Digital Welfare Borders: The effects of Artificial Intelligence in Migrants’ Access to Welfarecore
DigiWeB · Horizon Europe grant · 2026-02-01–2031-01-31
EC contribution
Total cost
Beneficiaries
About the data
Source: CORDIS (official EU open data), Horizon Europe. Framework HORIZON · call ERC-2025-STG · scheme HORIZON-ERC · topic ERC-2025-STG. CORDIS record →
Objective
DigiWeB is the first study of how Artificial Intelligence (AI) is merging welfare systems and migration management. Governments are increasingly relying on AI to make decisions about who gets welfare benefits. This is important because AI combines large amounts of data and makes predictions based on ""risk factors,"" which can be discriminatory, especially against marginalized migrants.DigiWeB takes a broad, interdisciplinary approach and makes four contributions: 1. It pushes the frontiers of research on digital welfare systems, explaining how AI and connected databases work to make decisions about welfare. 2. It introduces a new way of studying AI’s impact by combining data science and social science, particularly in the context of migration management.3. The project’s approach can be applied to other fields, like policing or counterterrorism, to understand the broader effects of AI.4. It highlights a significant shift in how governments operate, showing how welfare systems are changing due to AI and digital technologies, with international implications.DigiWeB has three main aims:1. To understand how welfare-AI functions and influences welfare decisions.2. To explore how these decisions are implemented by social workers and how they impact migrants.3. To theorize the international effects of welfare-AI.The project uses both data science to study welfare algorithms and social science to explore how they impact people in practice across three countries (Netherlands, Sweden, UK). It will provide a major advance in understanding modern government, as AI is transforming welfare provision and migration management faster than current scholarship and policy can respond. By extension, DigiWeB will offer practical improvements for responsible welfare-AI.""
Beneficiaries (1)
| Organisation | Country | Role | EC contribution | SME |
|---|---|---|---|---|
| QUEEN MARY UNIVERSITY OF LONDON | UK | coordinator | €1,499,763 |
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