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Update of Iraq and Syria Data in New Paper

This week The Statistical Journal of the IAOS published a new(ish) paper by Megan Price and Patrick Ball. The open-access paper, Selection bias and the statistical patterns of mortality in conflict, is a revisiting and updating of both the Iraq and Syria examples used in an earlier paper, Big Data, Selection Bias, and the Statistical Patterns of Mortality in Conflict, which was published last year inThe SAIS Review of International Affairs (JHU Press, 2014). HRDAG believes that the concerns highlighted by these examples are important for a wide variety of audiences, including both the foreign policy readers reached by The SAIS Review and the ...

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Kristian Lum, lead statistician at HRDAG | Predictive Policing: Bias In, Bias Out | 56 mins

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You may contact us via info @ hrdag.org or use this form. Would you like to receive our newsletter? Great! Please sign up here. Find us on Mastodon Follow HRDAG on Mastodon. Employment with HRDAG Please keep in touch by signing up for our newsletters and following us on Twitter @hrdag or Mastodon. If you do not see a job listed here, please do not send your CV or résumé, as we do not file or save them, and we will only have to send you a sad “no thank you” letter. Volunteering with HRDAG Are you interested in volunteering your time to the Human Rights Data Analysis Group? We’re very flattered—but at this time we’re ...

Using Statistics to Assess Lethal Violence in Civil and Inter-State War

Patrick Ball and Megan Price (2019). Using Statistics to Assess Lethal Violence in Civil and Inter-State War. Annual Review of Statistics and Its Application, Volume 6. 7 March 2019. © 2019 Annual Reviews. All rights reserved. https://doi.org/10.1146/annurev-statistics-030718-105222.

Patrick Ball and Megan Price (2019). Using Statistics to Assess Lethal Violence in Civil and Inter-State War. Annual Review of Statistics and Its Application. 7 March 2019. © 2019 Annual Reviews. All rights reserved. https://doi.org/10.1146/annurev-statistics-030718-105222.

Setting the Record Straight on Predictive Policing and Race

William Isaac and Kristian Lum (2018). Setting the Record Straight on Predictive Policing and Race. In Justice Today. 3 January 2018. © 2018 In Justice Today / Medium.

William Isaac and Kristian Lum (2018). Setting the Record Straight on Predictive Policing and Race. In Justice Today. 3 January 2018. © 2018 In Justice Today / Medium.

Cuentas y mediciones de la criminalidad y de la violencia

Exploración y análisis de los datas para comprender la realidad. Patrick Ball y Michael Reed Hurtado. 2015. Forensis 16, no. 1 (July): 529-545. © 2015 Instituto Nacional de Medicina Legal y Ciencias Forenses (República de Colombia).

The Death Toll in Syria

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HRDAG contributes to textbook Counting Civilian Casualties

Next week, on June 11, Oxford University Press officially puts Counting Civilian Casualties: An Introduction to Recording and Estimating Nonmilitary Deaths in Conflict on the market. This textbook, edited by Taylor B. Seybolt, Jay D. Aronson, and Baruch Fischhoff, responds to the increasing concern for civilians in conflict and aims to promote scientific dialogue by highlighting the strengths and weaknesses of the most commonly used casualty recording and estimation techniques. HRDAG is very well represented here, as our colleagues have co-authored four chapters, and Nicholas Jewell, who sits on our Science Committee, has co-authored a fifth. ...

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Mailing List Subscription We use Mailchimp to help us keep track of community members who want to stay informed about what HRDAG is doing and thinking. If you self-subscribe to our list, we will never share your contact information. We will never subscribe anyone who does not explicitly agree to a subscription.  Over the course of a year, we mail quarterly letters and fundraising letters, as well as one or two updates as events demand. If, during the course of a fundraising campaign, you make a donation, we will do our best to remove you from the remainder of fundraising mailings that year. We may use your contact information to invite you to ...

Estimating Deaths in Timor-Leste

Kosovo Data – Killings, Migrations and More

Much of the debate about the March–June 1999 war between NATO and Yugoslavia turned on how many people left their homes in particular places and at certain times. Solid information about the flow of refugees out of Kosovo has helped investigators to link patterns in the flow to patterns of NATO bombing, Yugoslav strategic plans for "cleansing" Kosovo, and Yugoslav and irregular troop deployments. At its heart, the debate was about whether refugees left their homes fleeing NATO attacks and fighting between the KLA and Yugoslav forces, or whether they left their homes after being threatened, assaulted, and robbed by Yugoslav police, army, and irregu...

Rise of the racist robots – how AI is learning all our worst impulses

“If you’re not careful, you risk automating the exact same biases these programs are supposed to eliminate,” says Kristian Lum, the lead statistician at the San Francisco-based, non-profit Human Rights Data Analysis Group (HRDAG). Last year, Lum and a co-author showed that PredPol, a program for police departments that predicts hotspots where future crime might occur, could potentially get stuck in a feedback loop of over-policing majority black and brown neighbourhoods. The program was “learning” from previous crime reports. For Samuel Sinyangwe, a justice activist and policy researcher, this kind of approach is “especially nefarious” because police can say: “We’re not being biased, we’re just doing what the math tells us.” And the public perception might be that the algorithms are impartial.

Hunting for Mexico’s mass graves with machine learning

“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.”

A better statistical estimation of known Syrian war victims

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.

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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.

Analyze This!

Doing a Number on Violators

Carnegie Mellon Partners With Human Rights Data Analysis Group To Improve Syrian Casualty Reporting

Scanning Documents to Uncover Police Violence

Administrative paperwork generated by police departments can hold evidence of police violence, but can present unique challenges for data processing.

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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