When AI Harms the Vulnerable: Lessons from Refugee, Justice, and Humanitarian Contexts

When AI Harms the Vulnerable: Lessons from Refugee, Justice, and Humanitarian Contexts¶ Introduction¶ Artificial intelligence systems are rarely tested most rigorously in comfortable conditions. They are tested at borders in the middle of the night, in bail hearings where a wrong prediction can mean months in pre-trial detention, and in disaster zones where connectivity is intermittent and data is incomplete. It is in these environments - high-stakes, resource-constrained, and populated by people who have the least power to push back - that the weaknesses of AI systems are exposed first and felt most acutely. At TechEthics , our mission is to develop technology that strengthens democratic resilience and social cohesion - which means engaging seriously with the cases where technology has done the opposite. This article examines documented and representative failures of AI deployment across three domains: refugee and asylum processing, criminal justice, and humanitarian response. In each