For over 25 years, Stanford’s Kimberly Babiarz has felt fiercely devoted to addressing the complex injustice of human trafficking, a crime she is quick to point out, “is everywhere.”
Modern slavery, which includes sex and labor trafficking, forced labor, domestic servitude, debt bondage, and forced marriage, is “a big, systemic problem in need of big, systemic solutions,” she notes.
Those kinds of solutions typically require a diverse array of skillsets and experience – not to mention a great deal of dedication to the work, both of which Babiarz found when she and longtime collaborator Grant Miller, Henry J. Kaiser, Jr. Professor in the Department of Health Policy at Stanford School of Medicine, linked up with Jessie Brunner of Stanford’s Center for Human Rights and International Justice, Clinical Associate Professor of Pediatrics Vicki Ward, and Luis Assis, labor prosecutor and Chief Data Scientist at Brazil’s Federal Labor Prosecution Office.
The group coalesced around a shared sense of frustration at the lack of an evidence base undergirding decades of anti-trafficking interventions and the Stanford Human Trafficking Data Lab was born in 2019 with a mission to bring data and evidence to the fight against human trafficking.
“Few things give me more satisfaction than gathering folks with disparate backgrounds and skillsets towards achieving a common goal to advance human rights,” said Brunner. “Forming the Lab was a unique opportunity to leverage advances in data science and technological innovation to bear on one of the most grievous abuses of our time.”
Fairly quickly, the team identified a gap they could fill in and around the remote Amazon region in northeastern Brazil.
“The steady pace of deforestation and land conversion in the Amazon relies on the exploitation of people, including some children, who work strenuous 16-hour days, often without pay, burning trees at extremely high temperatures and converting them into charcoal,” explains Miller, the Lab’s Principal Investigator. “This all takes place at illegal work sites, where laborers live without adequate shelter or clean water, that are intentionally hidden from view in remote areas.”
Because these sites consist of an almost geometric line-up of dome-shaped kilns devoted to burning trees and an output of thick smoke, the researchers realized their footprints are uniquely visible from space.
Using geospatial data and remote detection algorithms, the lab was able to pinpoint a clear way in which data science could be leveraged to help Brazilian prosecutors locate and investigate the stealth work sites where laborers are often exploited in conditions analogous to slavery.