Machine Learning Is Being Used to Uncover the Mass Graves of Mexico's Missing
A view of mass grave site on the outskirts of Veracruz city, Veracruz state (AFP/Ilse Huesca)
In March of this year, a massive grave was uncovered buried beneath the soil of the coastal Mexican state of Veracruz. The grave made national headlines because it contained more than 240 skulls and corpses, the remains of disappeared people.
But for many, the grave’s existence came as no surprise. In Mexico, a country where almost 30,000 people have gone missing due to drug-related violence since 2006, the grave was a reminder of a difficult reality: the search for missing people often begins by looking underground.
Mexico is home to over 122 million people and spans more than 750,000 square miles of land. There is no road map that makes clear where to start the search for mass graves, or the bodies of the disappeared (desaparecidos) that they hold.
Or at least there hasn’t been - until now. A team of multi-country researchers, data scientists, and statisticians is using machine learning to predict which counties in Mexico are most likely to have hidden graves. If their model works as well as they hope, it will be a powerful application of an emerging technology that provide answers to one of the most difficult aspects of the desaparecidos problem: knowing where to look.
The team is composed of three separate groups: the Programa de Derechos Humanos at the Ibero-American University in Mexico City; data-focused non-profit Data Cívica, also based in Mexico City; and the Human Rights Data Analysis Group (HRDAG), a San Francisco-based organization that applies scientific analysis to human rights violations.
Each organization contributes a unique piece of analysis or data which together form a fuller picture of where to search. The group at the Ibero-American University has been scraping local and national Mexican newspaper and radio data for mentions of hidden graves for years as part of a larger project. They’ve created a comprehensive database of the details behind every report of a hidden grave. It’s the country’s first database of the sort, and it’s a crucial bank of knowledge that details in which municipalities hidden graves have been discovered in the past.
Data Cívica contributes data on social demographics about every municipio, or county, in the country. By combining Mexico’s public open data system with geographic data, they’ve been able to create a detailed profile of sociodemographic data for every one of Mexico’s 2457 counties.
These two pieces are crucial to the machine learning model that HRDAG uses to predict which counties are likely to have hidden graves in them.
Read the rest at Quartz
Related: Modeling the Location of Hidden Graves in Mexico (HRDAG)
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