Dr. Eirliani Abdul Rahman

What if the fight against child trafficking could begin before a child disappears?

Dr. Eirliani Abdul Rahman is building TRAPP, Trafficking Risks: AI for Proactive Protection. An AI-enabled decision-support platform designed to help police and frontline organizations identify emerging trafficking risks and intervene earlier.

About The Fellow

EAR

Co-Founder & Co-Director, Global Responsible Tech Lab · University of Mannheim

Dr. Eirliani brings a rare combination of child protection experience, public health training, diplomatic judgment, and responsible technology leadership to the Fellowship.

Her child protection work began with Nobel Peace Prize laureate Kailash Satyarthi, for whom she led the #FullStop to #childsexualabuse campaign, reaching 16 million people in six weeks. She later spent nearly a decade working on child trafficking before turning toward the AI tools that could help institutions act earlier.

A former Singapore Foreign Service officer, Dr. Eirliani has worked across government, civil society, universities, and international policy forums. Drawing on her expertise in child protection and responsible technology, she has given evidence before the UK House of Commons, briefed the German Federal Foreign Office, and spoken at forums including the Munich Security Conference, Bled Strategic Forum, Cambridge, Oxford, Stanford, MIT, and Harvard.

She holds a doctorate in public health from Harvard, a master’s degree from the London School of Economics, and is co-founder and co-director of the Global Responsible Tech Lab at the University of Mannheim.

Why This Work Matters

One morning in New Delhi, Dr. Eirliani visited a rescue center for victims of child trafficking. In the courtyard sat an older man, surrounded by villagers who had come to meet their sons after a rescue operation.

He looked confused.

To him, the situation was not a crime pattern or a policy failure. It was debt. Survival. A decision made under pressure. He believed he had no choice but to sell his son into servitude.

That moment revealed the deeper challenge at the heart of anti-trafficking work: trafficking does not emerge randomly. It follows routes, pressures, vulnerabilities, economic patterns, and institutional blind spots. Yet the people trying to stop it often work with information that is scattered across police records, case files, district-level data, and local knowledge that never becomes usable intelligence.

Dr. Eirliani’s work begins there.

TRAPP asks whether law enforcement agencies can move from reactive rescue to proactive protection, not by replacing human judgment, but by giving police officers and state partners better tools to see where risk is building before harm occurs.

The Bergel Institute is supporting this work because it reflects exactly the kind of possibility the Institute was created to pursue: field-rooted innovation aimed at improving the human condition.

The Work

TRAPP, an AI-powered platform for proactive trafficking prevention, is designed to help anti-trafficking work move from fragmented response to coordinated prevention.

Being piloted in Odisha, India, the platform will integrate more than 20,000 historical case records from civil society partners with police operational data, trafficking route information, socioeconomic indicators, and district-level vulnerability patterns. From that foundation, TRAPP will generate predictive heatmaps, AI-assisted explanations, and network analyses that help identify where trafficking risk is emerging.

What makes the project distinctive is that it is being built in partnership with police officers conducting anti-trafficking operations, civil society organizations supporting children and families, state authorities responsible for implementation, and researchers working at the intersection of public health, child protection, and responsible AI.

The platform will include multilingual interfaces in Odia and Hindi so officers can access risk summaries and plan operations without advanced technical expertise. The goal is not to replace human judgment, but to help frontline institutions see patterns earlier, coordinate more effectively, and intervene before harm occurs.

During the Fellowship year, Dr. Eirliani will focus on building the foundation for the Odisha pilot, including data-sharing protocols, standardized case records, the first district-level vulnerability heatmap, and the technical architecture for an interactive AI platform.