Research project

Bridging Generations and Cultures: Enhancing Refugee Women’s Access to Information through Generative AI and Cultural Exchange

Project overview

Funded by Web Science Institute Stimulus Fund (?5435.8) , through the project, we aim to prioritizing the voices and experiences which are currently underrepresented groups in digital society research (House of Lords, 2023). Many refugee women are skeptical about engaging with technology, perceiving it as inaccessible or irrelevant to their cultural and daily needs. While inspired by their children’s use of digital tools, they feel existing platforms, including Generative AI (GenAI), lack cultural sensitivity and inclusivity.

Project Summary
This interdisciplinary project aims to facilitate intergenerational knowledge exchange by engaging university students in supporting refugee women in using Generative AI (GenAI) tools to enhance their access to essential health and daily life information resources. Song and storytelling workshops will foster meaningful relationships between university students and the project participants. Through the workshop,
participants will share their cultural knowledge and lived experiences, contributing to the training and refinement of AI models with culturally relevant inputs. This reciprocal exchange will empower refugee women while broadening the global awareness and intercultural competencies of participating students.

Staff

Lead researchers

Dr Chiying Lam BEd, MA, PhD, FRSPH

Lecturer in Community Music and Scl Jstc
Research interests
  • Post-colonial discourses of power & identity within the music practitioners' community
  • Musicians' pedagogical practice
  • Music education research methods
Connect with Chiying

Other researchers

Dr Tan Viet Tuyen Nguyen

New Frontiers Fellow
Research interests
  • Human-centered Artificial Intelligence
  • Social Human-Robot Interaction
  • Multimodal Perception and Interaction
Connect with Tan Viet Tuyen

Collaborating research institutes, centres and groups

Research outputs