INTRODUCTION

India is rapidly emerging as a key player in the global AI landscape, with its vast talent pool and growing adoption of AI-driven solutions across industries. Strategic investments in research, open-source initiatives, and policy support are crucial to positioning India as a leader in AI innovation.

Artificial Intelligence (AI): Overview & Key Concepts

• Definition of AI

• AI is the capability of machines (especially computers) to perform tasks requiring human intelligence which include language understanding, pattern recognition, problem-solving, and decision-making.

• AI systems can learn from experience and process large amounts of data rapidly.

• Types of AI

Capability-Based Types

• Artificial Narrow Intelligence (ANI) / Weak AI: Specialised for specific tasks (e.g., virtual assistants like Siri, recommendation systems) and cannot generalise beyond its programmed domain.

• Artificial General Intelligence (AGI) / Strong AI: Hypothetical AI that possesses the ability to understand, learn, and apply knowledge across a wide range of tasks, similar to human intelligence.

• Superintelligent AI: AI that surpasses human intelligence in all aspects, including problem-solving, creativity, and social intelligence.

Functionality-Based Types

• Reactive Machines: AI systems that react to specific stimuli with pre-programmed responses, without the ability to store or learn from past experiences (e.g., Deep Blue chess computer).

• Limited Memory AI: AI that uses past experiences and data to make decisions and improve performance over time (e.g., self-driving cars).

• Theory of Mind AI: Advanced AI that would understand emotions, beliefs, intentions, and other human-like aspects, enabling it to interact in a more empathetic manner.

• Self-Aware AI: A theoretical form of AI that has consciousness and can understand its own existence and purpose.

• AI Subsets: Specialised fields within artificial intelligence that focus on specific methods or approaches to achieving machine intelligence.

• Machine Learning (ML)

• Uses algorithms to learn from data and make predictions.

• Requires manual feature extraction for training models.

• Example: Fraud detection in banking.

• Deep Learning (DL) (Subset of ML)

• Uses multi-layered neural networks to automatically extract features from data.

• Requires large datasets and high computational power.

• Example: Facial recognition, self-driving cars.

AI continues to evolve and integrate into various fields, shaping the future of technology and human interaction.

Timeline of evolution of AI in India

• Early Days (1960s-1980s):

• Indian institutes like IIT Kanpur and IISc Bangalore laid the groundwork for AI research.

• In 1986, the Knowledge Based Computer Systems (KBCS) project marked India's first major AI research initiative.

• Foundations (1990s):

• The establishment of C-DAC in 1988 boosted supercomputing capabilities, indirectly supporting AI research.

• Indian software companies began exploring AI for business process automation.

• Growth Phase (2000s):

• Indian IT giants like TCS, Infosys, and Wipro invested in AI research and development.

• Academic institutions expanded their AI and machine learning programs.

• Acceleration (2010s):

• The "Digital India" initiative launched in 2014-15 emphasized emerging technologies, including AI.

• In 2018, NITI Aayog released the National Strategy for Artificial Intelligence.

• AI-focused startups emerged and attracted significant funding.

• Current Era (2020s):

• AI has become central to both government and private sector initiatives.

• India is positioning itself as a global AI hub, with applications in healthcare, agriculture, and smart cities.

• The government launched initiatives like "AI for All," integrating AI into sectors like education and governance.

Importance of AI

• Automation and Efficiency: AI-powered systems automate repetitive and labour-intensive tasks, increasing productivity and reducing human errors across industries like manufacturing, logistics, and customer service.

• Example: The Union Ministry of Agriculture & Farmers Welfare has launched an AI Chatbot for the PM-KISAN scheme, providing multilingual support and real-time responses to farmers' queries, with plans to expand its availability to all 22 Indian languages.

• Enhanced Decision-Making: AI analyses vast amounts of data to provide real-time insights, enabling businesses, judiciary, governments, and researchers to make more informed and precise decisions.

• Example: In December 2023, the Manipur High Court used ChatGPT to clarify that the Village Defence Force (VDF) comprises local volunteers trained to guard villages against threats like insurgency. This information was key in the court’s ruling to set aside Zakir Hussain's dismissal from VDF due to procedural flaws.

• Healthcare Advancements: AI assists in early disease detection, personalised treatment plans, robotic surgeries, and drug discovery, improving patient outcomes and reducing healthcare costs.

• Example: AI-powered Microsoft HoloLens, introduced at Peerless Hospital in Kolkata, enhances precision in knee and joint-replacement surgeries by providing surgeons with a 3D holographic view of the entire limb, reducing human error and offering personalized alignment for implants.

• Economic Growth and Job Creation: AI drives innovation by enabling new business models, increasing efficiency in industries, and creating demand for AI-related skills and services.

• Example: A study by ServiceNow, in collaboration with Pearson, has projected that AI could actually drive employment growth, creating an estimated 2.73 million jobs in India by 2028.

