2020 JUN 17

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  • India has joined the US, UK, European Union (EU) and Australia as one of the founding members of the newly launched Global Partnership on Artificial Intelligence (GPAI).


  • Artificial intelligence (AI) is an inter-disciplinary branch of science concerned with building smart machines capable of performing tasks that typically require human intelligence.
  • The term was coined in 1956 by John McCarthy, who is dubbed as the ‘Father of AI’.
  • In simple terms, AI refers to the ability of machines to perform cognitive tasks like thinking, perceiving, learning, problem solving and decision making. AI makes it possible for machines to learn from experience, adjust to new inputs and perform human-like tasks.



  • Artificial intelligence is based on the principle that human intelligence can be defined in a way that a machine can easily mimic it and execute tasks.
  • AI functions on three basic concepts: machine learning, deep learning, and neural networks.


  • AI is categorized in different ways:
    • Weak AI vs. Strong AI: Weak AI describes "simulated" thinking. That is, a system which appears to behave intelligently, but doesn't have any kind of consciousness about what it's doing. For example, a chatbot might appear to hold a natural conversation, but it has no sense of who it is or why it's talking to you. Strong AI describes "actual" thinking. That is, behaving intelligently, thinking as human does, with a conscious, subjective mind.
    • Narrow AI vs. General AI: Narrow AI describes an AI that is limited to a single task or a set number of tasks. For example, the capabilities of IBM's Deep Blue, were limited to playing chess. General AI describes an AI which can be used to complete a wide range of tasks in a wide range of environments. As such, it is much closer to human intelligence.
    • Superintelligence: The term "superintelligence" is often used to refer to general and strong AI at the point at which it surpasses human intelligence, if it ever does.



  • According to the Artificial Intelligence Readiness Index 2019, released by the International Development Research Centre (IDRC) and Oxford Insights, India stands 19 among 194 countries.



  • Economic impact: AI is emerging as a new factor of production, augmenting the traditional factors of production viz. labor, capital and innovation and technological changes. It is estimated that AI will add $ 957 billion to India’s GDP by the year 2035 boosting India’s annual growth by 1.3%.
  • Next industrial revolution: In 2016, the World Economic Forum called AI “the fourth industrial revolution” that will radically transform the way we live, work, and connect with each other. India, with its large population, labour force and emerging market, will be an active player in this upcoming revolution.
  • Social development and inclusive growth: AI technologies can be custom-made for the unique opportunities and challenges that India faces. Increased access to quality health, inclusive financial growth, providing real-time advisory to farmers and help address unforeseen factors towards increasing productivity, building smart and efficient cities are some of the examples that can be most effectively solved through the use of AI.
  • Garage for 40% of the world: India provides a perfect playground for enterprises to develop scalable solutions which can be easily implemented in the rest of the developing and emerging economies. Simply put, ‘Solve for India’ means solve for 40% or more of the world. For eg: AI technologies suited for the Indian agricultural sector could easily be customised for other developing nations based on their local climatic conditions. 


  • Agriculture: AI holds the promise of driving a food revolution and meeting the increased demand for food. Some use cases include improvement in crop yield through real time advisory, advanced detection of pest attacks, and prediction of crop prices to inform sowing practices. It also has the potential to address challenges such as inadequate demand prediction, inefficient irrigation and irrational use of pesticides and fertilisers.
  • Manufacturing: Manufacturing industry is expected to be one of the biggest beneficiaries of AI based solutions, thus enabling industry 4.0. Impact areas include engineering (AI for research and development), demand forecasting, cost effective production, predictive maintenance and increased asset utilisation, quality assurance and warehousing.
  • Security: AI can become a virtual wall. AI can be used for border control tasks, including border surveillance, detecting cross-border crime patterns, search and rescue, intelligence gathering etc. Several governments have already begun testing AI for better law enforcement, regulate immigrations, spot potentially dangerous travelers and detect smuggling at their borders.
  • Policy making: Indian policy making continues to rely on extrapolating a small amount of data and developing ‘one-size-fits-all’ programs. AI helps in analyzing large volume of data and develop targeted policies, thereby improving the efficiency of policies and use of public resources.
  • Healthcare: Application of AI in healthcare can help address issues of high barriers to access to healthcare facilities, particularly in rural areas.


