Researchers Quantify the Carbon Footprint of Generating AI Images

Researchers at the AI startup Hugging Face and Carnegie Mellon University discovered (PDF) that generating an image using artificial intelligence has a carbon footprint equivalent to charging a smartphone. Meanwhile, AI-generated text takes up as much energy as charging a smartphone to about 16 percent full. Engadget reports: The study didn't just look into image and text generation by machine learning programs. The researchers examined a total of 13 tasks, ranging from summarization to text classification, and measured the amount of carbon dioxide produced per every 1000 grams. For the sake of keeping the study fair and the datasets diverse, the researchers said they ran the experiments on 88 different models using 30 datasets. For each task, the researchers ran 1,000 prompts while gathering the "carbon code" to measure 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, whether it be text generation, summarization, image captioning, or image generation. Image generation ranked highest in the amount of emissions it produced and text classification was 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."

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