# The Carbon Emissions of Writing and Illustrating Are Lower for AI than for Humans

arXiv: https://arxiv.org/abs/2303.06219 · HTML: https://mlsanity.com/paper/2303.06219/

## Key facts

- Cited by 10 papers in the map (data through 14 Oct 2026).
- Builds on 3 of its 41 references that are in the map.
- First posted on arXiv 8 Mar 2023.

## Builds on (most cited first, 3 of 3)

- [Energy and Policy Considerations for Deep Learning in NLP](https://mlsanity.com/paper/1906.02243/) (2019)
- [Estimating the Carbon Footprint of BLOOM, a 176B Parameter Language Model](https://mlsanity.com/paper/2211.02001/) (2022)
- [The Carbon Footprint of Machine Learning Training Will Plateau, Then Shrink](https://mlsanity.com/paper/2204.05149/) (2022)

## Built on by (most cited first, 10 of 10)

- [Making AI Less "Thirsty": Uncovering and Addressing the Secret Water Footprint of AI Models](https://mlsanity.com/paper/2304.03271/) (2023)
- [Mapping the Ethics of Generative AI: A Comprehensive Scoping Review](https://mlsanity.com/paper/2402.08323/) (2024)
- [Machine-assisted quantitizing designs: augmenting humanities and social sciences with artificial intelligence](https://mlsanity.com/paper/2309.14379/) (2023)
- [Integrating ESG and AI: A Comprehensive Responsible AI Assessment Framework](https://mlsanity.com/paper/2408.00965/) (2024)
- [A Water Efficiency Dataset for African Data Centers](https://mlsanity.com/paper/2412.03716/) (2024)
- [Exploring Anthropomorphism in Conversational Agents for Environmental Sustainability](https://mlsanity.com/paper/2505.07142/) (2025)
- [FernUni LLM Experimental Infrastructure (FLEXI) -- Enabling Experimentation and Innovation in Higher Education Through Access to Open Large Language Models](https://mlsanity.com/paper/2407.13013/) (2024)
- [Illustrating Classic Brazilian Books using a Text-To-Image Diffusion Model](https://mlsanity.com/paper/2408.00544/) (2024)
- [Toward Agentic Environments: GenAI and the Convergence of AI, Sustainability, and Human-Centric Spaces](https://mlsanity.com/paper/2512.15787/) (2025)
- [DumpsterCluster: From Dumpster Diving to Serving LLaMA-70B on 60 GPUs](https://mlsanity.com/paper/2608.14614/) (2026)

## Abstract (arXiv)

As AI systems proliferate, their greenhouse gas emissions are an increasingly important concern for human societies. We analyze the emissions of several AI systems (ChatGPT, BLOOM, DALL-E2, Midjourney) relative to those of humans completing the same tasks. We find that an AI writing a page of text emits 130 to 1500 times less CO2e than a human doing so. Similarly, an AI creating an image emits 310 to 2900 times less. Emissions analysis do not account for social impacts such as professional displacement, legality, and rebound effects. In addition, AI is not a substitute for all human tasks. Nevertheless, at present, the use of AI holds the potential to carry out several major activities at much lower emission levels than can humans.