April 19, 2024
AI in DeepMind Falls Short of Complete Solution for Climate Issues
AI

AI in DeepMind Falls Short of Complete Solution for Climate Issues

Google DeepMind Climate Action Lead Sims Witherspoon shared her perspective on the potential of artificial intelligence (AI) in addressing climate change at the Wired Impact Conference in London. With the recent consolidation of Google’s Brain and DeepMind AI teams under the unified banner of Google DeepMind, Witherspoon introduced a strategic framework named “Understand, Optimize, Accelerate” for leveraging AI in the fight against climate change.

The three-step framework involves first engaging with communities affected by climate change, then assessing the applicability of AI solutions, and finally deploying these solutions for impactful change. Witherspoon stressed the importance of collaboration in this endeavor, underscoring the need for combined efforts from academics, regulatory bodies, corporations, non-governmental organizations (NGOs), and the communities directly impacted by climate challenges.

In a notable collaboration with the U.K.’s National Weather Service Meteorological Office in 2021, Google DeepMind utilized comprehensive radar data to analyze rainfall in the U.K. The data was processed through Google’s Deep Generative Model of Rain (DGMR) generative AI model. A qualitative assessment involving 50 meteorological experts from the U.K. Met Office favored the AI methods, ranking them as the top choice over traditional approaches.

Despite the promising potential of AI in addressing climate change, Witherspoon emphasized that it is not a one-size-fits-all solution. Responsible deployment is crucial, considering the environmental impact of AI processes, particularly their energy intensity. Witherspoon acknowledged the necessity of operating on a carbon-free energy grid to mitigate these concerns.

This viewpoint aligns with previous warnings from experts like Kate Saenko of Boston University, who, in May, drew attention to the environmental impact of large AI models. Saenko highlighted that the 175 billion parameter GPT-3 model consumed energy equivalent to 123 cars for a year, generating 552 tons of CO2 even before its public release. These concerns underscore the importance of responsible AI development and deployment to ensure that the benefits of AI in addressing climate change do not come at the cost of exacerbating environmental challenges.

Image By rorozoa

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