How can AI help fight climate change?

As climate change intensifies the devastation from storms, wildfires and droughts, artificial intelligence (AI) and digital tools are increasingly being seen as a way to predict and limit its impacts.

Governments, tech firms and investors are showing growing interest in machine-based learning systems that use algorithms to identify patterns in data sets and make predictions, recommendations or decisions in real or virtual settings.

In June, the Rise Fund, an impact investing arm of private equity firm TPG, invested $100 million in a data and AI-driven “nowcasting” system devised by Kentucky-based startup Climavision to predict weather patterns with granular accuracy.

And an intergovernmental roadmap on AI’s role in fighting global warming is due to launch at November’s COP26 climate summit in Scotland.

But AI can also be highly energy-intensive and environmentally damaging, say critics who warn that the tech could be a costly distraction from more effective ways of tackling climate change.      

How can AI help combat climate change?

The technology is already being used to send natural disaster alerts in Japan, monitor deforestation in the Amazon, and design greener smart cities in China.

AI applications could also help design more energy-efficient buildings, improve power storage and optimise renewable energy deployment by feeding solar and wind power into the electricity grid as needed.

On a smaller scale, it could help households minimize their energy use - automatically switching off lights not in use or sending power from electric vehicles back into the grid to meet anticipated demand.

By 2030, the tech could help cut global greenhouse gas emissions by 4%, according to a recent study by accounting firm PricewaterhouseCoopers for Microsoft, which is developing machine learning products for the climate change market.

Peter Clutton-Brock, co-founder of the Centre for AI and Climate (CAIC), a Britain-based think tank, said the technology was “pushing back boundaries” for climate modelling.

AI can process huge amounts of unstructured data like pictures, graphs and maps, opening “huge possibilities for understanding the dynamics around sea level rise and ice sheets,” he told the Thomson Reuters Foundation.

Who will be able to use it?

The high cost of AI computational resources has pushed research largely into the private sector, where the market is “extremely vibrant,” according to Chris Goode, Climavision’s CEO. 

Climavision’s system uses a high-resolution radar network along with data from satellites and high-altitude weather balloons to fill in what the company says are “hundreds of gaps” in existing weather forecasting networks.

Energy and transport businesses, farmers, even the U.S. military will have access to “real-time elements of the atmosphere, what’s happening at this very moment, because it’s updated on a second-by-second mode,” Goode said.  

Ari Cohen, the external affairs director for TPG, which last week announced a new $5.4 billion Rise Climate

fund to invest in “climate solutions around the world”, said the AI market was likely to grow, as countries and corporations transition toward low-carbon energy.

From electricity grids to smart appliances, “data and AI-driven software will be integral to predicting market behaviour, balancing operations in real time and maximising energy yield,” he said in emailed comments.