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Science and Technology > IT & Computers > Artificial intelligence
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GS3 > Science and Technology > IT & Computers > Artificial intelligence
REFERENCE NEWS:
In a significant step to encourage artificial intelligence (AI) development in India, the Union Cabinet recently approved the national-level IndiaAI Mission with a budget outlay of Rs.10,371.92 crore.
The IndiaAI Mission seeks to showcase to the international community the positive applications of the revolutionary technology for societal benefit, thereby elevating India's global competitiveness.
KEY COMPONENTS OF THE IndiaAI MISSION
IndiaAI Compute Capacity: Establishing a scalable AI computing ecosystem supported by a substantial GPU infrastructure and an AI marketplace, facilitating AI innovation. The ecosystem will comprise AI compute infrastructure of 10,000 or more Graphics Processing Units (GPUs), built through public-private partnership.
IndiaAI Innovation Centre: Focusing on the development and deployment of indigenous Large Multimodal Models and sector-specific foundational models.
IndiaAI Datasets Platform: Creating a unified platform for easy access to quality non-personal datasets to boost AI innovation.
IndiaAI Application Development Initiative: Promoting the development and adoption of AI applications in critical sectors to drive socio-economic transformation.
IndiaAI FutureSkills: Enhancing AI education and training, particularly in Tier 2 and Tier 3 cities, to broaden the base of AI knowledge and skills across the country.
IndiaAI Startup Financing: Offering financial support to deep-tech AI startups to enable the development of futuristic AI projects.
Safe & Trusted AI: Establishing guidelines and frameworks to ensure the responsible development, deployment, and adoption of AI technologies.
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.
Initially conceived as a technology that could mimic human intelligence, AI has evolved in ways that far exceed its original conception.
INDIA AND AI:
As per NITI Aayog, by 2035, AI has the potential to add 1 trillion dollars to India’s economy
According to the Principal Scientific Advisor (PSA) to the Government of India, AI expenditure in India saw an increase of 109.6% during 2018 to reach US$ 665 million. Moreover, AI expenditure is projected to grow at a CAGR of 39% over the period 2019–2025, reaching around USD 11,781 million by 2025.
Example: BYJU'S uses AI for personalized learning experiences.
SECTOR-WISE APPLICATION IN INDIAN CONTEXT:
Healthcare:
AI addresses access barriers, especially in rural areas with poor connectivity.
Enables AI-driven diagnostics, personalized treatment, early pandemic identification, and imaging diagnostics.
Example: Niramai Health Analytix, an AI-based health tech startup in India, utilises AI for early breast cancer detection.
Agriculture:
AI promises to revolutionize food production and address demand.
Tackles challenges like demand prediction, irrigation issues, and pesticide misuse.Enhances crop yield, pest detection, and crop price prediction.
Example: SatSure, a Bengaluru-based spacetech start-up, leverages satellite imagery and AI for crop yield predictions.
Education:
Enhances learning with personalized education and automates administrative tasks.
Predicts interventions to reduce dropouts and recommend training.
Smart Cities and Infrastructure:
AI integration in smart cities improves quality of life for urban populations.
Improves traffic control and security through crowd management.
Smart Mobility and Transportation:
Includes autonomous ride-sharing fleets, driver assist features, and predictive maintenance.
Example: Surat Smart City employs AI for traffic management and surveillance.
Retail:
AI improves user experience with personalized suggestions and efficient inventory management.
Example: Flipkart utilizes AI for personalized shopping recommendations and inventory management.
Manufacturing:
AI enables adaptable systems for smart decisions in unfamiliar situations.
Impacts R&D, supply chain, production efficiency, maintenance, quality assurance, and logistics.
Example: Tata Steel applies AI for predictive maintenance.
Energy:
AI enhances power balancing and efficiency in renewable energy and grid maintenance.
Banking and Financial Services:
Enhances customer interaction with virtual assistance and chatbots.
Improves back-office operations, credit scoring, fraud prevention, and risk prediction.
Enables robo-advisory and algorithmic trading in wealth management.
Example: Paytm uses AI for fraud detection and enhancing customer service.
GOVERNMENT INITIATIVES:
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.
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.
Sector wise:
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.
Defence:
Center for Artificial Intelligence and Robotics (CAIR) in DRDO conducts research in artificial intelligence
Indian Army already has Wheeled Robot with Passive Suspension, Snake Robot etc.
Agriculture:
NITI Aayog and IBM have partnered to develop a crop yield prediction model using AI to provide real time advisory to farmers.
CHALLENGES:
Limited Expertise: India faces a shortage of skilled AI professionals. For instance, despite growing demand, there's a lack of trained data scientists and AI engineers.
Data Ecosystem: The absence of a robust data ecosystem impedes AI innovation. For instance, without access to diverse and high-quality datasets, developing effective AI models becomes challenging.
Cost Barrier: AI implementation can be costly, hindering adoption, especially for smaller businesses. For example, deploying AI infrastructure and acquiring necessary tools can pose financial challenges.
Privacy Concerns: There are significant concerns regarding data privacy and security, inhibiting AI deployment. Without clear regulations and standards, businesses and users are wary of sharing data.
Collaboration Gap: Effective AI development requires collaboration among stakeholders. However, a lack of collaboration hampers progress. For instance, limited partnerships between government, academia, and industry impede knowledge sharing.
Technical and Ethical Issues: Technical challenges like data quality and ethical considerations such as fairness in AI algorithms need addressing. Without proper guidelines, the trust in AI systems diminishes.
Research Deficiency: India lags in AI research investment and output. For example, compared to other nations, Indian academia and industry invest less in AI R&D, limiting breakthrough innovations.
Intellectual Property Challenges: Weak intellectual property protection discourages AI innovation. For instance, without robust IP laws, companies hesitate to invest in developing new AI solutions.
Narrow Application Focus: AI development in India is often sector-specific, limiting broader societal impact. For example, focusing solely on industries like IT and healthcare neglects opportunities in other sectors.
Commercial Focus Over Welfare: The predominant focus on commercial interests sidelines welfare-driven AI applications. For instance, prioritizing profit-driven AI initiatives over social impact projects neglects marginalized communities' needs.
WAY FORWARD:
A two-tiered structure for promoting AI research:
Centre of Research Excellence (CORE) focused on developing a better understanding of existing core research and pushing technology frontiers through creation of new knowledge
International Centres of Transformational AI (ICTAI) for developing and deploying application-based research. Private sector collaboration is considered to be a key aspect of ICTAIs.
V Kamakoti Committee on Artificial Intelligence: Recommendations::
Set up digital data banks, marketplaces and exchanges to ensure availability of cross-industry information
Data ombudsman: to address data-related issues and grievances.
Ensure availability of funds for R&D
Setting up National Artificial Intelligence Mission (N-AIM)
Government data sharing:
Government of India has large amounts of data lying in silos across ministries.
The government can launch a mission of making all these data available for public good after undertaking proper privacy checks.
For example – climate data, non-strategic remote sensing data, regional language speech (from All India Radio), soil health data etc.
Corporate data sharing:
Corporates based in India may be mandated to share their data for social good.
For example, sharing transportation pattern of individuals/mass transits, collected by service providers and aggregators, can help the city planners help in planning routes, predicting and managing traffic.
PRACTICE QUESTION:
Q. Discuss how India can leverage AI-based technologies for national development.(10 marks, 150 words)
