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Predictive policing tools send cops to poor/black neighborhoods
In this post, Cory Doctorow writes about the Significance article co-authored by Kristian Lum and William Isaac.
Trips to and from Guatemala
Searching for Trends: Analyzing Patterns in Conflict Violence Data
Megan Price and Anita Gohdes (2014). Searching for Trends: Analyzing Patterns in Conflict Violence Data. Political Violence @ a Glance. © 2014 PV@G.
El problema del asesinato a líderes es más grave de lo que se piensa
Una investigación de Dejusticia y Human Rights Data Analysis Group asegura que en Colombia hay un subregistro de los asesinatos de líderes sociales que se han perpetrado en Colombia. Al analizar las diferentes cifras de homicidios que han publicado diversas organizaciones desde 2016, se llegó a la conclusión que la problemática es mayor de lo que se cree.
Third CLS Story
Recognising Uncertainty in Statistics
In Responsible Data Reflection Story #7—from the Responsible Data Forum—work by HRDAG affiliates Anita Gohdes and Brian Root is cited extensively to make the point about how quantitative data are the result of numerous subjective human decisions. An excerpt: “The Human Rights Data Analysis Group are pioneering the way in collecting and analysing figures of killings in conflict in a responsible way, using multiple systems estimation.”
Here’s how an AI tool may flag parents with disabilities
HRDAG contributed to work by the ACLU showing that a predictive tool used to guide responses to alleged child neglect may forever flag parents with disabilities. “These predictors have the effect of casting permanent suspicion and offer no means of recourse for families marked by these indicators,” according to the analysis from researchers at the ACLU and the nonprofit Human Rights Data Analysis Group. “They are forever seen as riskier to their children.”
Preliminary Statistical Analysis of Documentation of Killings in the Syrian Arab Republic.
Megan Price, Jeff Klingner, and Patrick Ball (2013). The Benetech Human Rights Program, commissioned by the United Nations Office of the High Commissioner for Human Rights (OHCHR). January 2, 2013. © 2013 HRDAG. Creative Commons BY-NC-SA.
On ensuring a higher level of data quality when documenting human rights violations to support research into the origins and cause of human rights violations
Romesh Silva. “On ensuring a higher level of data quality when documenting human rights violations to support research into the origins and cause of human rights violations.” ASA Proceedings of the Joint Statistical Meetings, the International Biometric Society (ENAR and WNAR), the Institute of Mathematical Statistics, and the Statistical Society of Canada. August, 2002.
Collecting Sensitive Human Rights Data in the Field: A Case Study from Amritsar, India.
Romesh Silva and Jasmine Marwaha. “Collecting Sensitive Human Rights Data in the Field: A Case Study from Amritsar, India.” In JSM Proceedings, Social Statistics Section. Alexandria, VA. © 2011 American Statistical Association. All rights reserved.
Counting the Unknown Victims of Political Violence: The Work of the Human Rights Data Analysis Group
Ann Harrison (2012). Counting the Unknown Victims of Political Violence: The Work of the Human Rights Data Analysis Group, in Human Rights and Information Communications Technologies: Trends and Consequences of Use. © 2012 IGI Global. All rights reserved.
Making the Case. Investigating Large Scale Human Rights Violations Using Information Systems and Data Analysis
Patrick Ball, Herbert F. Spirer, and Louise Spirer, eds. Making the Case. Investigating Large Scale Human Rights Violations Using Information Systems and Data Analysis . © 2000 American Association for the Advancement of Science. All rights reserved. Reprinted with permission. [full text] [intro] [chapters 1 2 3 4 5 67 8 9 10 11 12]
Different Convenience Samples, Different Stories: The Case of Sierra Leone.
Anita Gohdes. “Different Convenience Samples, Different Stories: The Case of Sierra Leone.” Benetech. 2010. © 2010 Benetech. Creative Commons BY-NC-SA.
Data-driven crime prediction fails to erase human bias
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.”
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.
Mapping Mexico’s hidden graves
When Patrick Ball was introduced to Ibero’s database, the director of research at the Human Rights Data Analysis Group in San Francisco, California, saw an opportunity to turn the data into a predictive model. Ball, who has used similar models to document human rights violations from Syria to Guatemala, soon invited Data Cívica, a Mexico City–based nonprofit that creates tools for analyzing data, to join the project.