Like ruling regimes elsewhere, the Narendra Modi government, too, has seen artificial intelligence as a gamechanger for a while but it started work earnestly on tailoring a strategy around the technology only about a year ago. That was when the government’s policy think tank Niti Aayog called for a meeting, chaired by its CEO Amitabh Kant.
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The meeting was the start of a journey to understand what AI means for India – could it be meaningful for a country of 1.3 billion people or was it just another flashy technology shining on the hype cycle?
For months after, at several meetings with the academia, government departments and agencies, technology companies, and amongst Niti Aayog officials themselves, the question posed itself in different ways. “The world is certainly looking at AI but does India need it?”, “If yes, what are its unique applications?”, “Are there high impact areas that India could bet on?”…
The meetings and the debates threw up one conclusion: in a country with one in five of the world’s poorest and lagging on healthcare, education, and farming incomes, AI would need to address needs of its teeming masses, the so-called bottom of the pyramid. The #AIforAll strategy is detailed in last week’s Niti Aayog discussion paper on India’s AI strategy .
“The maximum AI deployment has happened in sectors with commercial interest,” said Anna Roy, a 1992-batch officer of the Indian Economic Service who was instrumental in bringing out the paper. “There are sectors where public goods are in prominence, where there are high externalities, where we cannot depend on private motive to deploy AI. The government needs to play a bigger role,” she told FactorDaily in an interview.
Internationally, there is a race between China, the US, and Russia, in AI. It is clear, for instance, that China doesn’t just want to develop AI solutions for itself but also set global standards. International commentators have also noted how the gap between the US and other countries on the defence front is reducing as its rivals adopt AI solutions rapidly.
That the Indian government was serious of AI and other cyber physical technologies was signalled in its economic survey of 2017-18. It mooted a national mission on cyber physical systems as part of half a dozen such missions that would double down on technology and R&D in areas such as dark matter, genomics, energy storage systems, mathematics, and agriculture.
There is a “hugely multidisciplinary area including deep mathematics used in artificial intelligence, machine learning, big data analytics, block chains, expert systems, contextual learning going to integration of all of these with intelligent materials and machines, control systems, sensors and actuators, robotics and smart manufacturing,” the survey noted.
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This was quickly followed by finance minister Arun Jaitley’s announcement in the Union Budget for 2018-19 that Niti Aayog would develop a national programme of artificial intelligence and machine learning. […]
read more – copyright by factordaily.com
Like ruling regimes elsewhere, the Narendra Modi government, too, has seen artificial intelligence as a gamechanger for a while but it started work earnestly on tailoring a strategy around the technology only about a year ago. That was when the government’s policy think tank Niti Aayog called for a meeting, chaired by its CEO Amitabh Kant.
copyright by factordaily.com
The meeting was the start of a journey to understand what AI means for India – could it be meaningful for a country of 1.3 billion people or was it just another flashy technology shining on the hype cycle?
For months after, at several meetings with the academia, government departments and agencies, technology companies, and amongst Niti Aayog officials themselves, the question posed itself in different ways. “The world is certainly looking at AI but does India need it?”, “If yes, what are its unique applications?”, “Are there high impact areas that India could bet on?”…
The meetings and the debates threw up one conclusion: in a country with one in five of the world’s poorest and lagging on healthcare, education, and farming incomes, AI would need to address needs of its teeming masses, the so-called bottom of the pyramid. The #AIforAll strategy is detailed in last week’s Niti Aayog discussion paper on India’s AI strategy .
“The maximum AI deployment has happened in sectors with commercial interest,” said Anna Roy, a 1992-batch officer of the Indian Economic Service who was instrumental in bringing out the paper. “There are sectors where public goods are in prominence, where there are high externalities, where we cannot depend on private motive to deploy AI. The government needs to play a bigger role,” she told FactorDaily in an interview.
Internationally, there is a race between China, the US, and Russia, in AI. It is clear, for instance, that China doesn’t just want to develop AI solutions for itself but also set global standards. International commentators have also noted how the gap between the US and other countries on the defence front is reducing as its rivals adopt AI solutions rapidly.
That the Indian government was serious of AI and other cyber physical technologies was signalled in its economic survey of 2017-18. It mooted a national mission on cyber physical systems as part of half a dozen such missions that would double down on technology and R&D in areas such as dark matter, genomics, energy storage systems, mathematics, and agriculture.
There is a “hugely multidisciplinary area including deep mathematics used in artificial intelligence, machine learning, big data analytics, block chains, expert systems, contextual learning going to integration of all of these with intelligent materials and machines, control systems, sensors and actuators, robotics and smart manufacturing,” the survey noted.
Thank you for reading this post, don't forget to subscribe to our AI NAVIGATOR!
This was quickly followed by finance minister Arun Jaitley’s announcement in the Union Budget for 2018-19 that Niti Aayog would develop a national programme of artificial intelligence and machine learning. […]
read more – copyright by factordaily.com
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