• Security and Cybersecurity: AI enhances threat detection, fraud prevention, and real-time monitoring, strengthening defence mechanisms in financial transactions, national security, and digital platforms.

• Example: MuleHunter.AI is an AI-powered tool developed by the Reserve Bank Innovation Hub to efficiently detect and eliminate mule accounts involved in money laundering and cybercrimes by analyzing account activity patterns.

• Scientific Research and Innovation: AI accelerates research by processing complex datasets in fields like genomics, astronomy, physics, and material science, leading to groundbreaking discoveries.

• Example: Indian scientists have developed a machine learning-based approach to predict Earth's crust movements over the Tibetan Plateau, offering a cost-effective and accurate alternative to traditional GPS-based methods.

• Environmental Sustainability: AI optimises energy consumption, improves climate predictions, and enhances resource management in industries like agriculture, water conservation, and renewable energy.

• Example: The National Remote Sensing Centre (NRSC), a programme under the auspices of the Indian Space Research Organization (ISRO), has engineered a new AI enabled monitoring system to observe forest cover change and combat deforestation.

• Disaster Prediction and Management: AI improves early warning systems for natural disasters, enhances crisis response, and optimises resource allocation in relief operations.

• Example: Climate Software Lab (CSL) has launched an AI-based Landslide Risk Assessment model to map landslide risks in vulnerable areas of the Indian subcontinent, impacting around 40 lakh people.

• Education and Skill Development:AI enhances learning through personalised education, automated assessments, intelligent tutoring systems, and adaptive learning platforms, making education more efficient and accessible.

• Example: Medha AI, India's first teacher-assistive AI developed by Cograd, is revolutionising education in rural areas of Uttarakhand by providing offline support for lesson planning, content delivery, and student assessment.

• Improved Accessibility and Inclusivity: AI-powered assistive technologies help individuals with disabilities by enabling speech-to-text, real-time translations, and personalised learning tools.

• Example: IIT-Hyderabad has developed "Swarajability," an AI-based job platform for people with disabilities, to help them access tech sector opportunities, with support from Kotak Mahindra Bank, Visual Quest India, and Youth4Jobs.

Global Initiatives

• UN AI Governance Initiatives

• The UN has been working on a strategic AI roadmap since 2019, focusing on ethical AI principles and capacity development.

• The 2023 High-Level Committee on Programmes and Management joint session, hosted by UNICEF, reinforced AI governance discussions.

• Global Initiative on AI for Health (GI-AI4H): 

• Launched in July 2023, under WHO, ITU, and the World Intellectual Property Organization (WIPO), the GI-AI4H stands as a resilient, long-term institutional structure, grounded in its mission to enable, facilitate, and implement AI in healthcare.

• US 

• Stargate initiative: The US launched the initiative, committing billions to semiconductor investments.

• The goal: Create 100,000 jobs and secure the US’s position as a leader in AI technology.

• OpenAI's ChatGPT: Based in the US, OpenAI, led by Sam Altman, emerged as a strong competitor with its advanced GPT models, including GPT-4 Turbo.

• China

• Chinese AI startup DeepSeek developed an open-source AI model in under two years with minimal capital.

• Compared to OpenAI’s $6.6 billion funding and 4,500 employees, DeepSeek accomplished much with only 200 employees and less than $10 million.

• France

• Mistral, a leading French AI startup, has launched Le Chat, an AI chatbot app for iOS and Android, offering conversational AI-generated responses. 

Indian Initiatives

• IndiaAI Mission

• The IndiaAI Mission aims to develop a domestic large language model focusing on Indian languages, culture, and context, ensuring bias-free technology and technological self-reliance. 

• The mission will also reduce overdependence on foreign AI models.

• The government is funding 18 AI solutions focused on agriculture, learning disabilities, and climate change

• AI for India 2.0 : 

• Aims to equip youth with frontier skills in Artificial Intelligence. 

• A joint initiative of Skill India and GUVI, this IIT Madras-accredited online course is offered in 9 Indian languages to break language barriers in technology education, particularly in rural areas.

• Niramai: A health-tech startup, uses AI to detect early signs of breast cancer, contributing to healthcare innovations.

• BHASHINI: An AI initiative, supports 22+ languages to promote inclusivity and has powered over 100 million inferences, demonstrating its broad application and reliability.

• AI4Bharat: A research lab at IIT Madras, advances AI for Indian languages through open-source contributions, developing state-of-the-art models in transliteration, translation, and speech processing

• BhasaAnuvaad: Created by AI4Bharat,  it covers 44,400 hours of audio across 13 Indian languages, making it the most extensive dataset for Indian speech translation.

Issues with AI

• Bias and Discrimination :AI systems can inherit biases from training data, leading to unfair treatment in hiring, lending, law enforcement, and other critical areas.

• Example: Amazon scrapped its AI recruitment tool after it became clear that it was biased against women, as it was trained on data predominantly from male applicants, leading the system to penalise resumes with gender-specific terms.

