Data Migration in HCI: The Politics of Invisible Borders, Informal Networks, and Immigrants’ Data

要旨

Host countries' infrastructures often challenge the legitimacy of immigrants' data from their home country, resulting in limiting their access to civic services. Drawing on interviews with 32 immigrants in Canada, we conceptualize Data Migration as the socio-technical, political, and infrastructural process in which immigrants make their data legitimate in their host country. Our findings show how credit bureaus, credential evaluators, healthcare databases, immigration portals, and other digital governance systems gatekeep immigrants’ civic rights and opportunities. We also highlight the crucial role of community-mediated informal networks in sustaining access where formal infrastructures fail. Using Ribot and Peluso’s Theory of Access, we demonstrate that systemic biases in policies and technical standards often privilege some immigrants while constraining others. Our work calls on HCI to critically examine migration governance and design data ecosystems that are equitable, pluralistic, and capable of supporting immigrant agency.

著者
Yasaman Rohanifar
University of Toronto, Toronto, Ontario, Canada
Rachel FJ. Levine
University of Toronto, Toronto, Ontario, Canada
Sharifa Sultana
University of Illinois Urbana-Champaign, Champaign, Illinois, United States
Syed Ishtiaque Ahmed
University of Toronto, Toronto, Ontario, Canada

会議: CHI 2026

ACM CHI Conference on Human Factors in Computing Systems

セッション: Social Impact and Responsible Tech

P1 - Room 120
7 件の発表
2026-04-16 20:15:00
2026-04-16 21:45:00