N4S:

This article connects two powerful forces shaping our future — Artificial Intelligence and energy sustainability. It dives deep into how AI, while revolutionising everything from healthcare to creativity, is also silently guzzling electricity at alarming rates (“Why AI Needs So Much Energy?”). In UPSC, questions from such topics often begin innocently (like the 2023 question on AI and clinical diagnosis), but they demand layered understanding. Many aspirants falter here — they either describe AI in isolation or ignore its wider implications. They miss interlinkages with environment, policy, or energy. This article helps exactly there. It not only explains AI’s energy demands in simple terms (e.g., GPUs “melting” under energy load) but shows how this is becoming a policy and ethical challenge too (“Smart Tech vs. Smart Planet”). It connects AI with nuclear energy, especially Small Modular Reactors (SMRs), a theme rarely found in standard books but crucial for aspirants who want to go beyond the obvious. The real strength of this article lies in its 360° view — it brings in perspectives of environmentalists, technologists, economists, and policymakers. For example, the contrast between Microsoft’s green AI ambition and the EU’s Green Digital Transformation policy shows how nations and corporations are responding differently. Most importantly, this article trains you to think like a generalist with a specialist lens — exactly what UPSC wants. It doesn’t just give you facts; it helps you frame a dynamic answer when asked, “Can smart tech and sustainability go hand in hand?”

This article explores the intersection of Artificial Intelligence and energy sustainability, a theme gaining relevance in UPSC. While AI transforms sectors like healthcare and education, its growing energy demands raise serious environmental and policy concerns. Aspirants often miss these connections, focusing on AI in isolation without linking it to energy use, ethics, or sustainability.

The article explains why AI systems consume so much power and introduces rarely discussed but important solutions like Small Modular Reactors. It also contrasts global responses, such as Microsoft’s green AI goals and the EU’s Green Digital Strategy. By combining environmental, technological, and policy angles, the article helps you build a multidimensional perspective — exactly what UPSC expects in complex, forward-looking questions.

PYQ ANCHORING

GS 3: 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]

MICROTHEME: Artificial Intelligence

The AI boom isn’t just about smarter tech — it’s also driving a huge spike in energy use. Data centres already eat up around 1.5% of the world’s electricity, and that number’s set to double by 2030, thanks to tools like ChatGPT and Midjourney. Yes, AI boosts productivity. But it’s also putting major pressure on power grids. So, how do we keep the digital revolution green?One promising answer: nuclear energy — especially Small Modular Reactors (SMRs). They’re cleaner, more reliable, and can scale up to meet AI’s growing hunger for power.

But that leads us to some tough questions: Can we roll out SMRs fast enough to match AI’s growth? Are policymakers and tech leaders even thinking about energy while building this AI future? And at what point do we ask — is smarter tech worth it if it’s not sustainable?

Why AI Needs So Much Energy?

High Computational Requirements: AI models like GPT-4 require massive computing during training and inference stages. Each training cycle can emit as much CO₂ as five cars running across their lifecycle. Example: MIT Technology Review estimates AI model lifecycle emissions rival some small nations’ per capita CO₂.
Continuous Power Use Post-Deployment: Once deployed, AI models operate across global servers 24/7. Tools like ChatGPT or Midjourney continuously consume energy to serve millions of users daily. Example: Midjourney and DALL·E require high-resolution image synthesis, stressing data centres 24×7.
Data Storage and Management: AI relies on gigantic datasets stored in high-performance storage systems. These systems demand constant cooling and uninterrupted energy supply. Data centres need continuous cooling, consuming additional 40-50% of the total energy.
Energy-Intensive GPUs: AI depends on power-hungry GPUs (Graphic Processing Units). Example: OpenAI’s CEO tweeted “our GPUs are melting,” illustrating thermal and energy inefficiencies.
Edge AI and Real-time Analytics: As AI integrates with IoT and real-time applications, more decentralized processing (Edge AI) will further increase total power requirements. AI services demand always-on global infrastructure. Example: Amazon, Microsoft, and Google run redundant global data hubs powered by fossil-heavy grids.

Smart Tech vs. a Smart Planet: Can Innovation Survive Without Sustainability?

As data centres and AI models consume more and more electricity, we’re forced to ask a tough question — is smarter tech really worth it if it’s not sustainable? The answer isn’t black and white. It depends on whom you ask — an environmentalist, a policymaker, a technologist, or even an economist. Each sees the trade-offs differently.

1. Environmentalist’s Perspective

View: No — sustainability must come first.
Smart tech that drains natural resources or increases emissions undermines global climate goals.
Example:
Training large language models like GPT-3 emitted ~500 tonnes of CO₂ — equivalent to five roundtrip flights between New York and Sydney per passenger. For an environmentalist, this is unacceptable unless offset by clean energy use or environmental benefit.

2. Technologist’s Perspective

View: Yes — but only if we innovate sustainably.
Tech can solve sustainability challenges, but the tools must evolve to be greener themselves.
Example:
Google uses AI to reduce energy consumption in its data centers by up to 40%. Smart tech isn’t the enemy — but its infrastructure must adapt.

