Artificial Intelligence and Machine Learning: Re Examining Modern Computational Intelligence Through Indian Knowledge Systems

The explosive growth of Artificial Intelligence (AI) and Machine Learning (ML) has transformed domains from healthcare to autonomous systems, yet prevailing paradigms—built on statistical induction, gradient descent, massive datasets, and opaque neural networks—face persistent challenges: lack of explainability, brittleness to shifts, cultural and ethical biases, unsustainable compute demands, and a reductionist equation of intelligence with predictive power alone. These limitations invite a deeper inquiry into alternative epistemic foundations for computational intelligence. This paper re-examines modern AI/ML through the lens of Indian Knowledge Systems (IKS)—the rigorous philosophical, logical, and cognitive traditions preserved in Nyāya, Vaiśeṣika, Sāṃkhya-Yoga, Advaita Vedānta, Upaniṣads, Yoga Sūtras, and allied śāstras. Far from mere cultural heritage, IKS offers substantive conceptual tools to complement and correct contemporary approaches. Key intersections include: Nyāya’s sophisticated pramāṇa framework (perception, inference, analogy, testimony) and tarka-based reasoning, which provide structured inference pathways beyond pure data induction—potentially strengthening explainable AI (XAI), counterfactual analysis, and hallucination reduction in large language models. Sāṃkhya-Yoga’s distinction between puruṣa (pure consciousness) and prakṛti (material/computational evolution) challenges anthropomorphic claims of machine “awareness” and inspires architectures that separate pattern computation from meta-cognition. Advaita Vedānta’s non-dual ontology and māyā doctrine illuminate the illusory nature of data-derived “reality,” resonating with debates on simulation and generative limits. Dharmic ethics—centered on ahimsā (non-harm), satya (truth), and loka-saṅgraha (world welfare)—offer normative anchors against unchecked utilitarian optimization in reinforcement learning and autonomous technologies. The paper advocates hybrid epistemologies: neurosymbolic models infused with Nyāya logic, consciousness-aware designs drawing from Yoga’s citta-vṛtti framework, and value-aligned objectives rooted in dharma. Re-framing intelligence through IKS shifts the focus from disembodied scalability to holistic, reflective, ethically responsible cognition oriented toward human flourishing (puruṣārtha), cosmic order (ṛta), and ecological harmony. This approach aligns with India’s NEP 2020 emphasis on IKS integration and advances a decolonial, pluriversal vision for global AI development.