In this post, Cory Doctorow writes about the Significance article co-authored by Kristian Lum and William Isaac.

“I was always a math nerd. My mother has a polaroid of me in the fourth grade with my science fair project … . It was the history of mathematics. In college, I was a math major for a year and then switched to statistics.

I always wanted to work in social justice. I was raised by hippies, went to protests when I was young. I always felt I had an obligation to make the world a little bit better.”

The International Truth and Justice Project and HRDAG have published a report on 500 Tamils who disappeared while in Army custody in Sri Lanka in 2009.

The report is titled “How many people disappeared on 17-19 May 2009 in Sri Lanka?” and Patrick Ball, director of research at HRDAG, is the lead author.

In the last three days of the Sri Lankan civil war, as thousands of people surrendered to government authorities, hundreds of people were put on buses driven by Army officers. Many were never seen again.

In a report released today (see here), the International Truth and Justice Project for Sri Lanka and the Human Rights Data Analysis Group showed that over 500 people were disappeared on only three days — 17, 18, and 19 May.

The Sri Lankan army must explain to the families of the disappeared and missing what happened to an estimated 500 Tamils who disappeared in their custody at the war end on/around 18 May 2009, said two international NGOs who have been collating and analysing lists of names.

Sri Lanka has one of the largest numbers in the world of enforced disappearances but these 500 represent the largest number of disappearances all in one place and time in the country. For a detailed account of the process of estimating the 500 please see: “How many people disappeared on 17-19 May 2009 in Sri Lanka?” .

“Usually, the thing you’re trying to predict in a lot of these cases is something like rearrest,” Lum said. “So even if we are perfectly able to predict that, we’re still left with the problem that the human or systemic or institutional biases are generating biased arrests. And so, you still have to contextualize even your 100 percent accuracy with is the data really measuring what you think it’s measuring? Is the data itself generated by a fair process?”

HRDAG Director of Research Patrick Ball, in agreement with Lum, argued that it’s perhaps more practical to move it away from bias at the individual level and instead call it bias at the institutional or structural level. If a police department, for example, is convinced it needs to police one neighborhood more than another, it’s not as relevant if that officer is a racist individual, he said.

“Kristian Lum… organized a workshop together with Elizabeth Bender, a staff attorney for the NY Legal Aid Society and former public defender, and Terrence Wilkerson, an innocent man who had been arrested and could not afford bail. Together, they shared first hand experience about the obstacles and inefficiencies that occur in the legal system, providing valuable context to the debate around COMPAS.”

Kristian Lum discusses the challenges of getting accurate data from conflict zones, as well as her concerns about predictive policing if law enforcement gets it wrong.

“Every kind of classification system – human or machine – has several kinds of errors it might make,” [Patrick Ball] says. “To frame that in a machine learning context, what kind of error do we want the machine to make?” HRDAG’s work on predictive policing shows that “predictive policing” finds patterns in police records, not patterns in occurrence of crime.

When Patrick Ball was introduced to Ibero’s database, the director of research at the Human Rights Data Analysis Group in San Francisco, California, saw an opportunity to turn the data into a predictive model. Ball, who has used similar models to document human rights violations from Syria to Guatemala, soon invited Data Cívica, a Mexico City–based nonprofit that creates tools for analyzing data, to join the project.

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.

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 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.”