In this NPR story, HRDAG’s Patrick Ball comments on first-of-its-kind projections.

“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. … “

Tarak Shah is quoted with regard to the National Police Index: “Police often avoid accountability by moving to another agency rather than face discipline. This tool, allowing anyone to look up and track the histories of such officers, provides an invaluable service for the human rights community in our fight against impunity.”

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.

HRDAG director of research Patrick Ball is quoted in this Nature article about how body counts are a crude measure of the war’s impact and more reliable estimates will take time to compile.

The Human Rights Data Analysis Group employs AI to analyze data from conflict zones, identifying patterns of human rights abuses that might be overlooked. This assists international organizations in holding perpetrators accountable.

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.”

In her work on statistical issues in criminal justice, Lum has studied uses of predictive policing—machine learning models to predict who will commit future crime or where it will occur. In her work, she has demonstrated that if the training data encodes historical patterns of racially disparate enforcement, predictions from software trained with this data will reinforce and—in some cases—amplify this bias. She also currently works on statistical issues related to criminal “risk assessment” models used to inform judicial decision-making. As part of this thread, she has developed statistical methods for removing sensitive information from training data, guaranteeing “fair” predictions with respect to sensitive variables such as race and gender. Lum is active in the fairness, accountability, and transparency (FAT) community and serves on the steering committee of FAT, a conference that brings together researchers and practitioners interested in fairness, accountability, and transparency in socio-technical systems.

We live in very challenging times. The pervasiveness of bias in AI algorithms and autonomous “killer” robots looming on the horizon, all necessitate an open discussion and immediate action to address the perils of unchecked AI. The decisions we make today will determine the fate of future generations. Please follow these amazing women and support their work so we can make faster meaningful progress towards a world with safe, beneficial AI that will help and not hurt the future of humanity.

53. Kristian Lum @kldivergence

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.

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.

“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.”

“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.”

Contrario a lo que se puede pensar, los datos oficiales sobre líderes sociales asesinados no necesariamente corresponden a la realidad y podría haber mucha mayor victimización en las regiones golpeadas por este flagelo, según el más reciente informe del Centro de Estudios de Justicia, Derecho y Sociedad (Dejusticia) en colaboración con el Human Rights Data Analysis Group.

NPR Illinois has covered the new National Police Index, created by HRDAG’s Tarak Shah, Ayyub Ibrahim of Innocence Project, and Sam Stecklow of Invisible Institute.

Video available. La organización Dejusticia, en alianza con una institución estadounidense, asegura que los crímenes van en aumento y existe un subregistro. “Aumentó la violencia letal contra líderes sociales en 2016 y 2017 en al menos 10%”, asegura Valentina Rozo, investigadora de Dejusticia.

Una investigación de Dejusticia y Human Rights Data Analysis Group concluyó que hay un subconteo en los asesinatos de líderes sociales en Colombia. Es decir, que el aumento de estos crímenes en 2016 y 2017 podría ser incluso mayor al reportado por las organizaciones y por las cifras oficiales.

“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.

A new study has estimated that over 500 Tamils were forcibly disappeared in just three days, after surrendering to the Sri Lankan army in May 2009.

The study, carried out by the Human Rights Data Analysis Group and the International Truth and Justice Project, based on compiled lists which identify those who were known to have surrendered, estimated that 503 people had been forcibly disappeared between the 17^th– 19^th of May 2009.