The Indian government’s proactive stance on AI regulations has sparked a debate: Is it premature to discuss policies for a technology that is still in its nascent stages within the country? For a population as diverse as India, the journey to understanding and implementing AI cannot just remain limited to the urban area but needs to be extended to the rural areas as well.
At the recently concluded Bengaluru Tech Summit, experts from various fields discussed the challenges and opportunities in regulating AI in India. The discussion highlighted the need for a use-case-driven approach rather than a sector-based or generic approach.
The Current State of AI in India
India is slowly evolving as an AI player, with significant achievements in sectors like healthcare, agriculture, and education. As reported earlier in 2024, Telangana became India’s first state to develop its own AI model. This was one of the early adoptions of AI by any Indian state. However, the level of AI integration still remains limited in the country.
Understandably, AI adoption in rural areas is slower due to challenges like limited internet access, low digital literacy, and the absence of regionally relevant datasets. Efforts like AI4Bharat and Microsoft’s Karya aim to bridge this gap, but large-scale adoption and implementation are still far from reality.
Shekar Sivasubramanian, CEO of Wadhwani AI, emphasised the importance of contextualisation for AI deployment in India. “How much of Odia is there on the internet? How much is there from Meghalaya or Tamil Nadu?” he asked, illustrating the need to create AI solutions that reflect India’s linguistic and cultural diversity.
Sivasubramanian also expressed that policies should be rooted in the realities of rural and semi-urban India, where the needs and workflows are significantly different from those in high-end urban areas.
“How does AI coexist when the presupposed assumption is standardisation?”
AI Tools Before AI Rules
Engaging in policy discussions at this stage may be too early. Formulating regulations is difficult without a comprehensive understanding and widespread implementation of AI across the nation.
Subi Chaturvedi, InMobi’s chief corporate affairs and public policy officer said, “The test of good regulation is… are you looking at adoption and proliferation, or are you putting the cart before the horse?”
She argued that regulation should come post-innovation and adoption rather than presumed progress. Chaturvedi also questioned if it’s even possible to create one-size-fits-all regulations for something as fast-changing as AI.
When NITI Aayog released the ‘National Strategy for Artificial Intelligence’ in 2018, AI was still in its birth stage in India. The reports also identified the challenges that come with adopting AI across focus sectors in India.
These included the lack of supporting data ecosystems, low levels of AI research and difficulty translating research into physical applications. It also spoke about the shortage of AI expertise and skilling opportunities.
Additional challenges were the high cost of resources and low awareness of AI’s benefits for businesses, as well as unclear privacy, security, and ethical regulations. An unattractive intellectual property regime also contributed to the hindrances.
However, Chaturvedi appreciated the government’s efforts to consult with developers, startups, and policymakers as a promising move towards more inclusive and practical solutions.
Addressing these challenges quickly through collaborative efforts, with the government leading, could help position India as a leader in AI, especially when considering the rules for India’s diverse and underserved communities.
AI Flaws are a Feature, Not a Bug
AI differs fundamentally from traditional technologies. Vivek Abraham, senior director at Salesforce, highlighted AI’s probabilistic nature, noting that identical prompts can produce varying outputs.
“Hoping for a 100% perfect world in any technology, even AI, is a pointless exercise,” he said. Abraham suggested that instead of chasing perfection, we should focus on frameworks that ensure safety while accepting the truth that some level of failure is inevitable. This is much like how the aviation and automobile industries work.
Sunil Abraham, Meta’s public policy director, added that AI’s unpredictability, including its ability to sometimes produce false answers based on user prompts, makes it tricky to regulate. He recommended tailoring regulations to specific sectors, with stricter rules for high-risk areas, such as medical diagnostics, and leaving creative and low-risk uses unregulated.
“Somebody using an LLM on their phone to write a new poem should be unregulated. Similarly, somebody using it to write a script for a movie or the lyrics for a song, should, ideally, be unregulated,” he told the audience.
The ‘India’ vs ‘Bharat’ Divide
The disparity between AI adoption in urban (India) and rural (Bharat) areas is still very large. Urban centres are witnessing AI-driven innovations in fintech and smart cities, whereas rural regions are in need of simple, intuitive, and empathetic solutions.
Sivasubramanian highlighted the importance of addressing this divide, urging policymakers to consider the realities of farmers, small businesses, and rural users. He expressed that it is crucial to first create an AI ecosystem in the country, ensuring that both ‘India’ and ‘Bharat’ are extensively adopting AI in workflows.
“The policy is also applicable to a farmer in Gujarat growing cotton,” he said. Policies must be understandable by all those who are relevant, even those who do not understand said technology.
India to Global
“AI knows no jurisdictional borders,” said Charmaine Ng, director for Asia Pacific at Schneider Electric. She emphasised the need for international standards that work across borders, highlighting the importance of collaboration among governments, industries, and civil society.
Building an ecosystem that supports education, infrastructure, and localised AI solutions is essential. As AI grows and spreads globally, a collated regulation approach that encompasses the needs of all is needed.
Ng called for global partnerships to protect privacy, trust, and democracy while helping AI benefit everyone. Such cooperation could also align India’s policies with global standards, giving Indian AI innovators a stronger chance to compete internationally.
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