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The dream of being an AI powerhouse
Article:
- Priyanka Pulla, author, analyse India’s dream of becoming an Artificial Intelligence(AI) powerhouse and challenges in fulfilling this ambition.
Important Analyses:
2. Recently, NITI Aayog in its report has chalked out an ambitious strategy for India to become an artificial intelligence powerhouse.
3. Artificial intelligence means the use of computers to make decisions instead of human beings.
4. NITI Aayog envisions AI solutions for India especially in five key areas-Agriculture, Smart cities, healthcare, education, infrastructure, and transport.
5. In Agriculture sector, machines will be helpful in the following manner:
- Provide information to farmers on various aspects related to agriculture like quality of soil etc.
- India could see a farming resolution because the country has 30 million farmers with smart phones but poor extension services.
- With India planning to install 100 GW of solar power by 2022, such AI will play central role in power planning.
- However, there are various hurdles in achieving these goals:
Lack of data.
- Most sophisticated form of machine learning like “deep learning”, attempt to mimic the human brain.
- Deep learning does not able to work for all companies in India because of lack of data.
- Presently, the firm uses traditional machines learning technologies such as regression analysis that work with less data.
- Another problem for AI firms today is finding the right people.
- As per the NITI Aayog’s report, about 50 Indian scientists carry out serious research and concentrated in elite institutions.
- Only 40% of AI professionals have worked in emerging technologies like deep learning.
- According to survey of Linkedin, 386 out of the 22,000 people with PhDs in AI across the would be Indians.
- Open libraries of machine learning code, can be customized to solve Indian problems.
6. The discussion paper of NITI Aayog mentioned no timeline for India’s goal of becoming AI superpower. But following changes are required immediately :
a)The government must collect and digitize data under its existing programmes.
b) To close the skill gap.
- For this, NITI Aayog suggested setting up a network of basic and applied AI research institutes. These institutes must collaborate with agricultural universities, medical colleges and infrastructure planners.
c)NITI Aayog’s ambitious road map does not mention deadlines or funding. Without these, it lacks accountability. The government must specify its commitments on these fronts.
