India Foundation organised a discussion on ‘AI in the light of Dharmic Science and Wisdom’ on 15 November, 2024 in New Delhi with Padma Bhushan Dr David Frawley, Vedacharya and Founder, American Institute of Vedic Studies as the speaker and Prof (Dr) K Gopinath, Professor, Newton School of Technology, Rishihood University as the discussant. Mr Côme Carpentier De Gourdon, Distinguished Fellow, India Foundation, moderated the discussion.
Mr Côme Carpentier De Gourdon drew attention to the expanding learning capabilities of AI and the autonomous development of neural networks which often eludes the understanding of their architects. He also mentioned David Frawley’s upcoming book on the subject and his seminars exploring the intersection of AI and spirituality.
Dr David Frawley critiqued the limitations of AI, stressing that it has not, and perhaps never will, achieve the level of intelligence represented by Lord Ganesha—the epitome of supreme intelligence. AI, while useful for communication, information storage, and comparative analysis, is fundamentally devoid of real human intelligence. He questioned the term ‘artificial intelligence’, arguing that it misleadingly suggests the creation of an ‘artificial human’, which is far from reality.
The discussion transitioned to the Upanishadic philosophy of knowledge, which distinguished between quantifiable knowledge and eternal, universal knowledge. Dr Frawley asserted that India excelled in producing high-intelligence individuals in technology and India’s emphasis on Vidya—self-knowledge—and the pursuit of infinite, universal understanding preserves its edge in intellectual contributions. He also reflected on the Upanishadic view of reality, noting that while physical phenomena can be subjectively measured and quantified, true reality is immeasurable, transcending quantification.
Dr Frawley addressed the replicability crisis in modern science, highlighting its implications for the credibility of experimental results and the limitations of artificial intelligence (AI). He asserted that AI, lacking prana (life force), is not a living entity but a tool limited to programmed functions. He also explored the adverse effects of AI on education and attention spans, stressing the importance of sustained attention as a cornerstone of yogic practice. He critiqued the Western world’s overreliance on intellect, advocating for a shift toward direct perception and inner knowledge as outlined in the Vedantic tradition. The latter designates Samadhi—the silent and focused mind—as a pathway to true knowledge.
The discussion highlighted the centrality of prana in sustaining both physical and psychological immunity. Modern society’s overdependence on technology is linked to a decline in prana and creativity, with Dr Frawley calling for an educational system that fosters inner knowledge and nurtures creativity. He also discussed the ethical dimensions of technological advancements and cautioned against the potential dangers of new technologies while recommending their ethical and mindful use. He underlined the role of the government in regulating technology to ensure its responsible deployment. Additionally, the vulnerabilities of centralised technological civilisations were discussed, requiring greater local responsibility and adherence to global ethical standards in managing technology. This balance, Dr Frawley argued, is essential for creating a sustainable and resilient society.
Prof (Dr) K Gopinath, from Rishihood University explored the unique perspective of Indian thought and its potential influence on artificial intelligence (AI), particularly through the distinction between linear and cyclic models of reasoning and computation. He argued that while linear reasoning dominates Western approaches, the cyclic model—more prevalent in Indian intellectual traditions—aligns more closely with the underlying principles of AI. He elaborated on the cyclical model, accentuating its iterative method for learning, adjustment, and prediction, which mirrors the functioning of AI systems. Prof Gopinath explained how AI employs deep learning techniques to predict outcomes and adjust its internal parameters based on continuous observations, demonstrating the practical application of cyclical reasoning.
He explained the integration of observation with computation in Indian thought, referencing drik ganita (calculation through observation) practised in traditional Indian astronomy and mathematics, and he highlighted how the cyclical model allows for a deeper understanding of complex realities by continuously refining predictions based on new data. This adaptive approach, he argued, is more effective than purely linear axiomatic reasoning in grappling with the intricacies of AI systems. Prof Gopinath also addressed the challenges in AI development, including the energy-intensive nature and extended training times of deep learning models, and underscored the need for a balanced integration of linear and cyclical models to enhance AI’s efficiency and applicability. Applying observation in AI was highlighted as a key factor in enabling dynamic adjustments and improving model accuracy over time.
Concluding his presentation, Prof Gopinath laid stress on the importance of understanding and leveraging both linear and cyclical models in AI research. He advocated for a synthesis of these approaches to build systems capable of addressing the multifaceted realities of the modern world, drawing inspiration from the rich traditions of Indian computational thought.
