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Into the Unknown: Leveraging Conversational AI in Supporting Young Migrants' Journeys Towards Cultural Adaptation

Authors: Sunok Lee; Dasom Choi; Lucy Truong; Nitin Sawhney; Henna Paakki;

Into the Unknown: Leveraging Conversational AI in Supporting Young Migrants' Journeys Towards Cultural Adaptation

Abstract

Accelerated globalization has made migration commonplace, creating significant cultural adaptation challenges, particularly for young migrants. While HCI research has explored the role of technology in migrants' cultural adaptation, there is a need to address the diverse cultural backgrounds and needs of young migrants specifically. Recognizing the potential of conversational AI to adapt to diverse cultural contexts, we investigate how young migrants could use this technology in their adaptation journey and explore its societal implementation. Through individual workshops with young migrants and stakeholder interviews - including AI practitioners, public sector workers, policy experts, and social scientist - we found that both groups of participants expect conversational AI to support young migrants in connecting with the host culture before migration, exploring the home culture, and aligning identities across home and host cultures. However, challenges such as expectation gaps and cultural bias may hinder cultural adaptation. We discuss design considerations for culturally sensitive AI that empower young migrants and propose strategies to enhance societal readiness for AI-driven cultural adaptation.

Publisher Copyright: © 2025 Copyright held by the owner/author(s).

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Keywords

conversational agent, large language model, migrants, cultural adaptation

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    influence
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
2
Top 10%
Average
Average
Green
hybrid