Integrating Community-Based AI with Local Knowledge for Sustainable Water Governance: A Case from the Osing People - Hidayati, Emi; Septalinda, Ficky; Fardian, M. Iqbal; Zidniyati, Zidniyati (Jurnal Penelitian IPTEKS, 2025)
Water scarcity is an escalating concern, especially in rural and indigenous regions where ecological vulnerability intersects with institutional weakness. This study investigates how Artificial Intelligence (AI) can be integrated with the Sustainable Livelihoods Approach (SLA) to enhance water governance among the Osing indigenous people in Banyuwangi, East Java. Using a mixed-method, multi-site design—including interviews, focus groups, and participatory observations—the research explores how local knowledge, social capital, and institutional structures shape community responses to AI-based interventions. Findings show that while AI offers predictive potential, its success hinges on epistemic justice and cultural contextualization. Villages with strong social and financial assets, such as Olehsari, exhibit greater readiness for AI integration, whereas others face barriers including low digital literacy, weak infrastructure, and limited trust. A hybrid model of community-based AI is proposed, combining algorithmic tools with indigenous ecological indicators and participatory design processes. The study contributes to the growing discourse on inclusive technology by demonstrating that sustainable water governance requires co-produced knowledge systems, where local and scientific epistemologies interact symmetrically. The integration of AI and SLA offers a replicable framework to address water challenges in indigenous communities without marginalizing their knowledge and identity.