In central India, where tomato growers have long grappled with the unpredictable impacts of extreme weather events, a Silicon Valley startup, ClimateAi, is pioneering an artificial intelligence (AI) platform to fortify farmers against the climate crisis. The region has endured severe droughts over the past decade, resulting in significant crop losses and jeopardising the livelihoods of local farmers.
ClimateAi’s platform, which recently conducted a study in Maharashtra, India, utilises data on climate, water, and soil to evaluate the vulnerability of crops to rising temperatures over the next two decades. In a groundbreaking case study, tomato producers were warned through the ClimateAi app about a potential 30% decrease in output due to impending heat and drought. Armed with this foresight, farmers adapted by switching to more climate-resilient seed varieties and adjusting planting times.
Himanshu Gupta, CEO and co-founder of ClimateAi, emphasised the role of AI as a “time and effectiveness multiplier” in addressing climate change. This innovative approach enables farmers to swiftly adapt their strategies, a process that traditionally took much longer. Gupta highlighted that this not only aids in climate resilience but also significantly reduces costs.
Beyond agriculture, experts assert that AI is poised to revolutionise various industries in the fight against climate change. From reducing pollution to enhancing weather models, AI’s predictive capabilities and efficiency are becoming invaluable tools for climate researchers. Fengqi You, chair professor at Cornell University’s engineering school, underlined AI’s potential in optimising decisions and resources across various domains.
However, as AI gains prominence, concerns arise regarding its environmental impact. The computational power required to run AI models, housed in energy-consuming data centers, poses challenges. Experts stress the need for a careful balance between AI’s benefits and its potential strain on the environment. Kara Lamb, an associate research scientist at Columbia University, acknowledged the trade-off but emphasised that the positives of applying AI to climate solutions outweigh the negatives.
AI’s contribution extends to scientific discovery, accelerating processes that traditionally relied on human analysis. From forecasting climate models to researching energy-conducting materials for solar panels, AI facilitates rapid experimentation and pattern recognition. It complements human efforts, making research faster and more effective in the battle against climate change.
In the Arctic, where warming is occurring at an alarming rate, AI assists scientists in making permafrost forecasts on a seasonal timescale. Anna Liljedahl, a scientist at the Woodwell Climate Research Center, noted that AI is “doing the dirty work,” providing a preliminary tool for researchers to verify and explore further.
AI’s applications extend to solutions as well, predicting renewable energy availability, researching carbon recapture materials, and modeling floods for emergency preparedness. Companies like ClimateAi and Google DeepMind are at the forefront of harnessing AI’s potential to address different facets of the climate crisis.
Despite AI’s promise, concerns about energy consumption loom large. Data centers powering AI models are often located in areas heavily reliant on fossil fuels. Striking a balance between harnessing AI’s potential and mitigating its environmental impact is crucial. Efforts by companies like Amazon Web Services, pledging to be “water positive,” showcase a growing awareness of these concerns.
As AI continues to evolve, lawmakers and regulators are urged to consider both its benefits and environmental implications. Experts emphasise the importance of making AI affordable and accessible, particularly for nations on the frontlines of the climate crisis.
