We have visited high-tech refugee camps in Greece, seen violent borders all over Europe, and spoken with hundreds of people who are at the sharp end of technologically-assisted brutality. AI in migration is increasingly used to make predictions, assessments, and evaluations based on racist assumptions it is programmed with. But with upcoming, legislation to regulate Artificial Intelligence (the EU"s "AI Act") the EU has a chance to live its self-proclaimed values, set a global standard and draw red lines on the most harmful technologies. Politicians have turned migration into a political weapon and the EU's policies are becoming increasingly violent: hardening of borders, increased deportation, empowering agencies like Frontex which have been repeatedly implicated in severe human rights abuses, and even condoning the arrest and incarceration of search-and-rescue volunteers, doctors, lawyers, and journalists. Increasingly, surveillance and automated technologies are being tested out at borders and in migration procedures -- with people seeking safety being treated as guinea pigs.

The migration of conversational AI agents across different embodiments in order to maintain the continuity of the task has been recently explored to further improve user experience. However, these migratable agents lack contextual understanding of the user information and the migrated device during the dialog conversations with the user. This opens the question of how an agent might behave when migrated into an embodiment for contextually predicting the next utterance. We collected a dataset from the dialog conversations between crowdsourced workers with the migration context involving personal and non-personal utterances in different settings (public or private) of embodiment into which the agent migrated. We trained the generative and information retrieval models on the dataset using with and without migration context and report the results of both qualitative metrics and human evaluation. We believe that the migration dataset would be useful for training future migratable AI systems.