Relevance: GS Paper III
Why has this issue cropped up?
In a recent discussion paper, NITI Aayog has chalked out an ambitious strategy for India to become an artificial intelligence (AI) powerhouse.
What is AI?
AI is the use of computers to make decisions that are normally made by humans.
How can AI be helpful to India?
- Many forms of AI surround Indians already, including chatbots on retail websites and programs that flag fraudulent bank activity.
- But NITI Aayog envisions AI solutions for India on a scale not seen anywhere in the world today, especially in five key sectors — agriculture, healthcare, education, smart cities and infrastructure, and transport.
- In agriculture, for example, machines will provide information to farmers on the quality of soil, when to sow, where to spray herbicide, and when to expect pest infestations. It’s an idea with great potential: India has 30 million farmers with smartphones, but poor extension services. If computers help agricultural universities advise farmers on best practices, India could see a farming revolution.
Obstacles to AI in India
- The first problem is data. Machine learning, the set of technologies used to create AI, is a data-guzzling monster. It takes reams of historical data as input, identifies the relationships among data elements, and makes predictions. Unfortunately, India has sparse data in sectors like agriculture, and this is already hampering AI-based businesses today.
- Another problem for AI firms today is finding the right people. Only about 50 Indian scientists carry out “serious research” and they are concentrated in elite institutions such as the Indian Institutes of Technology and the Indian Institutes of Science. Meanwhile, only about 4% of AI professionals have worked in emerging technologies like deep learning.
Way forward
- First, if the government is serious about AI solutions powering agriculture or healthcare, it must collect and digitise data better under its existing programs.
- Second, to close the skill gap, NITI Aayog suggests setting up a network of basic and applied AI research institutes. But if these institutes are to fulfil their mandate, they must collaborate closely with agricultural universities, medical colleges and infrastructure planners.
- Third, NITI Aayog’s ambitious road map does not mention deadlines or funding. Without these, it lacks accountability.
Conclusion
The government must make haste and specify its commitments on the above fronts.
