While India is grappling with regulating artificial intelligence (AI), many argue that such discussions are being rushed, as AI is still in its early stages and adoption is still limited.
Experts at the recently concluded Bengaluru Tech Summit highlighted the need for policymakers to take a use-case-driven approach rather than a sector-based or generic approach.
For a diverse country like India, developing AI must go beyond urban-centric debates and take into account the unique challenges in rural areas, such as wider use of regional languages and less internet access.
AI adoption in rural areas is slower due to challenges like low digital literacy, limited internet access, and lack of regionally relevant datasets, and large-scale implementation is still far from reality.
Subi Chaturvedi, InMobi’s chief corporate affairs and public policy officer, argued that regulations should come post-innovation and adoption rather than perceived progress.
Vivek Abraham, senior director at Salesforce, pointed out that AI's probabilistic nature means that identical prompts can produce varying outputs, and it is thus difficult to regulate.
Sunil Abraham, Meta’s public policy director, recommended tailoring regulations to specific sectors with stricter rules for high-risk areas such as medical diagnostics and leaving low-risk uses unregulated.
Addressing challenges, particularly in India's underserved communities, could position India as a leader in AI.
Many experts spoke about the importance of creating AI solutions that reflect India’s linguistic and cultural diversity and take into account the realities of rural and semi-urban India.
Charmaine Ng, director for Asia Pacific at Schneider Electric, emphasised the need for international standards for AI that work across borders.