# A User Study of Perceived Carbon Footprint

arXiv: https://arxiv.org/abs/1911.11658 · HTML: https://mlsanity.com/paper/1911.11658/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 26 Nov 2019.

## Built on by (most cited first, 2 of 2)

- [Generalizing while preserving monotonicity in comparison-based preference learning models](https://mlsanity.com/paper/2506.08616/) (2025)
- [On Monotonicity in AI Alignment](https://mlsanity.com/paper/2506.08998/) (2025)

## Abstract (arXiv)

We propose a statistical model to understand people's perception of their carbon footprint. Driven by the observation that few people think of CO2 impact in absolute terms, we design a system to probe people's perception from simple pairwise comparisons of the relative carbon footprint of their actions. The formulation of the model enables us to take an active-learning approach to selecting the pairs of actions that are maximally informative about the model parameters. We define a set of 18 actions and collect a dataset of 2183 comparisons from 176 users on a university campus. The early results reveal promising directions to improve climate communication and enhance climate mitigation.