National Strategy for Artificial Intelligence: NITI Aayog

National Strategy for Artificial Intelligence: NITI Aayog

National Strategy for Artificial Intelligence: NITI Aayog

What is Artificial Intelligence (AI)?

  • AI refers to the ability of machines to perform cognitive tasks like thinking, perceiving, learning, problem solving and decision making.  
  • It is a constellation of technologies that enable machines to act with higher levels of intelligence and emulate the human capabilities of sense, comprehend and act. Thus, computer vision and audio processing can actively perceive the world around them by acquiring and processing images, sound and speech

Global Developments in Artificial Intelligence

  • Countries around the world are becoming increasingly aware of the potential economic and social benefits of developing and applying AI. For example, China and U.K. estimate that 26% and 10% of their GDPs respectively in 2030 will be sourced from AI-related activities and businesses.
  • Infrastructural supply side interventions have been planned by various countries for creating a larger ecosystem of AI development.
    •  Creation of “data trusts”, rolling out of digital connectivity infrastructure such as 5G / full fiber networks, common supercomputing facilities, fiscal incentives etc. are some of the focus areas of various governments.
  • For building the future workforce for AI, countries are also significantly increasing the allocation of resources for Science, Technology, Engineering and Maths (STEM) talent development through investment in universities, mandating new courses (e.g., AI and law), and offering schemes to retrain people.
  • National governments have significantly increased public funding for AI through increasing the R&D spend, setting up industrial and investment funds in AI startups, investing in network , infrastructure & AI-related public procurements.

Artificial Intelligence and India

A national AI strategy needs to be premised on a framework which is adapted to India’s unique needs and aspirations, while at the same time, is capable of achieving the country’s full potential of leveraging AI developments. Such a framework could be seen as an aggregation of the following 3 distinct, yet inter-related components:

1. Opportunity: the economic impact of Artificial Intelligence for India

AI has the potential to drive growth through enabling:

  1. Intelligent automation i.e. ability to automate complex physical world tasks that require adaptability and agility across industries
  2. Labour & capital augmentation: Enabling humans to focus on parts of their role that add the most value, complementing human capabilities and improving capital efficiency, and
  3. Innovation diffusion i.e. propelling innovations as it diffuses through the economy. AI innovations in one sector will have positive consequences in another, as industry sectors are interdependent based on value chain. Economic value is expected to be created from the new goods, services and innovations that AI will enable

2. AI for Greater Good: Social development & Inclusive growth

A disruptive technology such as AI needs to be seen from the perspective of the transformative impact it could have on the greater good – improving the quality of life and access of choice to a large section of the country. The recent advancements in AI need to be custom-made for the unique opportunities and challenges that India faces.

  1. Healthcare: Application of AI can help address issues of high barriers to access to healthcare facilities, particularly in rural areas through implementation of use cases such as AI driven diagnostics, personalized treatment, early identification of potential pandemics, and imaging diagnostics, among others.
  2. Agriculture: AI can address challenges such as inadequate demand prediction, lack of assured irrigation, and overuse / misuse of pesticides & fertilisers. 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.
  3. Smart Mobility, including Transports and Logistics: Potential use cases in this domain include autonomous fleets for ride sharing, semi-autonomous features such as driver assist, and predictive engine monitoring & maintenance, autonomous trucking & delivery, and improved traffic management.
  4. Retail: AI can improve user experience by providing personalized suggestions, preference-based browsing and image-based product search.
  5. Manufacturing: AI can enable 'Factory of the Future' through flexible and adaptable technical systems to automate processes & machinery to respond to unfamiliar or unexpected situations by making smart decisions.
  6. Energy: Potential use cases include energy system modelling & forecasting to decrease unpredictability and increase efficiency in power balancing and usage. In renewable energy systems, AI can enable storage of energy through intelligent grids enabled by smart meters, and also improve the reliability & affordability of photovoltaic energy.
  7. Education and Skilling: Potential use cases include augmenting and enhancing the learning experience through personalised learning, automating and expediting administrative tasks, and predicting the need for student intervention to reduce dropouts or recommend vocational training.

Key challenges to adoption of AI in India

Analyzing across the focus sectors, the challenges are concentrated across common themes of:

  1. Legal personality of AI: First we need a legal definition of AI. Given the importance of intention in India’s criminal law jurisprudence, it is essential to establish the legal personality of AI (which means AI will have a bundle of rights and obligations), and whether any sort of intention can be attributed to it.
    • Since AI is considered to be inanimate, a strict liability scheme that holds the producer or manufacturer of the product liable for harm, regardless of the fault, might be an approach to consider.
    • Since privacy is a fundamental right, certain rules to regulate the usage of data possessed by an AI entity should be framed as part of the Personal Data Protection Bill, 2018.
  2. Lack of enabling data ecosystems: Datasets that are relevant for AI applications to learn are indeed rare. The most powerful AI machines are the ones that are trained on supervised learning. This training requires labeled data – data that is organised to make it ingestible for machines to learn
  3. Low intensity of AI research
    • Core research in fundamental technologies
    •  Transforming core research into market applications
  4. Inadequate availability of AI expertise, manpower and skilling opportunities
  5. High resource cost and low awareness for adopting AI in business processes
  6. Unclear privacy, security and ethical regulations: 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. This makes it vulnerable to serious issues like data breach and identity theft.
  7. Unattractive Intellectual Property regime to incentivise research and adoption of AI

Way Forward for India

India has a unique opportunity at this moment. Using the talent available within the country, it can repeat the success story of IT industry. At the same time, if necessary steps are not taken in time, it will lose the opportunity. AI  can  help in the major programmes  of  the  Government viz. Digital India, Make in India, and Skill India.

Recommendations:

  1. Applications and Infrastructure Development: The government must create  infrastructure  to  support  development  of AI applications. 
    1. One critical infrastructure is cloud which is needed for the development of applications. AI applications require  high  computational  power,  large  memory  and  storage  space  which  are  available  on  the cloud
    2. High speed network is another requirement necessary for development of AI applications. This is essential to collect and share large amount of data.
  2. Regulations and Policy: As AI applications touch several aspects of human life, regulations are needed to ensure safety of the people, protection of privacy, etc
    • Regulations need to be made to ensure that the applications developed are not biased towards a specific view. The biasing may be intentional when it is incorporated by the developer of the application.
    • Policy is needed for making the results of R&D available to the public. Several R&D projects are funded by the Government in the country but often the results remain confined to a limited number of persons.
    • As a policy, Government should also work on making people aware about this technology. This is necessary if  we want to create  confidence  in the people for  using AI-based applications
  3. Research and Development: Most of  the developed and several developing countries are investing heavily in R&D and innovation in the area of artificial intelligence. India needs to initiate a Programme to support R&D and innovation in this area
    • Involvement of industry is necessary while funding R&D projects. The companies need to be persuaded to form a consortium and so that a common fund could be made available to support the  projects  at  the  R&D  centres / academic institutions
  4. Human Resource Development: In order to cope up with the problems due to the loss of jobs, the workforce will have to be retrained to take up new types of jobs which may emerge with the automation of the processes.
    • There is a need to attract bright students to do research in the area of AI. Doctoral and Post-doctoral fellowships should be instituted and made available to the people interested in research in the area of AI.
    • The universities and technical education institutions need to be  supported  by  the  Government  for initiation of these programmes.

 

References: Niti Aayog Report, Forbes India Report, Reasearch Gate, The Hindu, Indian Express

Image Source

Source: Niti Aayog Report