The Impact of AI on the Environment: A Critical Analysis

AI poses significant challenges and risks for the environment, both directly and indirectly.

Artificial intelligence (AI) is transforming various domains of human activity, from healthcare to education, from business to entertainment. However, AI also poses significant challenges and risks for the environment, both directly and indirectly. In this article, we will analyze the environmental impact of AI and how to mitigate the risks, based on the latest research and evidence.

The Direct Impact of AI on the Environment

The direct impact of AI on the environment refers to the energy consumption and carbon emissions of the hardware and infrastructure that enable AI applications. According to a study by Strubell et al. (2019), training a large neural network can emit as much carbon as five cars in their lifetimes. Another study by Schwartz et al. (2019) estimated that the global carbon footprint of AI in 2017 was 284 megatons of CO2, equivalent to the annual emissions of 50 million cars. The main factors that contribute to the high environmental cost of AI are the computational complexity, the data intensity, and the rapid innovation cycle of AI models and systems.