Techtonic 2018

“The time from lab to land is much longer than what it needs to be”

Rajiv Kumar, vice-chairman, NITI Aayog on leveraging the Digital India initiative and extending innovation from the classroom to the shop floor

Vishal koul

Since we already have an overarching Digital India initiative in place, what’s the underlying thought behind pursuing a new policy for artificial intelligence?

It’s not a different policy. The objective of Digital India is to eliminate the digital divide in the country and implement the BharatNet project to connect 250,000 Gram Panchayats with high-speed broadband connectivity, with a focus on last mile connectivity, especially for schools, hospitals and primary healthcare centres. It lays the foundation for a digital society that will build on the growing internet penetration in the country. In the absence of a digital economy, one can’t talk of participating in any of the new technologies, be it artificial intelligence, robotics or Industry 4.0. Besides bridging the digital divide, the focus is also on how to integrate innovation in our education system, comprising schools, universities and even some of the R&D-focused institutions which are not exactly seeped in a culture of innovation. The time from lab to land in our country is much longer than what it needs to be. Though there have been some breakthrough inventions from the Council of Scientific & Industrial Research (CSIR) or the Indian Council of Agricultural Research (ICAR), the journey to the actual application still takes too long. Moreover, developed nations have already completed their digital transition and have taken the lead in artificial intelligence, machine learning, robotics, 3D printing and cloud. Hence, we too need initiatives to make the transition as swiftly as we can.

What’s the task force’s mandate?

There are professors in IITs who are already teaching and working on artificial intelligence. Industrial labs are already using machine learning to create new molecular frameworks. Even in agriculture, machine learning can get farmers to predict the response of the soil to particular seeds better. Now, we want to bring all that together. So, you’ve got a situation where you have theoretical work going on in AI and then there is the applied aspect of AI, which is where you want to bring all the stakeholders toge


You don’t want to be left behind. Do you?

Our work is exclusively for discerning readers. To read our edgy stories and access our archives, you’ve to subscribe