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Meet a Mathematician! – Tarak Shah
“You look at all the huge problems in the world, and you are trying to find ways to plug in. And it turns out—whether it is cooking a meal for somebody who’s hungry or cleaning some data so that you can do analysis on the things that we actually need to do to advance our work to make the world a little bit better— the main thing they require is somebody to care enough to do it.”
Who Knows? Fact-Finding in a Failing State w/ HRDAG and Data + Society
How do scientists and statisticians stand up to authoritarianism, especially when it happens in their home countries? That was the topic tackled by the Computer Says Maybe podcast, featuring HRDAG’s Executive Director Megan Price, Data and Society’s Janet Haven and Charlton McIlwan, and podcast host Alix Dunn.
Patrick Ball on Using Statistics to Uncover Truth
“The story of missing data is what I’ve spent my whole career thinking about,” explained Patrick. “The joke in our team is if the data were perfect, lawyers would do this with excel.”
Press Release, Timor-Leste, February 2006
Counting the Dead in Sri Lanka
Bangladesh
The Bigness of Big Data: samples, models, and the facts we might find when looking at data
Patrick Ball. 2015. The Bigness of Big Data: samples, models, and the facts we might find when looking at data. In The Transformation of Human Rights Fact-Finding, ed. Philip Alston and Sarah Knuckey. New York: Oxford University Press. ISBN: 9780190239497. © The Oxford University Press. All rights reserved.
Views to a Kill: Exploring the Implications of Source Selection in the Case of Guatemalan State Terror, 1977-1996.
Christian Davenport and Patrick Ball. “Views to a Kill: Exploring the Implications of Source Selection in the Case of Guatemalan State Terror, 1977-1996.” Journal of Conflict Resolution 46(3): 427-450. 2002. doi.org/10.1177/0022002702046003005
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,” he says. “That’s why these amazing techniques that the industry people have are great in industry, but they don’t actually generalize to our space very well.”
5 Humanitarian FOSS Projects to Watch
Dave Neary described “5 Humanitarian FOSS Projects to Watch,” listing HRDAG’s work on police homicides in the U.S. and other human rights abuses in other countries.
Recognising Uncertainty in Statistics
In Responsible Data Reflection Story #7—from the Responsible Data Forum—work by HRDAG affiliates Anita Gohdes and Brian Root is cited extensively to make the point about how quantitative data are the result of numerous subjective human decisions. An excerpt: “The Human Rights Data Analysis Group are pioneering the way in collecting and analysing figures of killings in conflict in a responsible way, using multiple systems estimation.”
Policing
PredPol amplifies racially biased policing
HRDAG associate William Isaac is quoted in this article about how predictive policing algorithms such as PredPol exacerbate the problem of racial bias in policing.
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.”