# How Spammers and Scammers Leverage AI-Generated Images on Facebook for Audience Growth

arXiv: https://arxiv.org/abs/2403.12838 · HTML: https://mlsanity.com/paper/2403.12838/

## Key facts

- Cited by 11 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 19 Mar 2024.

## Built on by (most cited first, 11 of 11)

- [Generative AI Misuse: A Taxonomy of Tactics and Insights from Real-World Data](https://mlsanity.com/paper/2406.13843/) (2024)
- [Adversarial Robustness of AI-Generated Image Detectors in the Real World](https://mlsanity.com/paper/2410.01574/) (2024)
- [Neglected Risks: The Disturbing Reality of Children's Images in Datasets and the Urgent Call for Accountability](https://mlsanity.com/paper/2504.14446/) (2025)
- [Is computational creativity flourishing on the dead internet?](https://mlsanity.com/paper/2407.17590/) (2024)
- [Application of AI-based Models for Online Fraud Detection and Analysis](https://mlsanity.com/paper/2409.19022/) (2024)
- [Designing Effective Digital Literacy Interventions for Boosting Deepfake Discernment](https://mlsanity.com/paper/2507.23492/) (2025)
- [A parameter-efficient three-branch architecture for multimodal misinformation detection with limited annotations](https://mlsanity.com/paper/2512.20257/) (2025)
- [Toward Accountable AI-Generated Content on Social Platforms: Steganographic Attribution and Multimodal Harm Detection](https://mlsanity.com/paper/2604.10460/) (2026)
- [Prefill-Guided Thinking for zero-shot detection of AI-generated images](https://mlsanity.com/paper/2506.11031/) (2025)
- [LAID: Lightweight AI-Generated Image Detection in Spatial and Spectral Domains](https://mlsanity.com/paper/2507.05162/) (2025)
- [Synthetic Sociality: How Generative Models Privatize the Social Fabric](https://mlsanity.com/paper/2605.14090/) (2026)

## Abstract (arXiv)

Much of the research and discourse on risks from artificial intelligence (AI) image generators, such as DALL-E and Midjourney, has centered around whether they could be used to inject false information into political discourse. We show that spammers and scammers - seemingly motivated by profit or clout, not ideology - are already using AI-generated images to gain significant traction on Facebook. At times, the Facebook Feed is recommending unlabeled AI-generated images to users who neither follow the Pages posting the images nor realize that the images are AI-generated, highlighting the need for improved transparency and provenance standards as AI models proliferate.