# She Works, He Works: A Curious Exploration of Gender Bias in AI-Generated Imagery

arXiv: https://arxiv.org/abs/2407.18524 · HTML: https://mlsanity.com/paper/2407.18524/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 2 of its 16 references that are in the map.
- First posted on arXiv 26 Jul 2024.

## Builds on (most cited first, 2 of 2)

- [Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings](https://mlsanity.com/paper/1607.06520/) (2016)
- [Multimodal datasets: misogyny, pornography, and malignant stereotypes](https://mlsanity.com/paper/2110.01963/) (2021)

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

- [LLM-based Human Simulations Have Not Yet Been Reliable](https://mlsanity.com/paper/2501.08579/) (2025)
- [A Framework for Critical Evaluation of Text-to-Image Models: Integrating Art Historical Analysis, Artistic Exploration, and Critical Prompt Engineering](https://mlsanity.com/paper/2412.12774/) (2024)

## Abstract (arXiv)

This paper examines gender bias in AI-generated imagery of construction workers, highlighting discrepancies in the portrayal of male and female figures. Grounded in Griselda Pollock's theories on visual culture and gender, the analysis reveals that AI models tend to sexualize female figures while portraying male figures as more authoritative and competent. These findings underscore AI's potential to mirror and perpetuate societal biases, emphasizing the need for critical engagement with AI-generated content. The project contributes to discussions on the ethical implications of AI in creative practices and its broader impact on cultural perceptions of gender.