Human-Centered AI Applications for Canada's Immigration Settlement Sector

Isar Nejadgholi, Maryam Molamohammadi, Kimiya Missaghi, Samir Bakhtawar
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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 service providers and government organizations to develop tailored AI tools that are empowering, inclusive and safe.
加拿大移民安置部门以人为本的人工智能应用
虽然人工智能已被频繁应用于移民领域,但这些应用大多集中在选择和筛选上,主要是为了增强国家和当局的能力,由于其可靠性研究不足以及对移民生活的影响较大,引起了人们的关注。与此相反,本文强调了人工智能在加拿大移民安置阶段的潜力,在这一阶段,信息的获取至关重要,而服务提供者却不堪重负。通过强调移民安置部门是可靠的人工智能应用的主要候选者,我们展示了其直接赋予移民权力的独特能力,但在人工智能研究中仍未得到充分探索。我们概述了以人为本、负责任的人工智能解决方案,以促进新移民的融入。我们呼吁人工智能研究人员以我们的工作为基础,参与多学科研究,并与服务提供商和政府组织积极合作,开发赋权、包容和安全的定制化人工智能工具。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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