Uncovering Algorithmic Avidyā in Generative AI

A Catur Pramāṇa Red Teaming Approach

Abstract

Western-centric AI ethics frameworks currently marginalize Hindu epistemology, triggering an epistemological crisis within spiritual domains. Addressing this, this study operationalizes the Balinese Hindu Catur Pramāṇa framework to empirically audit the Gita-GPT model, aiming to diagnose Algorithmic Avidyā (Algorithmic Ignorance) and formulate mitigation strategies. Using a qualitative epistemological red teaming methodology, 15 adversarial prompts nuanced with Balinese theology were executed, with outputs deductively analyzed against authoritative texts. The results emphatically demonstrate that the system systematically generates Algorithmic Avidyā through four fatal mechanisms. First, at the Śabda layer, the machine actively executes epistemic fabrication and hallucination of sacred verses. Second, at the Pratyakṣa layer, it causes severe context collapse by failing to recognize critical spatial-cultural boundaries (Desa-Kala-Patra). Third, at the Upamāṇa layer, it imposes materialistic comparative fallacies that distort theological analogies. Fourth, at the Anumāṇa layer, it constructs illusions of reasoning entirely devoid of causal spiritual awareness. Consequently, this study concludes that uncalibrated generative AI fundamentally disrupts authentic spiritual mediation, creating a representational hegemony that directly threatens traditional religious authority and erodes Balinese customary law (Dresta). To mitigate these severe ethical impacts and preserve the local religious ecosystem, we strongly advocate for a paradigm shift toward theological sovereignty. This requires constructing an endemic Nusantara Large Language Model, mandating Expert-in-the-Loop governance involving spiritual authorities (Sulinggih), and aligning Reinforcement Learning algorithms explicitly with Dharma principles.