Narendra Modi government announced a major initiative to adopt artificial intelligence (AI) for India’s development programmes but three months later it has been realised that things are easier said than done. A Report published on June 04, Niti Aayog took a look at India’s AI strategy, there were five major factors outlined:
- Health care
- Smart cities and Infrastructure
- Smart mobility
The lack of potential data research work at homegrown companies or in the academic and not only is the volume of data scarce, the quality is also questionable. Professional skilled labour in areas such as AI and data analytics are very costly in India compared to other countries. India ranked a dismal 43 out of 45 countries in the 2017 global IP index (pdf) compiled by the US Chamber of Commerce, which ranks patents, copyrights, trademarks, trade secrets and market access, enforcement, and ratification of international treaties.
A statistical Report of 2016, shows that just 45,000 patents were filed in India on the other hand China registered over 1.1 million in the same year.
India unlike the US and China which have hundreds of educational programmes in data science and AI, does not have anything even close to it. Even though India produces over a million engineers every year, a 4% dismissal of AI professionals in the country have largely worked on cutting-edge technologies such deep learning and neural networks.
The major drawbacks of this initiative to launch Artificial Intelligence as listed by Niti Aayog were:
- Low Intensity of work
- High resource cost
- Low Awareness
- Unclear Privacy
- Ethical Regulations
- Unattractive Intellectual property (IP) Regime
- Inadequate expertise, manpower and skilling opportunities