A plan for India to carve its own space in the AI dominance race

Context: Instead of getting into a complex and expansive algorithm race (comparison with the US), India's national goal should be to turn data into useful "knowledge", specific to solving our own problems.

Challenges to Artificial Intelligence (AI) adoption in India:

• Lack of top-notch AI-research entities: like universities and colleges, either measured by citations or other parameters such as winning prestigious AI contests; Poor performance in algorithm development.
• Increasing Chinese dominance: Chinese scientists have demonstrated and claimed "quantum supremacy" in a race that seems to upend Google and the US.

Opportunities for AI in India:

• Rise in data usage: during the pandemic; Digital data growth rate twice as fast as the global average.
  • Digital data rose from 40,000 petabytes in 2010 to 2.3 million petabytes by 2020.
• Atmanirbhar Bharat initiative: focused on the localization of manufacturing, products and technology, including citizens' data.
• Unified Payments Interface (UPI): Uplifting hundreds of millions of people and enabling over 9,000 start-ups to build products and services.
• Large workforce: that can take part in collecting and codifying data for consumption and in creating large-scale technology infrastructure.

Way forward:

• Focus on India-specific use cases: and data instead of focusing on complex algorithm race.
• Turning data into 'knowledge": "knowledge" comes from general-purpose algorithms, and good-quality data between 5–30% of the total data takes up the majority of preparation time for any AI work.
• Creating data infrastructure in key areas: As India did in cases of Aadhaar and UPI. It will -
  • Improve the quality of life at an everyday level, and significantly enhance governance.
  • Elevate interoperability, which in turn would reduce operational costs and serve as a "template" for developing a post-COVID global AI economy.
• Develop a five-year view to plan and fund the following projects:
  • Projects for the private sector could be: Address, Identity and Gender Disambiguation; It can add up to 1% of India's gross domestic product (GDP).
  • Projects for public services could be: Optimization of public transport in the post-pandemic world, using sensor-based data collected as part of the Indian government's smart city programmes.
  • Projects for government services could be: Integration of public services and spending to ensure predictive usage of scarce resources for growth.
• Protect user privacy: using technologies that enable the generation of unbiased AI decisions to ensure that the outcomes and recommendations are acceptable in a country as diverse as India.