  • Education and Skilling: AI can potentially solve for quality and access issues observed in the Indian education sector. Potential use cases include enhancing the learning experience through personalised learning, automating and expediting administrative tasks, and predicting the need for student intervention to reduce dropouts.
  • Energy: Potential use cases in the energy sector include energy system modelling and forecasting to increase efficiency in power balancing and reliability. In renewable energy systems, AI can enable storage of energy through intelligent grids enabled by smart meters, and also improve the reliability and affordability of photovoltaic energy.
  • Smart Mobility: Potential use cases in this domain include autonomous fleets for ride sharing, semi-autonomous features such as driver assist, and predictive engine monitoring and maintenance. Other areas that AI can impact include autonomous trucking and delivery, and improved traffic management.
  • Smart Cities: Integration of AI into cities and infrastructure could help meet the demands of a rapidly urbanising population and providing them with enhanced quality of life. Potential use cases include traffic control to reduce congestion and enhanced security through improved crowd management.
  • Retail: The retail sector has been one of the early adopters of AI solutions, with applications such as improving user experience by providing personalised suggestions, preference-based browsing and image-based product search. Other use cases include customer demand anticipation, improved inventory management, and efficient delivery management.


  • Global Partnership on Artificial Intelligence: It is an international initiative to guide the responsible development and use of AI, based on human rights, inclusion, diversity, innovation, and economic growth. Its Secretariat is hosted by the Organization for Economic Cooperation and Development (OECD) in Paris. India is one of its founding members.
  • National Strategy of Artificial Intelligence (NSAI): Through the budget speech for 2018-19, government mandated NITI Aayog to establish the National Program on AI, with a view to guiding the research and development in new and emerging technologies. Hence, it created the NSAI, with the motto #AIforAll. NITI Aayog has decided to focus on five sectors that are envisioned to benefit the most from AI:


  • AIRAWAT: Acronym for ‘Artificial Intelligence Research, Analytics and knoWledge Assimilation plaTform’, it is India’s cloud computing platform being developed by the NITI Aayog as part of the National Strategy of Artificial Intelligence (NSAI).
  • National supercomputing mission: The mission aims to connect national academic and R&D institutions across the country with a grid of more than 70 high-performance computing facilities. It includes developing an indigenously build 100 PF Artificial Intelligence supercomputing system. The mission is being implemented by the Department of Science and Technology and Ministry of Electronics and Information Technology (MeitY), through the Centre for Development of Advanced Computing (C-DAC), Pune and Indian Institute of Science (IISc), Bengaluru.
  • National mission on Cyber Physical System: It is a Rs. 3,660 crore mission that involves development of AI, machine learning, deep learning, big data analytics, quantum computing, quantum communication, quantum encryption, data science and predictive analytics.
  • In education sector:
    • IIT Hyderabad has launched a Bachelor of Technology (B.Tech) program in AI.
    • IIIT Hyderabad has introduced executive programs on AI and machine learning and blockchain and distributed ledger technologies.
    • The CBSE has included AI as an elective subject for its ninth-grade classes.


