
The rise of generative AI, exemplified by ChatGPT, has captivated the public by offering unmediated access to advanced models. Prof Ravindran described this as a “co-pilot” model, augmenting human intelligence in fields like programming, design, and healthcare. However, he cautioned against over-reliance on such systems due to critical issues like bias, robustness and misinformation. He cited real-world examples, such as biases in recruitment and judicial tools, which underscore AI’s potential to perpetuate harm if unchecked.
Turning to India, he lauded homegrown innovations like the Garbhini-GA models for pregnancy care and a muzzle-pattern recognition system for cattle identification. These projects demonstrate how AI can address India-specific challenges. However, he warned that the lack of diverse datasets and a gap between proofs of concept and scalable solutions hinder progress.
Prof Ravindran advocated for a holistic approach to AI regulation, involving government, industry, and academia. He proposed a multi-stakeholder safety institute to address concerns like bias, deepfakes, and environmental impact while fostering responsible AI development.
Concluding with a word of caution, he stressed that AI, for all its advancements, still struggles with simple human tasks. He called for better public education on AI to demystify its capabilities and align its potential with societal needs.On Day 1 of the 13th edition of the ThinkEdu Conclave, presented by SASTRA University and hosted by The New Indian Express, Prof Balaraman Ravindran, Head of the Wadhwani School of Data Science and Artificial Intelligence (WSAI) at IIT Madras, delivered a thought-provoking session titled "Intelligence at Work: What Youngsters Need to Know About AI." With artificial intelligence (AI) being one of the most transformative forces of the 21st century, Prof Ravindran explored its potential to reshape industries, education and society at large while addressing its ethical and practical challenges.
Prof Ravindran traced AI’s origins back to Alan Turing, dismissing the notion that AI’s story began with Sam Altman or ChatGPT. He highlighted early innovations, such as the chatbot ELIZA from the 1960s, and explained how AI has evolved from problem-solving tools to a service-driven ecosystem. This shift, he noted, reduces the risk of another "AI winter" and solidifies AI’s growing relevance across industries.
Discussing AI’s ubiquity, he pointed out how it powers everyday conveniences like Google Maps and food delivery apps — systems many use without realizing their underlying complexity. He explained that past breakthroughs like IBM’s Deep Blue and Watson relied on diverse technologies that don’t align with the current generative AI trend.