# Comparing the willingness to share for human-generated vs. AI-generated fake news

arXiv: https://arxiv.org/abs/2402.07395 · HTML: https://mlsanity.com/paper/2402.07395/

## Key facts

- Cited by 12 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 12 Feb 2024.

## Built on by (most cited first, 12 of 12)

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- [Taxonomy to Regulation: A (Geo)Political Taxonomy for AI Risks and Regulatory Measures in the EU AI Act](https://mlsanity.com/paper/2404.11476/) (2024)
- [From Generation to Detection: A Multimodal Multi-Task Dataset for Benchmarking Health Misinformation](https://mlsanity.com/paper/2505.18685/) (2025)
- [Designing Effective Digital Literacy Interventions for Boosting Deepfake Discernment](https://mlsanity.com/paper/2507.23492/) (2025)
- [Addressing Data Scarcity in Bangla Fake News Detection: An LLM-Based Dataset Augmentation Approach](https://mlsanity.com/paper/2605.01292/) (2026)
- [Evaluating the Propensity of Generative AI for Producing Harmful Disinformation During the 2024 US Election Cycle](https://mlsanity.com/paper/2411.06120/) (2024)
- [Images Amplify Misinformation Sharing in Vision-Language Models](https://mlsanity.com/paper/2505.13302/) (2025)
- [Do small language models generate realistic variable-quality fake news headlines?](https://mlsanity.com/paper/2509.00680/) (2025)

## Abstract (arXiv)

Generative artificial intelligence (AI) presents large risks for society when it is used to create fake news. A crucial factor for fake news to go viral on social media is that users share such content. Here, we aim to shed light on the sharing behavior of users across human-generated vs. AI-generated fake news. Specifically, we study: (1) What is the perceived veracity of human-generated fake news vs. AI-generated fake news? (2) What is the user's willingness to share human-generated fake news vs. AI-generated fake news on social media? (3) What socio-economic characteristics let users fall for AI-generated fake news? To this end, we conducted a pre-registered, online experiment with N= 988 subjects and 20 fake news from the COVID-19 pandemic generated by GPT-4 vs. humans. Our findings show that AI-generated fake news is perceived as less accurate than human-generated fake news, but both tend to be shared equally. Further, several socio-economic factors explain who falls for AI-generated fake news.