The effect of artificial intelligence on the environment is still being debated.

Panelists at POLITICO’s AI & Tech Summit on Wednesday discussed the immense potential of machine learning programs in aiding efforts to decrease greenhouse gas emissions. This could involve using machine learning to enhance predictions for energy demand and weather patterns, as well as accelerating development in renewable energy and climate solutions such as nuclear fusion and direct air capture.

There are still uncertainties surrounding the amount of strain that energy-intensive AI programs will contribute to the issue of climate change.

Jake Loosararian, the CEO of Gecko Robotics, a company that utilizes AI to monitor energy infrastructure, stated that utilizing additional energy equates to relying on a greater amount of non-renewable fuels.

However, there are some who doubt that the increasing utilization of AI will result in a rise in emissions that contribute to global warming.

David Sandalow, a researcher at Columbia University’s Center on Global Energy Policy, has analyzed the available literature on this topic for the past few months and has found that the data is lacking. He pointed out that according to the International Energy Agency, the data centers powering AI and other internet applications only accounted for 0.6% of global greenhouse gas emissions in 2020.

According to Sandalow, emissions from AI may become a significant issue in the future, but there is also potential for them to decrease.

The unpredictable course of emissions is a result of the possibility for enhancements in the efficiency of AI program-operating chips, algorithms, and data centers, according to his argument.

Sandalow suggested implementing policy frameworks and incentives to prevent an increase in AI emissions as the use of AI continues to expand.