HRDAG is mentioned in the “child welfare (sometimes called “family policing”)” section: At least 72,000 low-income children are exposed to AI-related decision-making through government child welfare agencies’ use of AI to determine if they are likely to be neglected. As a result, these children experience heightened risk of being separated from their parents and placed in foster care.

From the article: “As we seek to advance the responsible use of data for racial injustice, we encourage individuals and organizations to support and build upon efforts already underway.” HRDAG is listed in the Data Driven Activism and Advocacy category.

From the article: “Price described the touchstone of her organization as being a tension between how truth is simultaneously discovered and obscured. HRDAG is at the intersection of this tension; they are consistently participating in science’s progressive uncovering of what is true, but they are accustomed to working in spaces where this truth is denied. Of the many responsibilities HRDAG holds in its work is that of “speaking truth to power,” said Price, “and if that’s what you’re doing, you have to know that your truth stands up to adversarial environments.”

From the article: “Based on Ball’s calculations, using our data, nearly 3,000 people could have been killed in the three areas we analyzed in the first 18 months of the drug war. That is more than three times the official police count.”

The World According to Artificial Intelligence – The Bias in the Machine (Part 2)

Artificial intelligence might be a technological revolution unlike any other, transforming our homes, our work, our lives; but for many – the poor, minority groups, the people deemed to be expendable – their picture remains the same.

Patrick Ball is interviewed: “The question should be, Who bears the cost when a system is wrong?”

Patrick Ball es un sabueso de la verdad. Ese deseo de descubrir lo que otros quieren ocultar lo ha llevado a desarrollar fórmulas matemáticas para detectar desaparecidos.

Su trabajo consiste en aplicar métodos de medición científica para comprobar violaciones masivas de derechos humanos.

Wilkerson was speaking at the inaugural Conference on Fairness, Accountability, and Transparency, a gathering of academics and policymakers working to make the algorithms that govern growing swaths of our lives more just. The woman who’d invited him there was Kristian Lum, the 34-year-old lead statistician at the Human Rights Data Analysis Group, a San Francisco-based non-profit that has spent more than two decades applying advanced statistical models to expose human rights violations around the world. For the past three years, Lum has deployed those methods to tackle an issue closer to home: the growing use of machine learning tools in America’s criminal justice system.

Biotechniques published an interview with Patrick Ball, inspired by his John Maddox Prize award.

“Led by the nonprofit Human Rights Data Analysis Group (HRDAG), the process began with creating a merged dataset of “fully identified victims” to avoid double counting. Only casualties whose complete details were listed — such as their full name, date of death and the governorate they had been killed in — were included on this initial list, explained Megan Price, executive director at HRDAG. If details were missing, the victim could not be confidently cross-checked across the eight organizations’ lists, and so was excluded. This provided HRDAG and the U.N. with a minimum count of individuals whose deaths were fully documented by at least one of the different organizations. … “

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.”

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.”

Work by HRDAG researchers Kristian Lum and William Isaac is cited in this article about the Policing Project: “While this bias knows no color or socioeconomic class, Lum and her HRDAG colleague William Isaac demonstrate that it can lead to policing that unfairly targets minorities and those living in poorer neighborhoods.”

Ball, a statistician, has spent the last two decades finding ways to make the silence speak. He helped pioneer the use of formal statistical modeling, and, later, machine learning—tools more often used for e-commerce or digital marketing—to measure human rights violations that weren’t recorded. In Guatemala, his analysis helped convict former dictator General Efraín Ríos Montt of genocide in 2013. It was the first time a former head of state was found guilty of the crime in his own country.

Patrick Ball, estadístico norteamericano, colabora con el Programa de Derechos Humanos de la Universidad Iberoamericana en una investigación sobre fosas clandestinas.