Content

1. Environmental Costs of Artificial Intelligence
2. Language of harmony

Environmental Costs of Artificial Intelligence

Core Issue

• AI discourse dominated by productivity & innovation gains (health, agriculture, governance).
• Environmental externalities of AI (energy, water, carbon, land) remain under-discussed and under-regulated.
• Editorial highlights the hidden ecological footprint of AI compute and large language models (LLMs).

Relevance

GS III (Science & Technology, Environment, Economy)

• Science & Technology
  • Energy-intensive nature of AI and LLMs.
  • Trade-off between innovation and sustainability.
• Environment
  • Climate change, water stress, e-waste, resource extraction.
  • Precautionary principle and sustainable development.
• Economy
  • Negative externalities of AI not internalised in pricing.
  • Long-term fiscal implications of climate adaptation.

Practice Question

• Artificial Intelligence is often projected as a tool for climate solutions, yet its own environmental footprint is significant.Discuss the environmental costs of AI and suggest policy measures India can adopt to promote “Green AI”. (250 words)

Key Evidence & Data

• OECD working paper:
  • Global ICT sector contributes 1.8–2.8% of global GHG emissions (some estimates: up to 3.9%).
• UNEP Issue Note (Sept 2024):
  • AI servers may consume 4.2–6.6 bcm of water by 2027.
  • Training one LLM ≈ 300,000 kg CO₂ emissions.
• Study (2019, NLP):
  • Training one large AI model emits ~626,000 pounds CO₂ ≈ lifetime emissions of 5 cars.
• UNEP (July 2024):
  • ChatGPT query consumes ~10× energy of a Google search.
• Data transparency concern: Corporate disclosures (e.g., low per-prompt energy claims) may be misleading due to aggregation bias.

Environmental Dimension

• Carbon footprint: High compute intensity → climate change amplification.
• Water stress: Data centre cooling → pressure on freshwater resources.
• Land & material footprint: Rare earths, chip manufacturing, e-waste.
• Rebound effect: Efficiency gains → higher overall AI usage.

Science & Technology Dimension 

• AI models increasingly compute-hungry (scaling laws).
• Shift from algorithm efficiency to brute-force scaling.
• Lack of standardised environmental metrics for AI lifecycle.

Governance & Regulatory Dimension

• Global normative efforts:
  • UNESCO (2021): Recommendation on Ethics of AI – recognises environmental harms (non-binding).
  • US: Artificial Intelligence Environmental Impacts Act, 2024.
  • EU: Harmonised AI rules + Corporate Sustainability Reporting Directive (CSRD).
• India’s gap:
  • AI policy focuses on AI for climate, not climate cost of AI.

Constitutional & Legal Dimension

• Article 21: Right to life → includes clean environment (SC jurisprudence).
• Precautionary principle: Unregulated AI scaling risks irreversible damage.
• Polluter Pays Principle: Relevant for high-compute AI developers & data centres.

Economic Dimension

• Hidden environmental costs → negative externalities not priced into AI services.
• Risk of greenwashing via selective disclosures.
• Long-term fiscal stress due to climate adaptation costs.

Ethical Dimension 

• Inter-generational equity: Today’s AI growth vs tomorrow’s climate burden.
• Environmental justice: Water- and energy-intensive data centres often located in vulnerable regions.
• Responsible innovation: Ethics must extend beyond bias & privacy to ecology.

India-Specific Policy Options

• Measurement First
  • Extend EIA Notification, 2006 to cover large-scale AI systems & data centres.
• Standard Setting
  • Develop AI environmental metrics (energy, water, GHG, land) with industry, think tanks, NGOs.
• Data & Disclosure
  • Mandate AI-specific disclosures under ESG norms via SEBI & MCA.
  • Learn from EU’s CSRD model.
• Green AI Promotion
  • Incentivise pre-trained models, model compression, energy-efficient chips.
  • Renewable-powered data centres; water-neutral cooling technologies.
• Policy Integration
  • Align AI strategy with India’s NDCs, Net Zero 2070 goal, SDGs 12 & 13.

Challenges

• Measuring AI footprint is technically complex & proprietary.
• Risk of over-regulation stifling innovation.
• Fragmented global standards → regulatory arbitrage.
• Weak enforcement capacity in environmental governance.

Prelims Pointers

• ICT sector GHG share ≈ 2–4% globally.
• Training LLMs has significant carbon & water footprint.
• UNESCO AI Ethics Recommendations are non-binding.
• EU CSRD mandates reporting of data centre & compute emissions.

