# Delving into: the quantification of Ai-generated content on the internet (synthetic data)

arXiv: https://arxiv.org/abs/2504.08755 · HTML: https://mlsanity.com/paper/2504.08755/

## Key facts

- Cited by 10 papers in the map (data through 14 Oct 2026).
- Placed in LLM synthetic data generation, one of 13 directions in Synthetic data and self-improvement for LLMs.
- Builds on 5 of its 22 references that are in the map.
- First posted on arXiv 29 Mar 2025.

## Placed in

- Synthetic data and self-improvement for LLMs / [LLM synthetic data generation](https://mlsanity.com/synth/llm-synthetic-data-generation/)

## Builds on (most cited first, 5 of 5)

- [Language Models are Few-Shot Learners](https://mlsanity.com/paper/2005.14165/) (2020)
- [GPT-4o System Card](https://mlsanity.com/paper/2410.21276/) (2024)
- [Self-Consuming Generative Models Go MAD](https://mlsanity.com/paper/2307.01850/) (2023)
- [Self-Improving Diffusion Models with Synthetic Data](https://mlsanity.com/paper/2408.16333/) (2024)
- [MONAL: Model Autophagy Analysis for Modeling Human-AI Interactions](https://mlsanity.com/paper/2402.11271/) (2024)

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

- [Watermarking Without Standards Is Not AI Governance](https://mlsanity.com/paper/2505.23814/) (2025)
- [The Impact of AI-Generated Text on the Internet](https://mlsanity.com/paper/2604.26965/) (2026)
- [Retrieval Collapses When AI Pollutes the Web](https://mlsanity.com/paper/2602.16136/) (2026)
- [A New Digital Divide? Coder Worldviews, the Slop Economy, and Democracy in the Age of AI](https://mlsanity.com/paper/2510.04755/) (2025)
- [When Does Model Collapse Occur in Structured Interactive Learning?](https://mlsanity.com/paper/2605.20151/) (2026)
- [Position: the Stochastic Parrot in the Coal Mine. Model Collapse is a Threat to Low-Resource Communities](https://mlsanity.com/paper/2605.04127/) (2026)
- [Steganography Without Modification: Hidden Communication via LLM Seeds](https://mlsanity.com/paper/2606.09135/) (2026)
- [Future of AI Models: A Computational perspective on Model collapse](https://mlsanity.com/paper/2511.05535/) (2025)
- [How unique are hallucinated citations offered by generative Artificial Intelligence models?](https://mlsanity.com/paper/2604.16407/) (2026)
- [Coherence-Driven Belief Formation and Population Dynamics of Contagion in LLM Agents](https://mlsanity.com/paper/2610.02654/) (2026)

## Abstract (arXiv)

While it is increasingly evident that the internet is becoming saturated with content created by generated Ai large language models, accurately measuring the scale of this phenomenon has proven challenging. By analyzing the frequency of specific keywords commonly used by ChatGPT, this paper demonstrates that such linguistic markers can effectively be used to esti-mate the presence of generative AI content online. The findings suggest that at least 30% of text on active web pages originates from AI-generated sources, with the actual proportion likely ap-proaching 40%. Given the implications of autophagous loops, this is a sobering realization.