3. Policy Maker’s Perspective

View: It’s a balancing act — tech drives development, but guardrails are needed.
Smart tech enables economic and social progress (healthcare, education, governance). But policies are needed to limit its carbon footprint.
Example:
The EU’s Green Digital Transformation initiative supports digital growth with strict environmental standards. It’s not “either-or” — it’s “both-and.”

4. Economist’s Perspective

View: Worth it — if productivity gains outweigh environmental costs.
AI boosts GDP, automates tasks, and creates new industries. Economists might accept short-term energy costs if long-term benefits are high.
Example:
PwC estimates AI could add $15.7 trillion to the global economy by 2030. But rising energy costs and carbon taxes might change the math.

5. Ethicist’s Perspective

View: Tech without sustainability violates intergenerational justice.
Smart tech should not serve today’s convenience at tomorrow’s cost.
Example:
If AI advances worsen climate conditions for future generations, the ethical foundation collapses — even if current users benefit.

6. Corporate Perspective (Big Tech)

View: Yes — and we’ll invest in solutions to make it sustainable later.
Companies often scale AI quickly and address sustainability reactively.
Example:
Microsoft aims to be carbon negative by 2030 — but its AI ventures like Copilot still add energy strain. Their response: invest in SMRs and green hydrogen to catch up.

INDIA’S PREPAREDNESS TO BALANCE THE SMART AND SUSTAINABLE

Major Argument	Supporting Examples / Initiatives
1. Building AI infrastructure with sustainability in mind	IndiaAI Mission (₹10,300 crore) – Aims to create public compute capacity for AI; sustainability is critical due to high energy demands. Paris AI Action Summit (2024) – India pledged to make AI development energy-efficient.
2. Prioritizing nuclear energy (especially SMRs) as a clean power source for digital growth	NITI Aayog – SMR Roadmap (2022) – Identifies SMRs as vital to low-carbon strategy. BARC & NPCIL Research – Indigenous 100 MW SMR development underway.
3. Aligning national policy with global safety and regulatory frameworks	IAEA SMR Safety Working Group – India participates in creating harmonized global safety norms for SMRs.
4. Leveraging strategic international partnerships for tech-energy synergy	India-U.S. Civil Nuclear Pact – Exploring SMRs under nuclear cooperation. India-France Nuclear Collaboration – Opportunity for clean tech + AI-aligned power hubs. Act East & Arctic Engagement – SMR included in Arctic diplomacy with Norway, Russia.
5. Encouraging multilateral clean energy cooperation to support AI scalability	Quad Clean Energy Program – India partners with the U.S., Japan, and Australia on SMR research and deployment.
6. Involving private players to build scalable green AI infrastructure	Public-Private Pilot Projects – Indian tech firms exploring partnerships with SMR companies like NuScale and TerraPower.

ROLE OF SMR’S IN ADDRESSING THE CHALLENGE

Small Modular Reactors (SMRs) are compact, factory-built nuclear reactors that produce between 50–300 MW of electricity. Their modular design allows quicker deployment, easier scaling, and on-site integration with energy-hungry AI data centres. Here’s why they are being seen as a game-changer for the future of digital energy:

1. Reliable, Round-the-Clock Energy for AI

Unlike solar or wind, SMRs provide continuous baseload power — a must for AI systems that require 24×7 uptime.

Example: In 2023, Google signed a deal to power its AI operations using nuclear energy.
SMRs are ideal for co-location with data centres, reducing transmission losses.
They can also produce industrial heat and hydrogen, supporting not just AI but green industrial ecosystems.

2. Speed, Scalability, and Flexibility

SMRs are designed to be modular and scalable, making them ideal for the fast-paced growth of AI infrastructure.

Deployment takes just 3–5 years, compared to over a decade for traditional nuclear plants.
NuScale Power in the U.S. received regulatory approval for modular construction, setting a global precedent.
Their small size allows easy integration into urban or industrial areas, including retrofitting old power sites like Microsoft’s project at Three Mile Island.

3. Environmental Sustainability

SMRs operate with zero direct CO₂ emissions, making them a strong ally in achieving climate goals.

Compared to land-intensive solar or wind farms, SMRs have a much smaller physical footprint per MW.
Newer models also use recycled or minimal water for cooling, a big advantage in water-scarce regions.

4. Safety by Design

Modern SMRs are equipped with passive safety features that minimize meltdown risk and require no external power to operate in emergencies.

Example: Rolls Royce SMRs use natural convection cooling, reducing the need for active safety interventions.
These advanced systems are designed with post-Fukushima learnings in mind, making them safer and more publicly acceptable.

5. Cost Efficiency and Economic Viability

With mass production and deployment, SMRs can drive down energy costs significantly.

According to NITI Aayog, SMRs are projected to reduce electricity costs in India from ₹10.3 to ₹5/kWh.
Their ability to co-locate with AI infrastructure reduces the need for expensive grid upgrades, further improving ROI.

