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Calculating US police killings using methodologies from war-crimes trials

100x100-boingboing-logoCory Doctorow of Boing Boing writes about HRDAG director of research Patrick Ball’s article “Violence in Blue,” published March 4 in Granta. From the post: “In a must-read article in Granta, Ball explains the fundamentals of statistical estimation, and then applies these techniques to US police killings, merging data-sets from the police and the press to arrive at an estimate of the knowable US police homicides (about 1,250/year) and the true total (about 1,500/year). That means that of all the killings by strangers in the USA, one third are committed by the police.”


Data ‘hashing’ improves estimate of the number of victims in databases

But while HRDAG’s estimate relied on the painstaking efforts of human workers to carefully weed out potential duplicate records, hashing with statistical estimation proved to be faster, easier and less expensive. The researchers said hashing also had the important advantage of a sharp confidence interval: The range of error is plus or minus 1,772, or less than 1 percent of the total number of victims.

“The big win from this method is that we can quickly calculate the probable number of unique elements in a dataset with many duplicates,” said Patrick Ball, HRDAG’s director of research. “We can do a lot with this estimate.”


UN Raises Estimate of Dead in Syrian Conflict to 191,000

Nick Cumming-Bruce of the New York Times writes about the UN Office of the High Commissioner of Human Right’s release of HRDAG’s third report on reported killings in the Syrian conflict.
From the article:
In its third report on Syria commissioned by the United Nations, the Human Rights Data Analysis Group identified 191,369 deaths from the start of the conflict in March 2011 to April 2014, more than double the 92,901 deaths cited in their last report, which covered the first two years of the conflict.
“Tragically, it is probably an underestimate of the real total number of people killed during the first three years of this murderous conflict,” Ms. Pillay said in a statement that accompanied the report, which observed that many killings in Syria were undocumented.


Quantifying Injustice

“In 2016, two researchers, the statistician Kristian Lum and the political scientist William Isaac, set out to measure the bias in predictive policing algorithms. They chose as their example a program called PredPol.  … Lum and Isaac faced a conundrum: if official data on crimes is biased, how can you test a crime prediction model? To solve this technique, they turned to a technique used in statistics and machine learning called the synthetic population.”


Want to know a police officer’s job history? There’s a new tool

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.


Ciencia de datos para trazar un mapa de la crueldad a la mexicana

From the article: Esta entidad, que existe desde 1991, es liderada por su fundador, Patrick Ball, un científico que acumula una experiencia de más de 25 años realizando análisis cuantitativos en los lugares y en las situaciones más convulsos del planeta. Sobre su colaboración con el proyecto del predictor de fosas clandestinas en México, único en el mundo, Ball afirmó en entrevista:

“Cuando hablamos de crímenes de lesa humanidad estamos hablando de instituciones, de organizaciones grandes, cometiendo miles o centenares de miles  de violaciones a víctimas distribuidas sobre una geografía enorme. Para entender los patrones en esas violaciones, la estadística puede brindar una mirada sobre quiénes son los responsables materiales e intelectuales, quiénes son las víctimas y dónde o cuándo pasaron esas violaciones. Pero la estadística no es contabilidad, pues no estamos hablando solamente de las violaciones que podemos ver, sino que también debemos calcular las violaciones no observadas, las escondidas, invisibles, para incluir en nuestro análisis la totalidad de las violaciones”.


Data Mining for Good: CJA Drink + Think

At the Center for Justice and Accountability's happy hour, "Drink and Think," Patrick Ball spoke about "Data Mining for Good." The talk included a discussion of how HRDAG brings human rights abusers to justice through data analysis, and HRDAG's work conducting quantitative analysis for truth commissions, NGOs, the UN and other partners. The event was held at Eventbrite. More photos are below. The Center for Justice and Accountability Young Professionals' Committee for Human Rights September 16, 2014 San Francisco, California Link to CJA event page Back to Talks   All photos © 2014 Carter Brooks.

HRDAG Offers New R Package – dga

Much of the work we do at HRDAG involves estimating the number of undocumented deaths using a statistical technique called multiple systems estimation (MSE, described in more detail here). One of our goals is to make this class of methods more broadly available to human rights researchers. In particular, we are finding that Bayesian approaches are extremely valuable for MSE. Accordingly, we are pleased to offer a new R package called dga (“decomposable graphs approach”) that performs Bayesian model averaging for MSE. The main function in this package implements a model created by David Madigan and Jeremy York. This model was designed to ...

HRDAG and Amnesty International: Prison Mortality in Syria

Today Amnesty International released “‘It breaks the human’: Torture, disease and death in Syria’s prisons ,” a report detailing the conditions and mortality in Syrian prisons from 2011 to 2015, including data analysis conducted by HRDAG. The report provides harrowing accounts of ill treatment of detainees in Syrian prisons since the conflict erupted in March 2011, and publishes HRDAG’s estimate of the number of killings that occurred inside the prisons. To accompany the report, HRDAG has released a technical memo that explains the methodology, sources, and implications of the findings. The HRDAG team used data from four ...

