The website, which was unveiled on Thursday, has been up and running for two years. It began with the realization that even though we have the tools to cope with climate change, it is a huge obstacle to dealing with public awareness and political will, said Yoshua Bengio, professor at the University of Montreal and founder of Mila, who also led the research team to the project. Bengio, a winner of the Turing Award, said the researchers wanted to create images that felt personal, leading to the idea of using AI to show what your house might look like during an environmental disaster.
“Citizens have heard in the past about climate change from scientists, reports and graphs,” Bengio said. “And there is a cognitive aspect, that is, something does not frighten us so much if it is not right before our eyes.”
Climate scientists reported in August that the world is already about 1.2 degrees Celsius warmer than pre-industrial levels. Temperatures should stay below 1.5 degrees, they say – a critical threshold to avoid the most serious consequences of the climate crisis. For every fraction of a degree of warming, the consequences of climate change worsen. Even by limiting global warming to 1.5 degrees, scientists say the kind of extreme weather the world experienced this summer, including floods and more devastating hurricanes, will become more severe and more frequent.
There are not many pairs of images out there that show home before and after a flood – the kind of data that would be useful for training an AI system on the relationship between the image it is fed with and what it should make it into. . To compensate for this, researchers started building a computerized virtual world. This world, equivalent to several blocks in a city, allowed them to control floods and other elements so they could create synthetic images of places “before” and “after” a climate disaster, said Sasha Luccioni, a postdoctoral fellow at the University of Montreal and Mila and a lead researcher on the project.
This synthetic data, along with real images showing flooded houses and images of smoky orange skies and smog, was used to train an AI system to take a given image from Google Street View and make it look like a climate disaster at hand. . To do this, the system first had to learn where e.g. Water should go in a given image, and then essentially paint water in a realistic way, including reflections of objects protruding from the water and considerations of illuminating the image.
After a user enters an address and ThisClimateDoesNotExist generates images, the site encourages the user to share them with others and presents resources to learn more about climate change and combat it.
“I think what we want is to channel the initial one, like, ‘Oh man, my house is underwater’ in climate action,” Luccioni said.
– CNN’s Rachel Ramirez contributed to this report.
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