Human-Centered AI Applications for Canada's Immigration Settlement Sector
Isar Nejadgholi, Maryam Molamohammadi, Kimiya Missaghi, Samir, Bakhtawar

TL;DR
This paper explores the potential of human-centered AI to improve Canada's immigration settlement services by empowering immigrants and supporting service providers, emphasizing responsible and inclusive AI development.
Contribution
It highlights the under-explored application of AI in immigration settlement, proposing a human-centered approach to enhance integration and collaboration with stakeholders.
Findings
AI can directly empower immigrants in settlement processes
Settlement sector is a promising but under-researched AI application area
Call for multidisciplinary collaboration to develop responsible AI tools
Abstract
While AI has been frequently applied in the context of immigration, most of these applications focus on selection and screening, which primarily serve to empower states and authorities, raising concerns due to their understudied reliability and high impact on immigrants' lives. In contrast, this paper emphasizes the potential of AI in Canada's immigration settlement phase, a stage where access to information is crucial and service providers are overburdened. By highlighting the settlement sector as a prime candidate for reliable AI applications, we demonstrate its unique capacity to empower immigrants directly, yet it remains under-explored in AI research. We outline a vision for human-centred and responsible AI solutions that facilitate the integration of newcomers. We call on AI researchers to build upon our work and engage in multidisciplinary research and active collaboration with…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
Topicsdemographic modeling and climate adaptation
