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RSTV: THE BIG PICTURE- RESPONSIBLE AI FOR SOCIAL EMPOWERMENT

RSTV


Introduction:

This century has seen transformational growth in technology. Technology over the last few decades has been rapidly evolving changing the way we think, work and live. When we talk of technology today, the focus is largely on artificial intelligence. Governments and organizations around the world are investing in and focusing heavily on AI. The pandemic has led the world to focus on new solutions for several problems through AI

Opportunities for India:

  • India, with its “AI for All” strategy, a vast pool of AI-trained workforce and an emerging startup ecosystem, has a unique opportunity to be a major contributor to AI-driven solutions.
  • AI-driven solutions can revolutionise healthcare, agriculture, manufacturing, education and skilling.
  • India has a large young population that is skilled and eager to adopt AI.
  • The country has been ranked second on the Stanford AI Vibrancy Index primarily on account of its large AI-trained workforce.
  • Our leading technology institutes like the IITs, IIITs and NITs have the potential to be the cradle of AI researchers and startups.
  • By building AI solutions at scale, India can become a trusted nation to which the world can outsource AI-related work.

Artificial intelligence can help transform Indian healthcare:

  • With a surge in non-communicable diseases and the increasing number of aging population in the country, the overall burden of disease management has been increasing year-on-year and to manage that, the government, the healthcare professionals and the healthcare institutions are looking for innovative ways.
  • Studies have shown that deep learning algorithms have given better insights to clinicians in predicting prognosis and future events in patients.
  • Advanced digital technologies like AI and ML can help in prevention as well as early detection of diseases by capturing and analysing various vitals of patients.
  • Artificial intelligence makes it possible to access the learning and data from hundreds of thousands of patient cases.

AI for agriculture:

  • Weather prediction: Agriculture across the world is dependent on climate, and so the use of AI for predicting the weather is the most obvious use case. There are multiple such initiatives across countries to predict weather both at a government level as well as by enterprises link IBM and Google.
  • Crop Monitoring using Image processing: Whether we use a satellite, a drone, or a robot to take images, there are cases where image processing is being used to assess the crop. This includes real-time crop vegetation index monitoring from satellite images, monitoring for pests, for yield size, yield prediction, soil assessment and a host of other use cases.
  • Smart Irrigation: Irrigation is one of the most labour intensive processes in farming which can be avoided by artificial intelligence because it is aware of historical weather pattern, soil quality and kind of crops to be grown. Automated irrigation systems are designed to utilize reaI time machine which can constantly maintain desired soil conditions in order to increase average yields.
  • Monitoring Soil Health: Conducting or monitoring identifies possible defects and nutrient deficiencies in the soil can be efficiently done by utilizing Al. With the image
  • Harvesting robots: There are various robots being built for harvesting yield..
  • Driverless tractors: The unavailability of farm labour has led to multiple companies across the world, introducing self-driving tractors. Mahindra and Mahindra Ltd, India’s largest manufacturer of tractors, showcased its first driverless tractor in Sept 2019.

AI and Smart Mobility:

  • Intelligent Transport Systems: With the help of AI real-time dynamic decisions on traffic flows such as lane monitoring, access to exits, toll pricing, allocating right of way to public transport vehicles, enforcing traffic regulations through smart ticketing etc. can be made. Accident heat maps could be generated using accident data and driver behaviour at specific locations on the road network.
  • Autonomous Trucking: AI can help in road safety and give the driver rest from the long hours of driving. With AI, optimal road-space utilisation which will help improve road infrastructure capacity.
  • Travel flow optimisation: With access to traffic data at the network level, AI can help make smart predictions for public transport journeys by optimising total journey time, including access time, waiting time and travel time.
  • Railways and AI: according to official statistics, more than 500 trains were involved in accidents between the years 2012-2017, 53% of them were due to derailment. Govt. of India has decided to use AI to undertake remote condition monitoring. The Govt. is using non-intrusive sensors for monitoring signals, track circuits, axle counters.
  • Community-Based Parking: AI will be needed to mediate the complex vehicle grid interaction (VGI) as well as charging optimisation. Parking guiding systems help drivers to find vacant parking spots while they are using the road and are near their destination.

Lack of R&D on AI in India:

  • Both the government and companies are largely focused on AI applications, not research and development (R&D).
  • And even in applications, much of the work is at the mid and lower ends of the spectrum.
  • India is not in the top 10 nations when it comes to AI research.
  • According to experts, currently, the race is really between the US, China and the EU, with the US in a slender lead. India has not even entered the race yet.
  • We are in danger of being on the wrong side of the techno-colonialism, just as we did in the last three general purpose technology (GPT) revolutions that divided the countries around the world into the haves and the have-nots.
  • Techno-colonialism describes the situation where the country or countries that control a technology exploit other, poorer countries that depend on access to that technology.
  • In the US, the close collaboration between academia and corporations has ensured enough money for research which would pay off decades into the future.
  • The US government’s Defense Advanced Research Projects Agency also got into AI research early.
  • China started much later but has invested big money to play catch-up.
  • In India, neither the government nor the industry has focused much on research compared to US and China.
  • In India we need to formulate a long-term plan just as we do for other infrastructure plans.
  • It will mean squeezing expenditure elsewhere to find money for R&D and also giving incentives to attract research talent and getting the biggest corporations involved.
  • For this the government must take a long-term view.
  • Unless we start now, we will forever remain a dependent rather than a leader in the technology stakes.

Way Forward:

  • It remains our collective responsibility to ensure trust in how AI is used. Algorithm transparency is key to establishing this trust.
  • We must protect the world against weaponisation of AI by non-state actors.
  • Riding on data and AI, India can achieve the bold vision of becoming a US$5 trillion economy by 2025.
  • To achieve this, AI needs to be extensively utilized in all sectors ranging from agriculture, MSMEs, financial services, healthcare to energy and logistics to create a vibrant AI economy.