[Burning Issue] Artificial Intelligence and Climate change

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Artificial Intelligence (AI) technologies have been often thought as a gateway to a future written in chrome, operating on a virtual cloud.

Even in Budget 2022-23, AI was described as a sunrise technology that would “assist sustainable development at scale and modernize the country.”

In terms of climate change, AI can prove to be immensely helpful in developing environment-friendly infrastructure, making climate predictions and decarbonizing industries. However, ironically, AI with itself brings an environmental cost to the development of the technology.

What is Climate Change?

  • It deals with the global phenomenon of climate transformation that significantly impacts the earth’s usual climatic conditions (temperature, precipitation, wind, etc.). 
  • They are mainly caused due to human-made activities.
  • The major source of climate change is global warming, which is primarily caused by the greenhouse effect.
  • Rapid urbanization and industrial revolution are the other main causes that lead to the risk of climate change with increased energy demand and production, especially in the form of fossil fuels.
  •  The growing risk of climate change has a disastrous impact on earth organisms, including human beings and earth’s flora and fauna.
  • It further leads to the destruction of the food chain and economic resources.

Social and Economic Impact of Climate Change

  • The cost of adapting coastal areas to rising sea levels.
  • Relocation of whole towns.
  • Shrinking productivity of harvests.
  • Loss of the capacity to work due to heat.
  • More wars to gain access to limited resources.
  • Freshwater will be short in the supply.
  • Spread of diseases due to higher temperatures.
  • Inflation in food and consumer goods.
  • The extreme meteorological phenomenon will cause widespread poverty.

Artificial Intelligence

  • Artificial intelligence is the simulation of human intelligence processes by machines, especially computer systems. Specific applications of AI include expert systems, natural language processing, speech recognition and machine vision.
  • In general, AI systems work by ingesting large amounts of labeled training data, analyzing the data for correlations and patterns, and using these patterns to make predictions about future states.
  • AI programming focuses on three cognitive skills: learning, reasoning and self-correction.

How can AI help in the mitigation of Climate Change?

  • AI is a disruptive paradigm that has greater potential to assess, predict, and mitigate the risk of climate change with the efficient use of data, learning algorithms, and sensing devices.
  • It performs a calculation, makes predictions, and takes decisions to mitigate the impacts of climate change.
  • By developing effective models for weather forecasting and environmental monitoring, AI makes us better understand the impacts of climate change across various geographical locations.
  • It interprets climatic data and predicts weather events, extreme climate conditions, and other socio-economic impacts of climate change and precipitation.
  • From a technical perspective, AI offers better climatic predictions, shows the impacts of extreme weather, finds the actual source of carbon emitters and includes numerous other reasonable contributions. 
  • This enables the policymakers to be aware of the rising sea levels, earth hazards, hurricanes, temperature change, disruption to natural habitats, and species extinction.

Applications of AI for Climate Change mitigation

The following are the few areas in which AI can directly help mitigate the risks posed by climate change:-

  • AI-assisted prediction models for climate change mitigation
  • Role of machine vision in climate informatics and forecasting
  • Recent trends in AI to reduce carbon footprints for a sustainable environment
  • AI for earth hazard management
  • AI to promote eco-friendly energy production and consumption
  • AI-assisted expert systems for climate change risk prediction and assessment
  • AI-assisted big data analytics Synergy of IoT, big data, cloud computing, and AI techniques in climate change prediction and mitigation
  • Machine learning for a sustainable green future
  • AI in reducing the impacts of global warming
  • Deep learning for sustainable earth surveillance and earth informatics

AI Can Accelerate Our Response to Climate Change

  • Improve Energy Efficiency– According to the Capgemini Research Institute, artificial intelligence should improve power efficiency by 15% in the next three to five years.
  • Optimize Clean Energy Development- AI computational models can find sites for dams that can produce the lowest amounts of GHG emissions.
  • Avoid Waste- Companies, governments, and leaders frequently deploy AI solutions to avoid waste, reduce energy waste from buildings or understand supply and demand.
  • Make Transportation More Efficient- AI is already the technology that powers autonomous vehicles, including shared cars and smart transportation systems in some cities.
  • Tools to Help Understand Carbon Footprint- AI can help build tools to help individuals and companies understand their carbon footprint and what actions they can take to reduce it.
  • Create New Low-Carbon Materials- If AI could develop new materials with similar properties but with a smaller carbon footprint, it could help slow climate change.

