Highlighting how AI can be effectively used in execution of government schemes, the report said that deep learning a part of AI can be employed to tackle issues of scale often prevalent in such schemes.
India should take lead in establishing a legal infrastructure on the application of artificial intelligence (AI) to become a frontrunner, suggested a recent ASSOCHAM-PwC joint study titled, ‘Leveraging artificial intelligence and robotics for sustainable growth.’ The jointly conducted study by ASSOCHAM-PwC highlighted how an early public sector interest could trigger a spurt of activity in the AI field in India, instead of waiting for technology to reach a level where regulatory intervention becomes necessary.
It also said that a range of application for AI techniques in large-scale public endeavours like Make in India, Skill India and others could range from crop insurance schemes, tax fraud detection, and detecting subsidy leakage and defence and security strategy. “If investments are made in the two initiatives without due cognisance of how Industry 4.0 (the next industrial revolution driven by robotic automation) may evolve with respect to demand for workforce size and skill sets, there is a possibility of ending up with capital-intensive infrastructures and assets that fall short of being optimised for automated operations and a large workforce skilled in areas growing beyond the need for manual intervention only,” it added.
The report stated that Make in India initiative which focuses on twin goals of strengthening country’s in-house innovation and production capabilities with added creation of employment opportunities may not end up creating nearly as many jobs as it is poised to at this point in time. Information technology (IT), manufacturing, agriculture and forestry are certain sectors that are expected to experience shrinkage of employment demand as robotic systems and machine learning algorithms take up several tasks, the report said.
Highlighting how AI can be effectively used in execution of government schemes, the report said that ‘deep learning,’ a part of AI, can be employed to tackle issues of scale often prevalent in such schemes. “It is essentially a process that can be used for pattern recognition, image analysis and natural language processing (NLP) by modelling high-level abstractions in data which can then be compared with various other recognised contents in a conceptual way rather than using just a rule-based method,” it said.
The study further said that in comparison to the West and frontrunners of AI adoption in Asia, such as China and Korea, the culture and infrastructure needed to develop a base for the adoption of AI in mainstream applications in India is in need of an impetus. Indian academics, researchers and entrepreneurs face a more acute challenge than corporates do in terms of the less than ideal infrastructure available for an AI revolution in India.
As such it is imperative in India to foster a culture of innovation and research beyond the organisation as is common in global technology giants. “To encourage the same level of innovation in AI research efforts in India, initiatives to hold events and build user communities in the field of AI will go a long way.”
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