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Context: Artificial Intelligence and its prospects.

AI refers to the ability of machines to perform cognitive tasks like thinking, perceiving, learning, problem solving and decision making. Initially conceived as a technology that could mimic human intelligence, AI has evolved in ways that far exceed its original conception. With incredible advances made in data collection, processing and computation power, intelligent systems can now be deployed to take over a variety of tasks, enable connectivity and enhance productivity.

How the artificial intelligence can transform Indian society/economy:

  • Economic impact: AI has the potential to drive growth through enabling: (a) intelligent automation i.e. ability to automate complex physical world tasks that require adaptability and agility across industries, (b) labor and capital augmentation: enabling humans to focus on parts of their role that add the most value, complementing human capabilities and improving capital efficiency, and (c) innovation diffusion i.e. propelling innovations as it diffuses through the economy. Accenture, in its recent AI research reports provides a framework for evaluating the economic impact of AI and estimates AI to boost India’s annual growth rate by 1.3 percentage points by 2035.
  • Health care: The Government of India, through its recent policy interventions, has shown a bold commitment to achieve Universal Health Coverage and increased access to comprehensive primary health care. Through the Ayushman Bharat programme announced in Union Budget 2018, probably the world’s largest government funded health care programme, the Government of India has embarked on a path breaking journey to ensure the affordability and accessibility of healthcare in India. Artificial intelligence can be used to solve lot of problems like data collection. using Artificial Intelligence to analyze the data it will help to gather the data that falls under the particular criteria in certain period of time which will be far more less than what would be time taken by human power.
  • Manufacturing: Under the Make in India initiative, the government aims to increase the share of GDP from the manufacturing sector to 25% by 2022. This will only be possible if timely and effective interventions by the government are implemented to foster growth of the manufacturing industry through promotion of technology.  Artificial Intelligence will be the key determining factor that will decide the survival of manufacturing SMEs in an increasingly competitive scenario. Not adopting this futuristic technology will keep costs elevated, inefficiencies in production and ultimately make operations unviable via-a-vis competition. The future is likely to lead to a sharp divide between the AI-enabled and the not AI-enabled manufacturing SMEs.
  • Education: In India, the importance of a developed education sector is amplified by a large youth population. Estimates indicate that currently over half the population of the country is below the age of 25. As the adoption of digital means of gathering data increases, it is important that these methods are effectively leveraged to deliver improved education and teaching. The adoption of technology in education is improving, though not at the pace required. It is estimated that schools globally spent nearly USD160 billion on education technology, or ‘EdTech’, in 2016, and forecast spending to grow 17% annually through 2020. Private investment in educational technology, broadly defined as the use of computers or other technology to enhance teaching grew 32% annually from 2011 through 2015, rising to USD4.5 billion globally.
  • Skills: A study by EY and Nasscom predicts that by 2022, around 46% of the workforce will be engaged in entirely new jobs that do not exist today, or will be deployed in jobs that have radically-changed skill sets. An Ernst & Young study states that there are 17 million new entrants into the Indian workforce year after year. With half of the country’s population below the age of 25, a pertinent step would be to prepare the young workforce by exposing them to the tech-enabled future of work with AI interfaces, machine learning, and increased automation. Online training programs, inclusion of AI and automation in the existing education curriculum, and corporate training programs for new hires can achieve this without much structural change and investment.
  • Agriculture: India has not been able to completely remove its exploitative dependence on resource intensive agricultural practices. Degradation of land, reduction in soil fertility, increased dependence on inorganic fertilizers for higher production, rapidly dropping water tables and emerging pest resistance are some of the several manifestations of India’s unsustainable agricultural practices. As global climate becomes more vulnerable and unpredictable, dependence on unsustainable and resource intensive agriculture will only heighten the risks of food scarcity and agricultural distress. An Accenture study says – digital farming and connected farm services can impact 70 million Indian farmers in 2020, adding USD9 billion to farmer incomes. AI will have significant global impact on agricultural productivity at all levels of the value chain.