• Privacy and Data Security: 

• AI-driven surveillance and data analytics raise risks for privacy, democracy, and decision-making.

• AI is used for behavioural profiling, influencing consumer and political choices.

• Example: Several countries and government agencies, including Italy, Taiwan, Australia, South Korea, NASA etc have banned or restricted the use of DeepSeek's AI over data privacy and security concerns,

• Job Displacement: Automation threatens traditional employment, especially in repetitive, low-skill jobs, requiring workforce reskilling to adapt to AI-driven industries.

• Ethical Concerns: AI applications in autonomous weapons, deepfake technology, and mass surveillance pose significant ethical dilemmas and risks to human rights.

• Regulatory Challenges: The rapid advancement of AI outpaces legal and regulatory frameworks, leading to gaps in governance, liability, and enforcement.

• Dependence on Big Tech : AI development is concentrated in a few major corporations, raising concerns about monopolies, unequal access, and corporate control over AI advancements.

• Energy Consumption and Environmental Impact: Training large AI models requires massive computational power, leading to high energy consumption and increased carbon emissions.

• Lack of Emotional Intelligence: AI lacks human empathy, making it unsuitable for roles requiring emotional understanding, such as mental health support and caregiving.

• National Security Concerns: AI’s potential to be used in military applications raises global security risks, especially regarding autonomous weapons.

• Example: Lethal autonomous weapons systems (LAWs) could lead to unaccountable warfare, challenging international humanitarian law.

WAY FORWARD

Establish a Balanced AI Regulatory Framework: Combine the strengths of three different governance models
US Model (Techno-Optimism): Free-market AI development with minimal regulation.
China Model (State-Driven): AI development under strict government control.
EU Model (Regulated Digital Economy): Focus on human rights and ethical AI.
Global AI Governance Framework: Establish a universal AI regulatory framework under the UN to ensure ethical development and prevent misuse.
Open-Source Ecosystem: India should foster a culture of open-source AI development, encouraging engineering brilliance while making AI solutions accessible for all.
Develop Sovereign AI Models: Build AI models tailored to India’s data sets, ensuring bias-free solutions for local needs, and not just focusing on application but creating end-to-end AI ecosystems.
AI for Social Impact: India should prioritize AI solutions that address national challenges, such as healthcare diagnostics, financial inclusion, and agricultural productivity.
Example: India is home to over 240 Gen AI startups, with 70% focused on industry-specific challenges across sectors like healthcare, education, BFSI, and agriculture
Multilingual and Multimodal Models: Focus on developing AI models that can address the needs of India’s 22 official languages and local dialects, fostering greater inclusivity.
AI Diffusion and Global Leadership: Secure India’s position as a Tier-I country in the AI diffusion realm, eliminating the restrictions faced in access to advanced hardware and training of frontier AI models
India has 420,000 AI professionals, the largest AI workforce globally, with 92% enterprise adoption and a $17-billion market potential.
Strengthen AI Hardware Ecosystem: Develop AI hardware capabilities, such as GPUs, within the country to reduce reliance on external suppliers and ensure technological sovereignty.
Foster Collaboration for Global Supply Chains: Position India as an indispensable partner in global AI hardware and software supply chains, increasing its influence and leadership on the international stage
Enhance AI Education & Skilling: AI-related courses should be integrated into higher education curricula, with a focus on programming, statistics, and algorithm development.
International Collaboration on AI Research: Strengthen partnerships between nations to develop transparent, unbiased, and accountable AI systems.

CONCLUSION

For India to move beyond being a service provider in AI and become a global leader, it must prioritise deep-tech research, reduce dependency on foreign models, and build an independent AI ecosystem. Strategic collaboration between academia, industry, and government is essential to drive long-term innovation and establish India as a key player in shaping AI’s future.

PYQ MAPPING

Q) What are the areas of prohibitive labour that can be sustainably managed by robots? Discuss the initiatives that can propel research in premier research institutes for substantive and gainful innovation (2015)

Q) Introduce the concept of Artificial Intelligence (AI). How does AI help clinical diagnosis? Do you perceive any threat to privacy of the individual in the use of AI in the healthcare? (2023)

Q) What is the technology being employed for electronic toll collection on highways? What are its advantages and limitations? What are the proposed changes that will make this process seamless? Would this transition carry any potential hazards?(2024)

SAMPLE QUESTION

Q) Artificial Intelligence is revolutionizing various sectors, including healthcare, agriculture, and education. Discuss the potential benefits and risks of AI in transforming India's economy. What steps should the government take to harness its potential effectively? (10 marks, 150 words)

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Polity

Keywords:
Artificial Intelligence AI robots GPU Graphics Processing Unit IndiaAI Mission Digital India Machine Learning Deep Learning C-DAC ChatGPT Cybersecurity Global Initiative on AI for Health BHASHINI Niramai AI for India 2.0 Data Security Digital data Privacy