Generative AI is known to consume large amounts of energy due to the extensive computing power required for training models and processing tasks, raising concerns about its contribution to environmental problems such as increased carbon emissions and resource depletion.
Sasha Luccionia prominent Canadian computer scientist and AI researcher known for her work on the environmental impact of artificial intelligence, recently discussed the topic at the ALL IN artificial intelligence conference in Montreal.
“I find it especially disappointing that generative AI is being used to search the web,” says Luccioni told AFP on the sidelines of the conference, complaining about the energy costs of using AI for tasks that traditional search engines could perform.
Thoughtful and efficient use of AI
Unlike regular search engines that retrieve existing information, AI models generate new content, requiring significant computing power to train on billions of data points and respond to user requests. For example, Google’s AI Summary feature provides AI-generated snapshots that summarize key points from multiple sources in response to complex questions.
“We are accelerating the climate crisis,” Luccioni warned, calling for greater transparency from tech companies and urging governments to legislate more effectively once such transparency is achieved.
Recognized by Time in 2024, as one of the 100 most influential figures in AI, in 2020 Luccioni helped create a tool called “CodeCarbon”, which allows developers to measure the carbon footprint of their code. This tool has been downloaded more than a million times. She is now working on a certification system to label AI models based on their energy efficiency. Comparing the system to the energy consumption ratings of U.S. Environmental Protection Agency appliances, she explained, “For a specific task, we can measure energy efficiency and say this model has an A+, and that model has a D.”
While she may be seen by some as anti-AI, Luccioni is keen to emphasize that her goal is to promote “energy sobriety” by encouraging users to make thoughtful and efficient use of AI technologies.
