711 results for search: %ED%99%8D%EB%B3%B4%EC%A0%84%EB%AC%B8%E3%85%BF%ED%85%94%EB%A0%88adgogo%E3%85%BF%EA%B0%81%EC%82%B0%EA%B1%B4%EC%A0%84%EB%A7%88%EC%82%AC%EC%A7%80%E3%81%BF%ED%99%8D%EB%B3%B4%E2%94%BA%EC%A0%84%EB%AC%B8%E2%82%AA%EA%B0%81%EC%82%B0%E4%9D%90%EA%B1%B4%EC%A0%84%EB%A7%88%EC%82%AC%EC%A7%80%E7%AE%A0nonbeing/feed/rss2/jeffklinger/privacy
Using Data to Reveal Human Rights Abuses
Profile touching on HRDAG’s work on the trial and conviction of Hissène Habré, its US Policing Project, data integrity, data archaeology and more.
The Forensic Humanitarian
International human rights work attracts activists and lawyers, diplomats and retired politicians. One of the most admired figures in the field, however, is a ponytailed statistics guru from Silicon Valley named Patrick Ball, who has spent nearly two decades fashioning a career for himself at the intersection of mathematics and murder. You could call him a forensic humanitarian.
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.
Guatemala: The Secret Files
Guatemala is still plagued by urban crime, but it is peaceful now compared to the decades of bloody civil war that convulsed the small Central American country. As he arrives in the capital, Guatemala City, FRONTLINE/World reporter Clark Boyd recalls, “When the fighting ended in the 1990s, many here wanted to move on, burying the secrets of the war along with hundreds of thousands of the dead and disappeared. But then, in July 2005, the past thundered back.”
How data science is changing the face of human rights
On the heels of the Women in Data Science conference, HRDAG executive director Megan Price says, “I think creativity and communication are probably the two most important skills for a data scientist to have these days.”
Documenting Syrian Deaths with Data Science
Coverage of Megan Price at the Women in Data Science Conference held at Stanford University. “Price discussed her organization’s behind-the-scenes work to collect and analyze data on the ground for human rights advocacy organizations. HRDAG partners with a wide variety of human rights organizations, including local grassroots non-governmental groups and—most notably—multiple branches of the United Nations.”
What happens when you look at crime by the numbers
Kristian Lum’s work on the HRDAG Policing Project is referred to here: “In fact, Lum argues, it’s not clear how well this model worked at depicting the situation in Oakland. Those data on drug crimes were biased, she now reports. The problem was not deliberate, she says. Rather, data collectors just missed some criminals and crime sites. So data on them never made it into her model.”
Benetech’s Human Rights Data Analysis Group Publishes 2010 Analysis of Human Rights Violations in Five Countries,
Analysis of Uncovered Government Data from Guatemala and Chad Clarifies History and Supports Criminal Prosecutions
By Ann Harrison
The past year of research by the Benetech Human Rights Data Analysis Group (HRDAG) has supported criminal prosecutions and uncovered the truth about political violence in Guatemala, Iran, Colombia, Chad and Liberia. On today’s celebration of the 62nd anniversary of the Universal Declaration of Human Rights, HRDAG invites the international community to engage scientifically defensible methodologies that illuminate all human rights violations – including those that cannot be directly observed. 2011 will mark the 20th year that HRDAG researchers have analyzed the patterns and magnitude of human rights violations in political conflicts to determine how many of the killed and disappeared have never been accounted for – and who is most responsible.
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.”
Truth Commissioner
From the Guatemalan military to the South African apartheid police, code cruncher Patrick Ball singles out the perpetrators of political violence.