Quantifying the Environmental Impact: The Carbon Footprint of Creating AI-Generated Images

The AI startup collaborated with Carnegie Mellon University and discovered that using artificial intelligence, whether it’s to create or clean up an essay, has a carbon footprint equivalent to charging a smartphone. Researchers revealed that generating text requires much less energy than generating photos, with AI-generated text taking up as much energy as charging a smartphone to only 16 percent of a full charge.

The study examined a total of 13 tasks, ranging from summarization to text classification, and measured the amount of carbon dioxide produced per every 1000 grams. To keep the study fair and diverse, the researchers ran the experiments on 88 different models using 30 datasets. For each task, they measured both the energy consumed and the carbon emitted during an exchange.

The findings highlight that the most energy-intensive tasks are those that ask an AI model to generate new content, with image generation ranked highest in the amount of emissions it produced and text classification classified as the least energy-intensive task.

The researchers urge machine learning scientists and practitioners to “practice transparency regarding the nature and impacts of their models, to enable better understanding of their environmental impacts.” They point out that the volume of emissions can easily stack up when considering how popular and public AI models have become, using the example of OpenAI’s ChatGPT chatbot with upward of 10 million users per day.