# Estimating the Increase in Emissions caused by AI-augmented Search

arXiv: https://arxiv.org/abs/2407.16894 · HTML: https://mlsanity.com/paper/2407.16894/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 1 of its 10 references that are in the map.
- First posted on arXiv 17 Jun 2024.

## Builds on (most cited first, 1 of 1)

- [Estimating the Carbon Footprint of BLOOM, a 176B Parameter Language Model](https://mlsanity.com/paper/2211.02001/) (2022)

## Built on by (most cited first, 1 of 1)

- [Quantifying the Climate Risk of Generative AI: Region-Aware Carbon Accounting with G-TRACE and the AI Sustainability Pyramid](https://mlsanity.com/paper/2511.04776/) (2025)

## Abstract (arXiv)

AI-generated answers to conventional search queries dramatically increase the energy consumption. By our estimates, energy demand increase by 60-70 times. This is a based on an updated estimate of energy consumption for conventional search and recent work on the energy demand of queries to the BLOOM model, a 176B parameter model, and OpenAI's GPT-3, which is of similar complexity.