Within the scientific community, it is estimated that artificial intelligence — otherwise meant to serve as a means to effectively combat climate change — will become one of the most egregious CO2 culprits should current trends continue.
Within the scientific community, it is estimated that artificial intelligence — otherwise meant to serve as a means to effectively combat climate change — will become one of the most egregious CO2 culprits should current trends continue. To raise awareness about the challenge, two University of Copenhagen students have launched a tool to calculate the carbon footprint of developing deep learning models.
On a daily basis, and perhaps without realizing it, most of us are in close contact with advanced AI methods known as deep learning. Deep learning algorithms churn whenever we use Siri or Alexa, when Netflix suggests movies and tv shows based upon our viewing histories, or when we communicate with a website’s customer service chatbot.
However, the rapidly evolving technology, one that has otherwise been expected to serve as an effective weapon against climate change, has a downside that many people are unaware of — sky high energy consumption. Artificial intelligence, and particularly the subfield of deep learning, appears likely to become a significant climate culprit should industry trends continue. In only six years — from 2012 to 2018 — the compute needed for deep learning has grown 300,000%. However, the energy consumption and carbon footprint associated with developing algorithms is rarely measured, despite numerous studies that clearly demonstrate the growing problem.
Read more at University of Copenhagen
Photo Credit: markusspiske via Pixabay
