Home Environment The Promise and Pitfalls of AI in the Fight Against Climate Change

The Promise and Pitfalls of AI in the Fight Against Climate Change

Innovation can help achieve a sustainable future, yet it poses environmental and ethical dilemmas

by Michael Witkowicz
Blue sky with white clouds and trees with brown branches and no leaves.
A reflection of the intersection of cloud computing and climate change. (OTR/Michael Witkowicz)

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Artificial intelligence is a mixed blessing when it comes to climate change, says Ozgur Turetken, a professor at Toronto Metropolitan University (TMU) and an expert in AI applications and analytics.

AI’s predictive algorithms can analyze vast datasets with accuracy, reshaping clean energy management and informing decisions on how to reduce carbon emissions in various industries transitioning to cleaner practices. But it also has an environmental impact as AI relies on data centres for storage and processing, which consumes substantial amounts of energy.

“AI revolutionizes climate forecasts, informs decarbonization decisions, and optimizes renewable energy allocation,” Turetken said. “Machine learning’s pattern analysis predicts trends accurately.” 

As an example of AI’s transformative potential, Turetken pointed to its role in combating deforestation in the Amazon. In that case, it can be used to analyze real-time data to identify hotspots, enabling targeted interventions and proactive measures to prevent illegal logging.

“AI alone cannot solve the problem of climate change, as it is caused by factors like greenhouse gas emissions, fossil fuel consumption, and energy overuse,” he said. “However, AI can play a crucial role in identifying trends and prioritizing actions to mitigate these effects.” 

Turetken stressed the need to address data biases and ensure ethical uses of AI. “Biases in AI algorithms can perpetuate discriminatory practices and lead to inaccurate decisions resulting in flawed solutions,” he said. “Biases in AI algorithms are obstacles to effective climate change mitigation.”

He also warned the integration of AI into climate change mitigation efforts is challenging because it takes a lot of energy to run the data centres used to store and process algorithms. The high energy demand stems from the intensive computing tasks involved in AI operations and the cooling systems needed to maintain optimal operating temperatures.

The Ontario Ministry of Environment, Conservation and Parks issued a written statement affirming that “the Ontario government is actively exploring the potential of AI across various sectors. 

“Climate change is a generational challenge, and our government will continue to fight climate change with new initiatives that are flexible to the opportunities, needs, and circumstances of Ontarians while protecting job creators and industry,” the statement said.

The federal Environment and Climate Change Canada office (ECCC) said in a written statement that AI and machine learning approaches are being actively researched for application in weather, environment, and climate research. The research is exploring the potential for AI and machine learning to improve prediction skill and help with the analysis of large data sets such as climate model outputs or satellite weather observations. 

In its statement, the ECCC also said it recognizes the substantial energy demands and extensive computing infrastructure associated with AI use.

“ECCC continues to be cognizant of the energy demands and strive for efficient and effective use of our computing and energy resources,” the statement concluded.

This article may have been created with the use of AI software such as Google Docs, Grammarly, and/or Otter.ai for transcription.

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