AI & Migration: Data Models to Improve Humanitarian Response and Policy Across the Channel

This project develops an AI-powered policy planning framework that integrates migration theory with machine learning to improve the fairness, accuracy, and ethics of migration decision making

This project addresses the growing use of AI in migration governance by developing a culturally informed, data-driven policy planning framework. While automated systems promise efficiency, they often lack contextual awareness and risk reinforcing bias and discrimination. By integrating migration theory with machine learning, the project will curate and harmonise diverse datasets—ranging from border control to demographic records—to improve predictive accuracy and reduce algorithmic bias.

In collaboration with stakeholders, including the Franco-British Council, the team will validate the framework through real-world engagement and produce a technical report, policy briefs, and academic outputs.

The project aims to empower policymakers and humanitarian organisations with transparent, ethical tools for migration planning, while laying the groundwork for future interdisciplinary research. It contributes to the UCL Grand Challenge of Data Empowered Societies by bridging AI and social science to support fairer, more humane migration governance.