  • Low public spending: The commercial advancements in AI in recent years have come primarily from the private sector. While the US and Europe enjoy innovation clusters in Silicon Valley, Boston, and London, India, bestowed with none of these resources, must turn to the public funding approaches.
  • Infrastructure deficit: For example, cloud-computing infrastructure, critical for AI systems, largely resides in servers beyond India’s borders. Furthermore, the absence of a large native-install base of on-demand cloud-computing infrastructure in India puts most recent advances in AI out of the reach of government-funded research labs.
  • Shortage of skilled labour: The estimated demand in 2020 would be 4.4 lakh for new-age tech professionals, while the supply is projected to be 2.4 lakh. This shortage will create a major vacuum in projects and industries involved in AI, big data analytics and machine learning. 
  • Potential unemployment: The deployment of AI technologies will reduce the need for low-medium skill labor. For eg: Automation in manufacturing will likely lead Make in India to fall short of its promise of job creation.
  • Lack of quality data: AI relies on available data sets for training and developing models. However, data collection in India is rudimentary, has no established standards and relies on obsolete methodologies. Also, the existing data is biased in favor of the socio-economically advantaged populations. The impact of such data bias in AI can be seriously damaging for India.
  • Privacy concerns: The use of data to allocate resources and monitor people raises significant concerns about civil rights and liberties. While privacy laws call for individual consent to use data, meaningful consent is hard to ascertain in India due to the low levels of education and digital awareness. Moreover, with AI systems, data is used, shared, and made sense of in ways that cannot even be imagined by a normal person.
  • Unclear security and ethical regulations: While AI development is still at a nascent phase, so are understandings of the risks and unknowns around AI. AI systems are deployed across a number of socio-political domains. Hence, the transparency and accountability over them, especially in the absence of proper rules and regulations, becomes a matter of concern.
  • Unattractive Intellectual Property regime: There is a severe backlog and high rate of pendency for domestic patent applications. Given the rapid rate of technological obsolescence, the inordinate delays discourage innovation and innovators.
  • Concentration of power: A few global technology companies have access to a majority of global digital data. This creates data oligopolies, who can potentially influence individual behaviors and preferences, disrupting the workings of governments, markets and communities for their benefits. Whether it’s Facebook targeting its users or Cambridge Analytica manipulating elections, these examples show how the interests of those deploying advanced data systems can overshadow public interest.


  • Policy support: For India to maximally benefit from the AI revolution, it must adopt a deliberate policy to drive AI innovation, adaptation, and proliferation in sectors beyond consumer goods and information technology services. The policy, while encouraging AI growth, should also embrace smart regulations to ensure responsible AI.
  • Targeted approach: The government should identify public sector applications like detecting tax fraud, preventing subsidy leakage, and targeting beneficiaries, where current advances in AI could make a significant impact.
  • Capacity building at grassroot stage: The National Education Policy must make radical recommendations on alternative models of education that would be better suited to an AI-powered economy of the future. The government must also take measures to reskill the existing workforce so that they can coexist with the AI driven industries.
  • Infrastructure development: A major push for development of indigenous IT infrastructure, with emphasis of data localization is necessary for the development of AI in India. For this, the government should prospect private cooperation in the form of PPP or hybrid annuity models.
  • Develop Strategic objectives: India must view machine intelligence as a critical element of its national security strategy and evaluate models of defense research in collaboration with the private sector and universities.
  • AI is the future that India can ill-afford to ignore to solve some of the most intractable problems of its people. Fortunately, it has potential in its labour force, academic institutions and geopolitical status. If recognised and used correctly, India can become a leader in AI development.


Microsoft in collaboration with ICRISAT, developed an AI Sowing App, which sends sowing advisories to participating farmers on the optimal date to sow. The farmers don’t need to install any sensors in their fields or incur any capital expenditure. All they needed was a feature phone capable of receiving text messages. The advisories contained essential information including the optimal sowing date, soil test-based fertilizer application, farm yard manure application, seed treatment, optimum sowing depth, and more. In 2017, the program was expanded to touch more than 3,000 farmers across the states of Andhra Pradesh and Karnataka during the Kharif cycle for a host of crops including groundnut, ragi, maize, rice and cotton, among others. The increase in yield ranged from 10% to 30% across crops.


Q. ‘Artificial Intelligence is the future that India can ill-afford to ignore’. In this light, discuss the potential applications of AI in Indian context. What measures have the government taken to realise these?