoners from 1985 to 1988 using reports completed by Habre’s feared secret police.


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.


Truth Commissioner


Welcoming our new Technical Lead

After almost two months of searching for the perfect fit, we’re very pleased to announce that Josh Shadlen has joined HRDAG as our new technical lead. Finding Josh was no easy feat. We were looking for what many people would call a “data scientist,” that is, someone with expertise in both computer science and statistics. These days, “data science” is one of the hottest fields out there. Bringing the perfect mix of academic depth and thoughtful reflection, Josh stood out for us. With prior jobs including gigs at Silicon Valley startups and Twitter, he’s got high-level (more…)

Hunting for Mexico’s mass graves with machine learning

“The model uses obvious predictor variables, Ball says, such as whether or not a drug lab has been busted in that county, or if the county borders the United States, or the ocean, but also includes less-obvious predictor variables such as the percentage of the county that is mountainous, the presence of highways, and the academic results of primary and secondary school students in the county.”


Estimating Deaths in Timor-Leste


A better statistical estimation of known Syrian war victims

Researchers from Rice University and Duke University are using the tools of statistics and data science in collaboration with Human Rights Data Analysis Group (HRDAG) to accurately and efficiently estimate the number of identified victims killed in the Syrian civil war.

Using records from four databases of people killed in the Syrian war, Chen, Duke statistician and machine learning expert Rebecca Steorts and Rice computer scientist Anshumali Shrivastava estimated there were 191,874 unique individuals documented from March 2011 to April 2014. That’s very close to the estimate of 191,369 compiled in 2014 by HRDAG, a nonprofit that helps build scientifically defensible, evidence-based arguments of human rights violations.


Analyze This!


Doing a Number on Violators


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.


One Better

The University of Michigan College of Literature, Science and the Arts profiled Patrick Ball in its fall 2016 issue of the alumni magazine. Here’s an excerpt:

Ball believes doing this laborious, difficult work makes the world a more just place because it leads to accountability.

“My part is a specific, narrow piece, which just happens to fit with the skills I have,” he says. “I don’t think that what we do is in any way the best or most important part of human rights activism. Sometimes, we are just a footnote—but we are a really good footnote.”


The Data Scientist Helping to Create Ethical Robots

Kristian Lum is focusing on artificial intelligence and the controversial use of predictive policing and sentencing programs.

What’s the relationship between statistics and AI and machine learning?

AI seems to be a sort of catchall for predictive modeling and computer modeling. There was this great tweet that said something like, “It’s AI when you’re trying to raise money, ML when you’re trying to hire developers, and statistics when you’re actually doing it.” I thought that was pretty accurate.


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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