Aligning AI Technology with Dharma: Values, Culture, and Consciousness in the Age of Generative and Agentic AI

Across 107 countries surveyed by Tao et al. (2024), every major large language model most closely resembles the value profile of English-speaking Protestant European societies. India ranked among the least well represented populations of 1.4 billion. AI alignment is never value-neutral. The pre-training, fine-tuning, RLHF, and constitutional methods that produce contemporary models embed cultural assumptions at every stage, and those assumptions originate from a narrow civilisational source. Mohamed, Png, and Isaac (2020) name this pattern algorithmic coloniality, and the empirical record now supports the diagnosis.

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This paper develops a Dharmic framework for AI alignment, working from Hindu, Buddhist, Jain, and Sikh primary sastric sources. The framework distinguishes thin alignment, which is rule-compliance verified by benchmarks, from thick alignment, which is contextual judgement adapted to Svadharma and capable of navigating cultural ambiguity. Satya names a foundational standard for AI truthfulness that exceeds benchmark-style hallucination scoring. Ahimsa extends the safety taxonomy to physical, epistemic, psychological, economic, cultural, and karmic dimensions. Karma provides a structured account of distributed responsibility for autonomous and agentic AI. Nishkama Karma contests engagement-maximisation as the default product objective. The Samkhya-Yoga classification of Sattva, Rajas, and Tamas yields a typology for evaluating AI systems, with most commercial AI sitting in the Rajasic register.

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A three-layer alignment architecture follows. Niyama corresponds to written rules and constitutional principles. Sadhana corresponds to the alignment training pipeline understood as disciplined practice. Viveka covers interpretability, evaluation, and ongoing discernment. The paper proposes Technological Swaraj as the orienting goal for Indian AI governance and identifies four contributions Indian institutions must build: cultural value benchmarks for Bharatiya contexts, Dharmic constitutional AI principles, multilingual training corpora across the twenty-two scheduled languages, and a sustained Darshana-AI research programme.