Ethical considerations in AI-powered language technologies: insights from East and West Armenian

Abstract

This study examines the ethical challenges and opportunities of AI-powered language technologies in the context of East and West Armenian, addressing critical concerns such as data sovereignty in diaspora communities, algorithmic bias in low-resource language processing, and the preservation of cultural authenticity. A structured ethical framework is proposed, emphasizing participatory governance, fairness-aware AI training, and transparency mechanisms to ensure linguistic inclusivity and cultural sustainability. The findings align with prior research on AI ethics and minority language preservation, confirming the importance of community-driven data governance while extending existing models through adaptive AI methodologies, interdisciplinary collaboration, and fairness-aware dialectal modeling. Case studies illustrate successful implementations of ethical AI principles, demonstrating measurable improvements in linguistic fairness, community trust, and dialectal representation. However, challenges remain in scalability, dataset availability, and balancing ethical trade-offs between privacy protections and AI performance. Future research should explore adaptive AI models that dynamically integrate sociolinguistic variations, strengthen participatory engagement strategies, and expand comparative analyses with other minority-language AI initiatives. While this study focuses on Armenian languages, its insights provide a scalable model for addressing the ethical and technological challenges posed by AI in linguistically diverse contexts.