What are the Global Trends for the Development of AI Technology?

  • Unfair Start- A few developed economies possess certain material advantages right from the start, they also set the rules.
  • They have an advantage in research and development, and possess a skilled workforce as well as wealth to invest in AI.
  • West vs the World- North America and East Asia alone account for three-fourths of global private investment in AI, patents and publications.
  • Political Advantage- The current state of inequity in AI in terms of governance raises concerns about the technological fluency of policymakers in developing and underdeveloped countries and their representation and empowerment at the international bodies that set rules and standards on AI.
  • Benefits for few- The developing and underdeveloped countries have not been much benefitted by the technology as AI’s social and economic benefits are accruing to a few countries only.

India & AI

  • In Budget 2022-23, AI was described as a sunrise technology that would “assist sustainable development at scale and modernize the country.”
  • Research ecosystem- India has 386 of a total of 22,000 Ph.D. educated researchers worldwide and ranked 10th globally in research.  AI research concentrated mostly at institutes, like IITs, IIITs and IISc.
  • Present Use of AI- Presently, AI is used in India in sectors such as Smart Mobility and Transportation, Healthcare, Agriculture, Education and Smart Cities & Infrastructure.
  • AI adoption across sectors-
  1. COREs– Centres of Research Excellence in Artificial Intelligence will focus on core research of AI.
  2. ICTAI– International Centre for Transformational Artificial Intelligence will provide the ecosystem for application-based technology development and deployment.
  3. AIRAWAT (AI research, analytics and knowledge assimilation platform will be a cloud platform for Big Data Analytics and Assimilation, with a large, power-optimized AI Computing infrastructure using advanced AI processing.

AI in India: Opportunities

AI has the potential to drive growth by enabling:

  • Intelligent automation i.e. ability to automate complex physical world tasks that require adaptability and agility across industries,
  • Labor and capital augmentation: enabling humans to focus on parts of their role that add the most value, complementing human capabilities and improving capital efficiency
  • Innovation diffusion i.e. propelling innovations as it diffuses through the economy

What is the Impact of AI Technology on Climate?

  • Carbon Footprint- The climate impact of AI can be majorly attributed to the energy use of training and operating large AI models.
  • Emissions- In 2020, digital technologies accounted for between 1.8% and 6.3% of global emissions.
  • At this same time, AI development and adoption across sectors skyrocketed and so did the demand for processing power associated with larger and larger AI models.
  • Quantification– A main problem to tackle in reducing AI’s climate impact is to quantify its energy consumption and carbon emission, and to make this information transparent.
  • UNESCO’s Efforts- The idea of sustainability is rapidly entering mainstream debates on AI ethics and sustainable development.
  • Recently, UNESCO adopted the Recommendation on the Ethics of Artificial Intelligence, calling on actors to “reduce the environmental impact of AI systems, including but not limited to its carbon footprint.”

Way Forward

  • Research: Dedicated studies, more investments in R&D, and better policy interventions are required in this field. AI needs to be developed and deployed so it can meet society’s needs and protect the environment by saving more energy than it expends.
  • Technology + Sustainable Development:  To make sure AI is used to help, and not hinder society, it’s time to merge the two big debates of the present time – digital technology and sustainable development (in particular, the environment). If we use the former to save the latter, this could be the best possible use made out of the resources available to us.
  • Opportunities for the Developing World: Governments of developing countries, including India, should assess their technology-led growth priorities in the context of AI’s climate costs.
  • Recommendation of WEF: The AI developers “must incorporate the health of the natural environment as a fundamental dimension.”


Governments of developing countries, India included, should also assess their technology-led growth priorities in the context of AI’s climate costs. It is argued that as developing nations are not plagued by the legacy infrastructure it would be easier for them to “build up better”. These countries don’t have to follow the same AI-led growth paradigm as their Western counterparts.

It may be worth thinking through what “solutions” would truly work for the unique social and economic contexts of the communities in our global village.

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