Way Forward

Update Nuclear Policies: Revise the Atomic Energy Act to allow private investment in SMRs, with necessary safety measures, as suggested by NITI Aayog.
Mandate Green AI Practices: Implement energy audits and green energy mandates for AI companies, similar to the EU’s Digital Services Act.
Increase Public Awareness: Launch campaigns to educate the public on nuclear energy, using platforms like Vigyan Samagam to dispel myths and build trust.
Launch SMR Pilot Projects: Start a pilot SMR project in AI clusters like Chennai through public-private partnerships, similar to Tamil Nadu’s nuclear corridor.
Promote Hybrid Energy Models: Pair SMRs with renewable energy sources like solar in high-irradiance areas (Rajasthan, Ladakh) and use AI for energy optimization in SMRs.

#BACK2BASICS: SMALL MODULAR REACTORS

What are Small Modular Reactors (SMRs)?

SMRs are advanced nuclear reactors with a capacity of up to 300 MW, designed to be modular, factory-built, and easily transportable. They offer:

Faster construction due to prefabrication
Scalability for phased deployment
Enhanced safety via passive cooling and underground installation
Suitable for remote areas, hydrogen production, desalination, and grid support

Steps Taken by India to Promote SMRs

Policy Support
The government sees SMRs as key to achieving net-zero by 2070, with support from DAE and NITI Aayog.
Indigenous Development
DAE has proposed a 220 MWe PHWR-based SMR, leveraging India’s nuclear expertise.
Regulatory Readiness
AERB is preparing a tailored regulatory framework for SMRs.
International Collaboration
India is exploring tech partnerships with the USA, Russia, and France (e.g., NuScale, RITM series).
Private Sector Role
The government encourages private participation, especially in manufacturing under ‘Make in India’.
R&D Focus
BARC and NPCIL are working on early-stage R&D, including hybrid nuclear-renewable systems.
Budget and Policy Backing
The Union Budget 2023–24 emphasized SMRs and urged public-private collaboration.

SMRs offer India a clean, safe, and decentralized power option. While challenges remain, active policy, regulatory, and R&D steps are being taken to enable deployment.

Significance of SMRs Across Different Sectors

Here’s your content presented in a clear and organized table format:

Application Area	Role of SMRs
1. Climate Change Mitigation	Provide zero-carbon energy, supporting IPCC and Paris Agreement goals.
2. Industrial Decarbonization	Power energy-intensive industries like steel, cement, and chemicals.
3. Water Desalination	Enable clean drinking water production in arid regions (e.g., UAE initiatives).
4. Space Exploration	NASA’s Project Kilopower is testing SMRs for future lunar and Martian colonies.
5. Remote Power Supply	Supply off-grid electricity to Arctic, island, and remote communities (e.g., Alaska).
6. Hydrogen Production	Generate clean hydrogen using high-temperature SMRs for fuel and industry.
7. Disaster Resilience	Ensure power for critical infrastructure like hospitals during emergencies.
8. Defense Sector	Provide secure, self-sufficient power for military bases (used in U.S. submarines).
9. Education & Research	Support nuclear R&D through university-based SMRs (e.g., Canada, UK).

Challenges in using SMRs

Challenge Area	Description	Example / Elaboration
1. Outdated Policies & Regulatory Bottlenecks	India lacks a clear framework for SMRs under current nuclear law, slowing private participation and innovation.	The Atomic Energy Act (1962) excludes private players and doesn’t account for modular or hybrid systems.
2. Public Skepticism & Nuclear Anxiety	Long-standing fears around nuclear safety hinder acceptance despite technological advances.	Microsoft’s SMR plan at Three Mile Island faced backlash due to past nuclear incidents like Chernobyl.
3. High Costs & Private Investment Hesitation	SMRs require large upfront capital and have long ROI timelines, discouraging private sector interest.	Estimated unit costs of ₹3,000–5,000 crore make financing and scalability difficult.
4. Delays & Capacity Constraints	Long approval timelines, lack of skilled nuclear professionals, and infrastructure readiness slow deployment.	India faces engineering and manpower shortages; nuclear projects like Kudankulam have seen prolonged delays.
5. Nuclear Waste & Security Risks	Even though SMRs generate less waste, India lacks tested disposal systems, and smaller units pose unique safety risks.	No deep geological repository exists; microreactors need strong safeguards to prevent sabotage or theft.
6. Integration with Renewables & Grids	SMRs must be aligned with intermittent renewables in a smart grid setup — something India is yet to plan for.	India’s national electricity planning hasn’t fully addressed nuclear-renewable co-deployment.
7. Environmental Trade-offs of Digital-AI Growth	Co-locating SMRs with data centres may intensify land, water, and e-waste challenges.	Meta’s Arizona data centre uses 1.5 billion litres of water/year; AI chip manufacturing produces toxic waste.

Question for Practice
Q. Explore the potential of Small Modular Nuclear Reactors (SMNRs) in meeting the growing energy needs of Arctic development and the expansion of AI and data infrastructure. Analyze the advantages and challenges associated with deploying SMNRs, and assess their feasibility as a sustainable and eco-friendly energy solution in India.