Clustering and Solving the Right Problem

In our database deduplication work, we’re trying to figure out which records refer to the same person, and which other records refer to different people. We write software that looks at tens of millions of pairs of records. We calculate a model that assigns each pair of records a probability that the pair of records refers to the same person. This step is called pairwise classification. However, there may be more than just one pair of records that refer to the same person. Sometimes three, four, or more reports of the same death are recorded. So once we have all the pairs classified, we need to decide which groups of records refer to the ...

Locating Hidden Graves in Mexico

For more than 10 years, and with regularity, Mexican authorities have been discovering mass graves, known as fosas clandestinas, in which hundreds of bodies and piles of bones have been found. The casualties are attributed broadly to the country’s “drug war,” although the motivations and perpetrators behind the mass murders are often unknown. Recently, HRDAG collaborated with two partners in Mexico—Data Cívica and Programa de Derechos Humanos of the Universidad Iberoamericana—to model the probability of identifying a hidden grave in each county (municipio). The model uses an set of independent variables and data about graves from 2013 ...

Momentous Verdict against Hissène Habré

Today we’re very pleased to hear of the verdict finding Hissène Habré guilty of crimes against humanity. Habré, president of Chad from 1982 to 1990, has been sentenced to life in prison in Dakar, Senegal, where he was tried. He is the first former head of state to be tried and found guilty of crimes against humanity in one country (Chad) by the courts of another country (Senegal).  Here’s more on the verdict from The Guardian. The verdict resonates especially with HRDAG because of our role in the trial. In September 2015, director of research Patrick Ball testified as an expert witness about the very high rates of prison mortality in ...

Reflections: Some Stories Shape You

The first time I met anyone at HRDAG, I was a journalist. It was 2006. I was working on a story about a graduate student at Carnegie Mellon who’d collaborated with the organization on a survey in Sierra Leone, and I contacted Patrick Ball to discuss the work. At the time, I found him challenging. But I thought his work—trying to estimate how many people were killed, or, in that study, otherwise injured, during wars—was fascinating. Over the next few years, I got to know other researchers working on similar questions. In 2008, as the war in Iraq ramped up, I spoke with epidemiologists from Johns Hopkins University, the World Health Organiz...

Where Stats and Rights Thrive Together

Everyone I had the pleasure of interacting with enriched my summer in some way.

Reflections: Growing and Learning in Guatemala

As a woman, mother and sociologist who is curious about the patterns of our political past in Guatemala, I feel privileged to know and work with the HRDAG team. Collaborating and learning from people like Patrick, Megan, Suzanne, Beatriz and Tamy has been an invaluable gift. I have discovered many things, both human and academic. For example, I’ve learned new ways of seeing what seemed everyday and simple, to discover that not only do the social sciences and statistics work hand in hand, but that they are critical for understanding Guatemala’s reality. Twenty years ago, on 29 December, 1996, Guatemala made history by signing the Guatemala Peace ...

Mexico

HRDAG and our partners Data Cívica and the Iberoamericana University created a machine-learning model to predict which counties (municipios) in Mexico have the highest probability of unreported hidden graves. The predictions help advocates to bring public attention and government resources to search for the disappeared in the places where they are most likely to be found. Context For more than ten years, Mexican authorities have been discovering hidden graves (fosas clandestinas). The casualties are attributed broadly—and sometimes inaccurately—to the country’s “drug war,” but the motivations and perpetrators behind the mass murders ...

Nonprofits Are Taking a Wide-Eyed Look at What Data Could Do

In this story about how data are transforming the nonprofit world, Patrick Ball is quoted. Here's an excerpt: "Data can have a profound impact on certain problems, but nonprofits are kidding themselves if they think the data techniques used by corporations can be applied wholesale to social problems," says Patrick Ball, head of the nonprofit Human Rights Data Analysis Group. Companies, he says, maintain complete data sets. A business knows every product it made last year, when it sold, and to whom. Charities, he says, are a different story. "If you're looking at poverty or trafficking or homicide, we don't have all the data, and we're not going to," ...

New death toll estimated in Syrian civil war

Kevin Uhrmacher of the Washington Post prepared a graph that illustrates reported deaths over time, by number of organizations reporting the deaths. Washington Post Kevin Uhrmacher August 22, 2014 Link to story on Washington Post Related blogpost (Updated Casualty Count for Syria) Back to Press Room  

Why It Took So Long To Update the U.N.-Sponsored Syria Death Count

In this story, Carl Bialik of FiveThirtyEight interviews HRDAG executive director Patrick Ball about the process of de-duplication, integration of databases, and machine-learning in the recent enumeration of reported casualties in Syria. New reports of old deaths come in all the time, Ball said, making it tough to maintain a database. The duplicate-removal process means “it’s a lot like redoing the whole project each time,” he said. FiveThirtyEight Carl Bialik August 23, 2014 Link to story on FiveThirtyEight Related blogpost (Updated Casualty Count for Syria) Back to Press Room  

100 Women in AI Ethics

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


Our work has been used by truth commissions, international criminal tribunals, and non-governmental human rights organizations. We have worked with partners on projects on five continents.

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