On a farm in St. Peters Bay, Prince Edward Island, a black four-wheeled rover with arms outstretched rolls through a row of thigh-high green leaves, its giant tires pressing against the red dirt of a potato field. It feels like it belongs more at home in the dusty red Martian landscape than on a farm.
“Right now, there were a few people stopping on the road to see what was happening,” said Aitzaz Farooq, interim associate dean of the School of Climate Change and Adaptation at the University of Prince Edward Island (UPEI).
Meet AgriRobot, a robot trained using artificial intelligence to recognize diseases in potato plants.
Farouk leads a team of researchers at UPEI (in partnership with the governments of Prince Edward Island and New Brunswick) who are using AI in new and innovative ways. AgriRobot was the brainchild of Charan Preet Singh, a master's student in the university's Department of Sustainable Design Engineering.
“The program will create a map with location information, so that even if someone has to enter, they will not need training…they can download that map to their mobile phone,” Farouk said. “It will direct you to where those infected plants are and pull them out.”
With climate change, farmers face more challenges than ever before. From floods, droughts and disease to warmer temperatures and shifts in growing and harvesting seasons, the agricultural business is changing rapidly, which means farmers – and technology – need to constantly keep up.
But there is a paradox: while AI helps with climate adaptation and mitigation, it has its own emissions problem. This is something that will only grow as AI is used in more and more applications.
AI requires a lot of computers – and energy
“AI is being used in all sorts of ways to address climate action,” said Priya Donte, co-founder and president of Climate Change AI, a global nonprofit that studies the use of AI in climate action.
“From helping us better forecast solar and wind on the power grid to helping us better integrate it into power grids…to helping us map things like deforestation and emissions using global satellite images in order to understand where deforestation or emissions are occurring.” In real time.”
AI runs on computers – lots of them – hosted in data centers around the world. While AI models are running, they need electricity. If this electricity comes from a grid that uses fossil fuels, it contributes to emissions.
Meanwhile, the computers in these data centers generate a lot of heat and need cooling, often requiring more electricity.
“Running AI is like running any other computer program,” said Yassin Gernet, a researcher in New York who works for Hugging Face, a company that hosts open source platforms where AI models are shared. “You have inputs, you want outputs.”
“It's going to do lots and lots of operations. Doing a lot of operations for one answer means there's a lot of energy and electricity consumed by the computer running those operations.”
The problem is that no one really knows how much AI represents in emissions in those data centers.
“We really have to look forward to growth in the emissions footprint of AI,” said Donte, who is based in Cambridge, Massachusetts.
“Basically, one thing that is challenging and needed is that there is not enough transparency between the data center providers, and between the machine learning entities that are actually creating the machine learning algorithms in terms of actually monitoring and measuring greenhouse gas emissions.”
Predicting forest fires before they start
As we face an ongoing climate crisis, scientists are trying to come up with ways to help us deal with the consequences.
In the Global South, locust infestations are increasing, threatening food security. to New tool called Kuzi The organization helps farmers by providing real-time data using satellites, soil moisture, surface temperature, humidity and more to predict potential disease outbreaks. It can then send a notification to farmers on their mobile phones.
As the risk of wildfires increases, engineers and scientists are creating new tools to sense and even predict when they will break out.
Dryad Networks, a company based in Germany, has developed solar-powered sensors that can smell a fire even before the flame breaks out.
“behind [the] “The membrane is a gas sensor that is sensitive to hydrogen, carbon monoxide and volatile organic compounds. So it's actually like an electronic nose that can actually smell fire,” said CEO Carsten Brinksholt. That's where AI comes in: We're running AI into the sensor, to have it actually recognize pre-trained machine learning models that have been trained on the smell of fire.
The company has already deployed 20,000 worldwide, with a pilot project in Part of the forests of California. Dryad has also started a pilot project with an organization he did not name, Brinksholt said.
Artificial intelligence comes at the expense of the environment
Experts say AI has huge potential, but first there must be a better idea of how much it contributes to emissions – and the transition to renewable energy sources.
“We both need to green the grid, and we need to make serious choices about how to make AI models more efficient in the places we will use them,” said Donte, of AI for Climate Change.
“But also, as we must do in every sector, we must reassess what uses are worthy of the electricity coming in.”
This extends to personal use of AI, because not all uses of AI are the same. Showing him two pictures, one of a dog and one of a cat, and asking him to choose the cat, takes much less energy than asking him to create or calculate something.
While we may enjoy creating filters for ourselves or asking questions about generative AI like ChatGPT, this comes at a cost in terms of emissions. In fact, one study suggests that every time an AI creates an image, it does Use enough power to charge the mobile phone.
“We certainly shouldn't look at AI as something less expensive,” Donte said. “I think it's very easy to watch this abstract thing on your computer that has no impact, but it does.”
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