AMINA: The Inclusive and Accountable AI for Marginalized Immigrant Nonprofit Assistance

2026-08-30

AI Summary

研究针对移民非营利组织面临的排斥问题，通过混合方法设计并评估了AI助手AMINA，旨在支持日常运营、对抗错误信息及促进多语言交流。

Abstract

Immigrant-led nonprofit groups, particularly those operating in politically sensitive contexts, face exclusion from formal registries and digital platforms. This paper reports a three-phase mixed-methods study with Iranian immigrant nonprofit practitioners: 27 semi-structured interviews, a co-design session, and 7 evaluation and feedback interviews on a prototyped AI assistant, AMINA. Our findings highlight how legitimacy barriers, capacity gaps, and politically charged misinformation constrain nonprofit operations. We translate these insights into design goals for an inclusive nonprofit AI assistant: support for everyday group operations, recognition of informal nonprofit efforts, proactive countering of misinformation, and multilingual, accessible interaction. User evaluations show AMINAs potential to reduce reporting burdens and foster transparency through proactive reminders, and catalyze collaboration across dispersed networks. We contribute to CSCW and HCI by characterizing the cooperative work of transnational immigrant nonprofits, extending scholarship on informality and misinformation, and demonstrating how AI can act as a collaborative partner that strengthens, rather than displaces, the human connections at the core of nonprofit ecosystems, while also posing major risks.

Problem

• marginalized immigrant nonprofits
• legitimacy barriers
• capacity gaps
• misinformation

Innovation

• AI assistant
• inclusive design
• misinformation countermeasures
• multilingual accessibility
• nonprofit support