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UN Human Rights Office estimates more than 306,000 civilians were killed over 10 years in Syria conflict
What we’ll need to find the true COVID-19 death toll
From the article: “Intentionally inconsistent tracking can also influence the final tally, notes Megan Price, a statistician at the Human Rights Data Analysis Group. During the Iraq War, for example, officials worked to conceal mortality or to cherry pick existing data to steer the political narrative. While wars are handled differently from pandemics, Price thinks the COVID-19 data could still be at risk of this kind of manipulation.”
Machine learning is being used to uncover the mass graves of Mexico’s missing
“Patrick Ball, HRDAG’s Director of Research and the statistician behind the code, explained that the Random Forest classifier was able to predict with 100% accuracy which counties that would go on to have mass graves found in them in 2014 by using the model against data from 2013. The model also predicted the counties that did not have mass hidden graves found in them, but that show a high likelihood of the possibility. This prediction aspect of the model is the part that holds the most potential for future research.”
Amnesty International Reports Organized Murder Of Detainees In Syrian Prison
Reports of torture and disappearances in Syria are not new. But the Amnesty International report says the magnitude and severity of abuse has “increased drastically” since 2011. Citing the Human Rights Data Analysis Group, the report says “at least 17,723 people were killed in government custody between March 2011 and December 2015, an average of 300 deaths each month.”
PredPol amplifies racially biased policing
HRDAG associate William Isaac is quoted in this article about how predictive policing algorithms such as PredPol exacerbate the problem of racial bias in policing.
Unbiased algorithms can still be problematic
“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.
Measures of Fairness for New York City’s Supervised Release Risk Assessment Tool
Kristian Lum and Tarak Shah (2019). Measures of Fairness for New York City’s Supervised Release Risk Assessment Tool. Human Rights Data Analysis Group. 1 October 2019. © HRDAG 2019.
Update of Iraq and Syria Data in New Paper
HRDAG Retreat 2015
How We Choose Projects
HRDAG To Join the Partnership on AI
Syrian civil war death toll exceeds 190,000, U.N. reports
Ayan Sheikh of PBS News Hour reports on 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:
The latest death toll figure covers the period from March 2011 to April of this year, came from the Human Rights Data Analysis Group and is the third study of its kind on Syria. The analysis group identified 191,269 deaths. Data was collected from five different sources to exclude inaccuracies and repetitions.
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.”
Sierra Leone
Release of Yellow Book Calls on Salvadoran Military to Open Archives
Welcoming Our 2021-2022 Human Rights and Data Science Intern
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The impact of overbooking on a pre-trial risk assessment tool
Kristian Lum, Chesa Boudin and Megan Price (2020). The impact of overbooking on a pre-trial risk assessment tool. FAT* ’20: Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency. January 2020. Pages 482–491. https://doi.org/10.1145/3351095.3372846 ©ACM, Inc., 2020.