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.”

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.

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

El modelo “puede distinguir entre los municipios en que vamos a encontrar fosas clandestinas, y en los que es improbable que vayamos a encontrar estas fosas”, explicó Patrick Ball, estadístico estadounidense que colabora con el Programa de Derechos Humanos de la Universidad Iberoamericana de la Ciudad de México.

Por ello, Human Rights Data Analysis Group (HRDAG), el Programa de Derechos Humanos de la Universidad Iberoamericana (UIA) y Data Cívica, realizan un análisis estadístico construido a partir de una variable en la que se identifican fosas clandestinas a partir de búsquedas automatizadas en medios locales y nacionales, y usando datos geográficos y sociodemográficos.

As executive director of the Human Rights Data Analysis Group, Megan Price uses statistics to shine the light on human rights abuses.

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.

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.

“In a recent article, social scientist Patrick Ball revisited his and Kristian Lum’s 2015 study, which made a compelling argument for the underreporting of lethal police shootings by the Bureau of Justice Statistics (BJS). Lum and Ball’s study may be old, but it bears revisiting amid debates over the American police system — debates that have featured plenty of data on the excessive use of police force. It is a useful reminder that many of the facts and figures we rely on require further verification.”

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.”

Kristian Lum, the lead statistician at the Human Rights Data Analysis Group, and an expert on algorithmic bias, said she hoped Stanford’s stumble made the institution think more deeply about representation.

“This type of oversight makes me worried that their stated commitment to the other important values and goals – like taking seriously creating AI to serve the ‘collective needs of humanity’ – is also empty PR spin and this will be nothing more than a vanity project for those attached to it,” she wrote in an email.

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.

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.

“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.”