Designing AI-Assisted Library Services to Empower Marginalized Communities: A Model for Social Inclusion - Irva Yunita; Rahmat Iqbal (UIN Raden Intan Lampung, 2025)
This study aims to design an artificial intelligence (AI)-assisted library service model to empower marginalized communities through a social inclusion approach. The research is grounded in the context of information access gaps and low digital literacy faced by disadvantaged groups, highlighting the need for library service innovations that are relevant to technological developments and community needs. This study employed a descriptive qualitative method, with data collected through literature review, observation, and interviews with librarians and representatives of marginalized communities. The data were analyzed using a thematic approach and verified through triangulation techniques. The findings indicate that integrating AI technologies—such as Canva for graphic design, CapCut for video production, and DeepL Translate for language translation—significantly enhances the capabilities and active participation of communities in accessing, processing, and producing information. The implementation of these services not only ensures equitable access to digital resources but also equips users with practical skills applicable to economic development, education, and social advocacy. The proposed service model is based on the core principles of social inclusion: equitable access, active participation, information empowerment, and recognition of diversity. This study concludes that AI-assisted library services designed under social inclusion principles can be an effective strategy to reduce the information gap and strengthen the role of libraries as agents of social change. The implications of this research are expected to serve as a reference for developing more inclusive library policies and practices in the digital era.