Instagram’s ‘80s trend is everywhere. But the fun and nostalgia comes with a environmental cost

First, Studio Ghibli-style AI portraits took the internet by storm, and now Instagram's '80s trend prompt is giving users another way to transform their photos into nostalgic, retro-style AI images. While people are enjoying recreating images and reliving nostalgia, the trend is also raising concerns about the environmental cost of generating large volumes of AI images. Here’s how the massive volume of AI generation is impacting the environment.

Power-hungry AI

According to Carnegie Mellon University and Hugging Face research, one AI-generated image can consume 0.01–0.29 kWh. One image may not seem significant, but if millions of people generate several images each as part of a viral trend, the total electricity consumption can become substantial.

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Since Data centres are the source behind AI image generation, these facilities run continuously and require large amounts of electricity.

AI has a water footprint too

Since a vast amount of AI work happens in data centres, they consume a massive amount of water as these centres consist of powerful servers and GPUs that generate a lot of heat. The researchers estimated that roughly 20–50 questions and answers with ChatGPT could correspond to about 500 ml of water use. However, the exact amount varies depending on the facility, cooling technology, location, and workload.

Hidden hardware cost

AI’s environmental impact is not limited to the electricity and water used by data centres. These massive centres equip specialised GPUs and other computing equipment to run generative AI models. These components require minerals, rare-earth elements, and other raw materials, and extracting these materials involves mining, which can consume significant energy and cause environmental damage.

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Therefore, behind AI image generation, there is a physical chain involving mines, minerals, semiconductor factories, GPUs, data centres, electricity and cooling systems, all of which contribute to the technology’s broader environmental footprint.

While the 80s trend has just started, it will soon start to fade, but another trend may shape the continuing cycle of mass AI image generation.