INDIA AI MISSION

Why in the news?

The Union cabinet has approved over Rs 10,300 crore for IndiaAI Mission to strengthen Artificial Intelligence (AI) Innovation Ecosystem.

About IndiaAI Mission 

• Aim:
  • Establish an ecosystem for AI innovation through public-private partnerships.
  • Deploying over 10,000 Graphics processing units (GPUs) for advanced AI computing infrastructure.
  • Driving responsible, inclusive growth of India's AI ecosystem through democratization, data quality improvement, and indigenous AI capabilities development.
• Ministry: An umbrella programme by the Ministry of Electronics and Information Technology (MeitY).
• Funding: To be made available over 5 years through a public-private partnership model.
• Implementing agency: 'IndiaAI' Independent Business Division under Digital India Corporation. 

About Artificial intelligence (AI)

• It refers to computer systems capable of performing complex tasks that historically only a human could do, such as reasoning, making decisions, or solving problems. 
• It encompasses a wide variety of technologies, including-
  • Machine learning (ML):  Uses algorithms trained on data sets to create models that enable machines to perform tasks that would otherwise only be possible for humans. 
    • Generative AI (GAI), evolved from ML, as a class of algorithms capable of generating new data. It includes Large Language Models (LLMs) like BharatGPT’s ‘Hanooman’ or ChatGPT and Generative Adversarial Network (GAN) used for generating deepfakes.
  • Deep learning: Trains computers to process information in a way that mimics human neural processes. 
  • Natural language processing (NLP): Allows computers to understand human language. E.g., BHASHINI.

Challenges in AI Adoption in India 

• Lack of trained professionals: According to NASSCOM, India houses a talent base of 416K AI professionals as opposed to the current demand of approximately 629K, a figure expected to surge to 1 million by 2026.
• Impact on Jobs: World Economic Forum has estimated that artificial intelligence will replace some 85 million jobs by 2025.
• Infrastructural challenges- Physical and Digital: Lack of AI-based infrastructure, such as cloud computing and limited availability of quality and open-source data.
• Ethical and Integrity Concerns:  
  • AI-based decisions are susceptible to inaccuracies, discriminatory outcomes, bias.
  • Unequal access to AI for marginalized populations can worsen the digital divide.
• Regulatory challenges: 
  • Lack of universal definition among regulators due to its global nature.
    • Also, keeping up with the evolving nature of AI can be challenging. 
  • Lack of transparency in AI systems can lead to users being unaware they are interacting with automated systems, impacting trust. 
  • Liability issues: The black box nature and self-learning ability of AI make it difficult to justify decisions and assign liability for errors. 
    • The inability of seeing how deep learning systems make their decisions is known as the ‘black box problem’. 

• Growing Instances of misuse: AI is being misused for Malicious Intent such as creation of Deep fakes to spread misinformation.

Way forward 

• Incorporate AI into curriculum, boost teaching and learning and encourage AI ventures.
• Firms can undertake upskilling of employees. 
  • As per a LinkedIn's report, nearly 94% of companies in India are upskilling employees due to advancing AI.
• Incentivize Indian start-ups to develop home-grown AI applications
• Identify suitable policymakers and regulatory institutions for AI governance laws. 
• Frame appropriate AI laws drawing on existing national technology policies and international frameworks.