You can bring bullet trains from Japan, but not Artificial Intelligence

Two ministries want to ride the AI wave. Do we know how much data are we individually fuelling into it? Algorithms read, use, and most alarmingly, assess our levels of stupidity (and vulnerability). Especially on apps like WhatsApp

Ministries of Commerce and Electronics and IT are claiming to build India’s roadmap for AI development in ways which look fuzzy now. This, at a time when countries are embarking on well-thought plans

Recent calls on big data and cyber-physical systems have been damp squibs. Will AI be better given that less than 40 academics in India are doing serious AI research or have the ‘the dark art’ to solve deep learning problems?

Developing AI is a completely different ball game as compared to developing space, power or train tech. Algorithms need to train on Indian data. And who has data today?

It’s with big tech companies which are collecting and connecting data, even influencing behaviour in ways that we hardly understand

No books, no human intervention, no training data and yet it learns, from first principles. Google-owned DeepMind showed last week that its artificial intelligence (AI) programme Alpha Go Zero was able to learn what knowledge was from itself. That’s spooky. Comparisons of AI to the invention of the steam engine or printing press for impact on humans now seem understated.

Even though a lot of AI expertise resides in the top 10-12 tech companies, governments are waking up to it as if it were an arms race.

AUTHOR

Seema Singh

Seema has over two decades of experience in journalism. Before starting The Ken, Seema wrote “Myth Breaker: Kiran Mazumdar-Shaw and the Story of Indian Biotech”, published by HarperCollins in May 2016. Prior to that, she was a senior editor and bureau chief for Bangalore with Forbes India, and before that she wrote for Mint. Seema has written for numerous international publications like IEEE-Spectrum, New Scientist, Cell and Newsweek. Seema is a Knight Science Journalism Fellow from the Massachusetts Institute of Technology and a MacArthur Foundation Research Grantee.

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