Bottom Line

• AI is neither climate-neutral nor environmentally benign.
• For India, the policy challenge is not to slow AI, but to green AI through measurement, transparency, and responsible governance—ensuring technological progress does not come at ecological cost.

Language of harmony

Core Issue 

• Malayalam Language Bill, 2025, passed by Kerala Assembly, aims to adopt Malayalam as the official language and promote its use across administration, education, judiciary, IT, and public life.
• Opposition from some leaders in Karnataka stems from fears of erosion of Tamil and Kannada linguistic minority rights in Kerala.
• Editorial argues that such fears are misplaced, arising from misreading of constitutional safeguards built into the Bill.

Relevance

GS Paper II (Polity, Governance, Constitution) – CORE

• Constitutional Provisions
  • Articles 345, 347, 350A, 350B, 263.
• Federalism
  • Cooperative vs competitive cultural federalism.
  • Centre–State and inter-State sensitivities.
• Governance
  • Language as a tool of administrative accessibility.
  • Role of Inter-State Council in dispute resolution.

Practice Question

• Language policies in India often trigger political and federal tensions.
  Discuss the constitutional safeguards available to linguistic minorities in the context of the Malayalam Language Bill, 2025. (250 words)

What the Bill Does?

• Declares Malayalam as the official language of Kerala for official purposes.
• Promotes Malayalam as first language for schoolchildren.
• Ensures explicit protections for linguistic minorities:
  • Tamil and Kannada minorities in notified areas can communicate with State authorities in their languages and receive replies likewise.
  • Non-Malayalam mother tongue students can study in other available languages as per National Education Curriculum.
  • Students from other States/foreign countries exempt from Malayalam exams at Classes IX, X, and Higher Secondary.

Constitutional & Legal Dimension  

• Article 345: State Legislature empowered to adopt any language for official purposes.
• Article 347: Protection of linguistic minorities at district/local level.
• Article 350A: Instruction in mother tongue at primary stage.
• Article 350B: Special Officer for Linguistic Minorities.
• Judicial Context:
  • Supreme Court of India ruling: Centre cannot indefinitely delay State Bills → led to revival of the Bill after 10 years (earlier version passed in 2015).

Inference: Bill operates within constitutional limits, balancing State autonomy and minority rights.

Federalism Dimension

• Asymmetric linguistic federalism: India’s linguistic States are approximations, not homogenous units.
• Migration has blurred linguistic borders, increasing multilingual coexistence.
• Language policy must reflect cooperative federalism, not competitive cultural politics.
• Opposition from other States reflects extra-territorial anxieties, not constitutional violation.

Social Dimension

• Linguistic pluralism is a core feature of Indian society.
• Risk of identity-based mobilisation if language debates turn adversarial.
• Protection of majority language need not imply marginalisation of minorities if safeguards are credible and implemented in good faith.

Governance & Administrative Dimension 

• Official language laws aim to:
  • Improve administrative accessibility.
  • Strengthen cultural confidence of States.
• However, poor communication and politicisation can:
  • Undermine inter-State trust.
  • Trigger unnecessary Centre–State frictions.

National Integration & Nation-Building

• Language is both a cultural resource and a potential fault line.
• Editorial stresses that the challenge is to:
  • Give every language its rightful place in administration and public sphere.
  • Avoid hostilities between communities.
• Nation-building requires dialogue, not dominance.

Institutional Mechanisms Highlighted

• Inter-State Council
  • Intended forum for resolving Centre–State and inter-State disputes.
  • Currently dormant and underutilised.
  • Editorial calls for strengthening its authority and role in language-related disputes.

Criticisms

• Misinterpretation risk: Language laws easily politicised beyond text.
• Centre’s inconsistency: Claims to promote all Indian languages but delays State legislation.
• Dormant federal forums: Lack of structured dialogue escalates disputes to political arenas.
• Hindi-centrism anxiety: Fear of “one-language cultural agenda” persists among non-Hindi States.

Way Forward 

• Good-faith dialogue among linguistic groups at State and national levels.
• Revitalise the Inter-State Council as a neutral mediator.
• Transparent communication by States on minority safeguards in language laws.
• Reinforce constitutional offices like Special Officer for Linguistic Minorities.
• National language policy must be plural, not hierarchical, aligning with cultural federalism.

Prelims Pointers

• States derive power to adopt official language from Article 345.
• Linguistic minority protections are constitutionally guaranteed (Arts. 347, 350A, 350B).
• Supreme Court has held that State Bills cannot be kept pending indefinitely by the Centre.
• Inter-State Council is under Article 263.