INDIA’S AI ADOPTION: SCIENCE & TECHNOLOGY

INDIA’S AI ADOPTION: SCIENCE & TECHNOLOGY

NEWS: The approach to regulating AI in India

WHAT’S IN THE NEWS?

India is rapidly integrating AI across sectors but lacks a formal national strategy or regulatory framework, raising concerns about ethics, transparency, and accountability. Learning from global models, India needs a clear AI policy outlining vision, safeguards, and enforcement mechanisms.

India’s Rapid AI Adoption Without a Formal Strategy

  • India is witnessing rapid AI integration across sectors like education, healthcare, agriculture, and public administration.
  • However, the country lacks a formal national AI policy, regulatory law, or governance framework, raising concerns about long-term direction and safeguards.
  • The absence of such frameworks creates uncertainty about ethical standards, data usage, accountability mechanisms, and inclusion, particularly for vulnerable groups.

Global Trends in AI Governance

  • Over the last year, global focus in AI governance has shifted from ethical and human rights concerns to innovation and economic growth.
  • Only a few countries like China, the European Union (EU), Canada, Korea, Peru, and the U.S. have passed specific legislation to regulate AI.
  • Countries such as the U.K., Japan, Brazil, Costa Rica, Colombia, and Pakistan have AI regulation bills in draft stages awaiting approval.
  • Nearly 85 countries and the African Union have launched formal AI strategy documents, outlining:
  • National goals and priority sectors
  • Budgets and implementation plans
  • Ethical and safety principles
  • Government-industry-academia partnerships

India’s Current Approach to AI Development

  • India does not have an officially approved AI strategy or legal framework, though efforts have been underway since 2018.
  • The government relies on the IndiaAI Mission, an umbrella initiative aimed at nurturing an innovative and trustworthy AI ecosystem.
  • A 2018 discussion paper by NITI Aayog outlined a proposed AI strategy, but it has not been adopted formally nor allocated funding.
  • The IndiaAI Mission is structured around seven foundational pillars, focusing on research, infrastructure, skilling, ethics, data governance, and startup ecosystems.
  • An expert advisory group is working on governance recommendations, but no official framework has yet been released or operationalized.

Strengths and Weaknesses of India’s Current Model

  • The current flexible, adaptive approach allows India to adjust to global geopolitical trends, evolving technology, and public sentiment.
  • However, the absence of a consolidated national strategy creates:
  • A lack of vision and coordination across ministries and institutions
  • Fragmented and reactive decision-making, often dependent on individual bureaucratic or political leadership
  • Limited clarity for investors, startups, or international partners on India’s AI trajectory
  • India’s AI capacity still lags behind global powers like the U.S., China, EU, and U.K., who dominate AI research, patent filings, and product development.

Urgent Need for Ethical Safeguards and Civic Accountability

  • With AI entering sensitive areas like public health, education, and welfare, lack of regulation risks:
  • Discrimination due to biased algorithms
  • Invasion of privacy through unregulated data collection
  • Exclusion of marginalized groups in public service delivery
  • Most AI use cases in India today are governed by voluntary guidelines and lack enforceable standards.
  • There is little public knowledge or transparency regarding:
  • How algorithms are built and validated
  • Who is accountable for decisions made by AI
  • How one can seek redressal if harmed by an AI-based decision
  • AI-generated content has already triggered social unrest in India, demonstrating the risks of misinformation, deepfakes, and unverified automated media.

Global Models of AI Regulation and Lessons for India

  • Countries have adopted different regulatory models based on governance styles and institutional maturity:
  • The EU and China follow a centralised, cross-sectoral model, applying uniform rules across domains.
  • The U.S. follows a decentralised, sector-specific model, with separate norms for healthcare, finance, defence, etc.
  • China also enforces differentiated laws for types of AI, like recommendation systems, facial recognition, and autonomous vehicles.
  • India’s Digital Personal Data Protection (DPDP) Act, 2023 offers a foundational framework and could be extended to address AI governance.
  • A hybrid model—blending centralised ethical oversight with sector-specific regulation—may work best in India’s federal and diverse context.

Way Forward: Building an Inclusive and Responsible AI Ecosystem

  • India must begin by drafting and publishing a formal national AI policy to guide development, deployment, and regulation.
  • This policy should include:
  • A clear national vision for AI and its strategic objectives
  • Ethical guidelines ensuring fairness, transparency, and accountability
  • Plans for infrastructure, including data centers, computing power, and secure storage
  • Sectoral priorities, such as AI in agriculture, healthcare, governance, education, and climate
  • Designation of a lead regulatory or coordinating authority
  • The AI policy should serve as a testbed to evaluate feasibility and enforcement tools before passing full-fledged laws.
  • Public consultation and civic awareness campaigns must be conducted to:
  • Ensure citizen participation
  • Educate stakeholders on AI risks and benefits
  • Build trust and inclusivity in AI governance
  • Collaboration with industry, academia, and civil society will be key in implementing responsible and scalable AI systems.

 

Source: https://www.thehindu.com/opinion/op-ed/the-approach-to-regulating-ai-in-india/article69453499.ece#:~:text=India's%20approach,development%20and%20adoption%20of%20AI.