The King Center on Global Development recently awarded a generous grant to the Stanford's Human Trafficking Data Lab, an early-stage research initiative jointly run by faculty and staff from the Center for Human Rights and International Justice, the Center for Health Policy, and Stanford School of Medicine. The Lab is developing a novel human trafficking data repository and working on innovative, multidisciplinary research projects using the repository to better understand essential questions about human trafficking markets and how policies and other interventions impact these phenomena. Through collaboration with additional Stanford faculty, the Human Trafficking Data Lab boasts expertise in a broad range of disciplines, including law, economics, medicine, statistics, computer science, and corporate governance.
“This type of core support from the King Center is absolutely key to growing our Lab and achieving our vision of localized, survivor-informed, evidence-based anti-trafficking policy and intervention,” said Jessie Brunner, Director of Human Trafficking Research at the Center for Human Rights and International Justice, who also serves as the director of the Lab’s strategic partnerships within the global anti-trafficking community.
The King Center’s grant will support a three-year, multi-faceted research agenda that will:
• enable the Lab to demonstrate the potential of existing administrative databases as a resource for policy-relevant analyses of trafficking;
• develop an innovative research program showing that rigorous quantitative social science research on human trafficking is possible; and
• translate this research into impactful anti-trafficking policy through policymaker engagement.
One of the Lab’s current projects examines if, and how, conditional cash transfer poverty reduction programs mitigate the risk of trafficking and child labor. This work appears to be the first quantitative, individual-level study of how poverty reduction social programs impact forced labor.
Additionally, using time-series stock price data, VAT regulatory filings, and corporate ownership network data, Lab members are conducting the first formal study of the fiscal impact of deterrence tools such as “dirty lists” on the valuation of publicly and privately held companies. They will also identify corporate tactics for evading the consequences of such accountability and deterrence mechanisms.
With initial support from Data Science for Social Good, ongoing support from the Stanford Institute for Human-Centered Artificial Intelligence, and direct collaboration with the MapBiomas Project in Brazil, the Lab is developing an algorithm capable of identifying illegal labor camps in the Brazilian Amazon. Lastly, the team is developing a decision support tool to assist anti-trafficking frontline activities broadly. This AI-powered "intuition engine" will help evaluate the accuracy and urgency of new tips/leads and help improve resource allocation and task forces planning.
Several Lab affiliates will be actively engaged in these projects, including PI Grant Miller, also a faculty affiliate of the Center for Human Rights and International Justice; Vicki Ward; Mike Baiocchi, Kim Babiarz, and Luis Fabiano de Assis, a Brazilian federal labor prosecutor and Visiting Scholar with the Center.
“Some of the most basic questions about human trafficking have not yet been answered, and the international community struggles to implement effective anti-trafficking policies,” said Luis Fabiano de Assis, a Brazilian Federal Prosecutor, Visiting Scholar at the Center for Human Rights and International Justice and Lab member. “To help change this scenario, our lab brings rich academic expertise and valuable real-world experience in health, development economics, law, computer science, human rights, and statistics into cooperation with key public and private stakeholders, as well as the international community.”
The new King Center grant provides a stipend for a post-doctoral scholar, which the Lab is in the process of hiring (more information here). The King Center previously provided a seed grant to launch the Lab—funding that allowed the Lab to design a data management and security protocol, populate the data environment with massive datasets, and engage a number of undergraduates and grad students in the research.