To be sure, the Indian government’s position has clearly evolved over time. In mid-2018, the government think tank, Niti Aayog, published a strategy document on AI. Its focus was on increasing India’s AI capabilities, reskilling workers given the prospect of AI replacing several types of jobs and evolving policies for accelerating the adoption of AI in the country. The document underlined India’s limited capabilities in AI research. It therefore recommended incentives for core and applied research in AI through centers of research excellence in AI and more application-focused, industry-led international centers for transformational artificial intelligence.
The paper also proposed reskilling of workers because of the anticipated job losses to AI, the creation of jobs that could constitute the new service industry and recognizing and standardizing informal training institutions. It advocated accelerating the adoption of AI by creating multistakeholder marketplaces. This would enable smaller firms to discover and deploy AI for their enterprises through the marketplace, thus overcoming information asymmetry tilted in favor of large companies that can capture, clean, standardize data and train AI models on their own. Finally, it emphasized the need for compiling large annotated dynamic datasets across domains – possibly with state assistance – which could then be readily used by industry to train specific AI.
In early 2021, the Niti Aayog published a paper outlining how AI should be used “responsibly”. This set out the context for AI regulation. It divided the risks of “narrow AI” (task-focused rather than a general artificial intelligence) into two categories: direct “system” impact and the more indirect “social” impact arising out of the general deployment of AI such as malicious use and targeted advertisements, including political ones. More recently, the government set up seven working groups under the India AI program, which were to submit their reports by mid-June 2023. But these are not yet available to the public.
These groups have many mandates – creating a data-governance framework, setting up an India data management office, identifying regulatory issues for AI, evaluating methods for capacity building, skilling and promoting AI startups, guide moonshot (innovative) projects in AI and setting up of data labs. More centers of excellence in AI related areas are envisaged.