Issues and challenges related to artificial intelligence:

  • Employment problems: India is no exception to the global AI wave, which is beginning to uproot workers from their jobs. A recent study by McKinsey and Company 2014 estimates that 6-8 million workers “currently employed in routine clerical, customer service, and sales jobs could be affected by advancements in machine learning and natural language interfaces (speech recognition).” A loss of jobs at this scale can have an impact on economic well-being for a large number of people, who may be dependent on these wage-earners, an important consequence for a middle-income country trying to raise a large number of citizens out of poverty.
  • Social discrimination: Much recent research shows that applications based on machine-learning reflect existing social biases and prejudice. Such bias can occur if the data-set the algorithm is trained on is unrepresentative of the reality it seeks to represent. If for example, a system is trained on photos of people that are predominantly white, it will have a harder time recognizing non-white people. This is what led a recent Google application to tag black people as gorillas. The impact of such data bias can be seriously damaging in India, particularly at a time of growing social fragmentation. It can contribute to the entrenchment of social bias and discriminatory practices, while rendering both invisible and pervasive the processes through which discrimination occurs.
  •  Gender inequality: women are 34 per cent less likely to own a mobile phone than men – manifested in only 14 per cent of women in rural India own a mobile phone, while only 30 per cent of India’s internet users are women. Women’s participation in the labor force, currently at around 27 per cent, is also declining, and is one of the lowest in South Asia. Data sets used for machine learning are thus likely to have a marked gender bias. The same observations are likely to hold true for other marginalized groups as well.
  • Research issues: India produced a whopping 2.6 million STEM graduates in 2016, second only to China and more than 4 times the graduates produced by USA, Disappointingly though, an overwhelming majority of this talent pool is focused on routine IT development and not so much on research and innovation. Exacerbating the problem further, a majority of the small population focused on research almost always prefers to pursue advance degrees (Masters or PhD degrees) to subsequently apply their expertise abroad.

Measures to be taken by the government:

  • Research competence: according to NITI Aayog vision document “national strategy for artificial intelligence” proposed a two-tier integrated approach to boost both core and applied research-
    • COREs (Centers of Research Excellence in Artificial Intelligence): COREs will focus on core research of AI, and will take on the mantle of executing the responsibilities of both ICON and CROSS as per the IM-ICPS framework. Thus, COREs will specialize in creating new knowledge through basic research and will source for fundamental knowledge / technologies that will be needed to keep India prepared for the next generation of technologies.
    • ICTAI (International Centre for Transformational Artificial Intelligence): ICTAIs will provide the ecosystem for application based technology development and deployment; This will be an industry-led initiative and expected to take on the top-level challenges identified or inter ministerial projects calling for AI based solutions.
  • Skilling: Re-skilling of the current workforce will require integration with relevant existing skilling initiatives, building of new platforms that can enable improved learning, and novel methods of allowing large scale employment generation through promotion of AI. To promote the skills of unskilled following measures to be taken:
    • Incentivizing creation of jobs that could constitute the new service industry.
    • Recognition and standardization of informal training institution
  • Adoption: Adoption of AI in India has been slow and remains limited. Estimates indicate that only 22% of the firms in India use AI in any business process. So To encourage the development of sustainable AI solutions at an appropriate price point for sectors such as health, education, and agriculture, it is necessary that a level playing field be ensured and a supportive environment be created for all players in the value chain. The development of any working AI-based product is a long process with very different specialized activities that are necessary for final delivery, just like any other product or service value chain.
  • Privacy: Most AI applications rely on huge volumes of data to learn and make intelligent decisions. Machine Learning systems feast on data – often sensitive and personal in nature – to learn from them and enhance themselves. This makes it vulnerable to serious issues like data breach and identity theft. So the government should implement the Srikrishna commission recommendations strictly.

Way forward: India, being the fastest growing economy with the second largest population in the world, has a significant stake in the AI revolution. Artificial Intelligence (AI) is poised to disrupt our world. With intelligent machines enabling high-level cognitive processes like thinking, perceiving, learning, problem solving and decision making, coupled with advances in data collection and aggregation, analytics and computer processing power, AI presents opportunities to complement and supplement human intelligence and enrich the way people live and work.

Source: https://www.business-standard.com/article/opinion/ai-policy-needs-coordinated-intelligence-119071001489_1.html.