On the other side of the world, Silicon Valley start-up Climate AI is developing an artificial intelligence platform to evaluate how vulnerable crops are to warming temperatures over the next two decades.
The tool uses data on the climate, water, and soil of a particular location to measure how viable the landscape will be for growing in the coming years.
Maharashtra, India, was one of its first case studies in 2021. Farmers could go into the Climate AI app and input what seed they were growing and where they wanted to plant it.
With that data, Climate AI ran simulations and found that extreme heat and drought would lead to an approximately 30% decrease in tomato output in the region over the next two decades. It warned growers that they should change their strategy.
The results proved pivotal—tomato producers adjusted their business plans by switching to more climate-resilient seed varieties and shifting the times they plant tomato seeds. Finding new growing locations usually takes a while for farmers affected by climate change, but “now it can happen in a matter of minutes, and it also saves them a lot of costs,” according to Himanshu Gupta, who grew up in India and is a co-founder of Climate Ai.
“The way we think about AI is that it’s a time and effectiveness multiplier for solutions to climate change,” Gupta said.
Better assessing future risks for farming is just one of the ways artificial intelligence technologies are being used to address the climate crisis.
AI first crashed into the public consciousness this year thanks to popular, consumer-facing AI tools like ChatGPT, and experts say the technology is set to revolutionize countless industries. But climate researchers have for years been thinking about how AI—computer programs that can rapidly analyze enormous amounts of data and complete complex tasks in ways similar to how a human might—could help them better understand and address the changing climate.
Now, experts say AI is poised to accelerate everything from reducing pollution to improving weather models.
“Efficiencies are one thing that AI is very good at: optimizing decisions and optimizing resources,” said Fengqi You, chair professor at Cornell University’s engineering school. “It’s a system that has very strong predictive capabilities that could be tremendously helpful in many domains, ranging from understanding small-scale molecules to broader climate systems to help us fight climate change.”
With the breakneck pace at which the planet has been warming, accelerating the speed at which the world deploys and implements solutions is crucial. But for all of AI’s promise, the infrastructure that supports the technology—data centres filled with rows of powerful, energy-sucking computers—could itself be a strain on the environment. Experts say software engineers must work closely with climate scientists to find a balance.
“It’s something that has to be considered as this trade-off,” said Kara Lamb, an associate research scientist at Columbia University’s earth and environmental engineering department. Still, “the positives outweigh the negatives in terms of applying it to these types of approaches.”
Artificial intelligence is a broad term that refers to various digital tools trained to perform a wide range of complex tasks that might previously have required input from an actual person. Generally, what these technologies have in common is their ability to rapidly process and find connections among vast amounts of disparate data.
This makes AI particularly good at things like forecasting and running simulations. Unlike traditional computer programs, AI tools can typically continue learning over time as new data is available or as the systems receive new feedback about the quality of their outputs.
While scientific discovery used to be reliant on humans’ ability to gather, observe, and analyze evidence, computers can now process large datasets, identify patterns, and run digital experiments in a fraction of the time that human researchers would need.
“For the climate models, fundamentally, we’re trying to solve these equations… how these atmosphere models are interacting, and it takes a long time to solve,” you said. Similarly, research on new energy-conduction materials, like those for solar panels, could require countless hours of testing that can now be sped up using AI.
“In the past, people used to need trial and error; we’d need researchers working every day and night,” you said. “Now, because of AI, which doesn’t need to sleep; it just needs electric power, it could keep working 24/7, and it can become very helpful in accelerating discovery.”
AI probably won’t replace the need for humans in the climate change fight. But it could make their work faster and more effective.
Researchers seeking to restore coastlines by replanting seagrass, for example, are using AI to model the best locations to target those replanting efforts, said Dan Keeler, chief communication officer at impact investing firm Newsday, which is involved in charitable efforts to support the coastal restoration.
An AI algorithm trained to address the issue could take into consideration everything from toxins in the water or disruptive shipping routes to how replanting efforts could impact nearby sea life or even coastal tourism.
“It’s very difficult to put all those together into a single model with conventional methods, but AI makes that much more possible,” Keeler said.
