Exploring the Use of Abusive Generative AI Models on Civitai

TL;DR

This paper conducts the first comprehensive empirical study of Civitai, an AIGC social platform, analyzing its content to understand abuse patterns and inform moderation strategies for safeguarding online creative communities.

Contribution

It provides a large-scale dataset and analysis of abusive content on Civitai, highlighting challenges and proposing moderation insights for AIGC social platforms.

Findings

87K models and 2M images analyzed

Identification of abuse patterns in generated content

Insights into moderation strategies for AIGC platforms

Abstract

The rise of generative AI is transforming the landscape of digital imagery, and exerting a significant influence on online creative communities. This has led to the emergence of AI-Generated Content (AIGC) social platforms, such as Civitai. These distinctive social platforms allow users to build and share their own generative AI models, thereby enhancing the potential for more diverse artistic expression. Designed in the vein of social networks, they also provide artists with the means to showcase their creations (generated from the models), engage in discussions, and obtain feedback, thus nurturing a sense of community. Yet, this openness also raises concerns about the abuse of such platforms, e.g., using models to disseminate deceptive deepfakes or infringe upon copyrights. To explore this, we conduct the first comprehensive empirical study of an AIGC social platform, focusing on its use for generating abusive content. As an exemplar, we construct a comprehensive dataset covering Civitai, the largest available AIGC social platform. Based on this dataset of 87K models and 2M images, we explore the characteristics of content and discuss strategies for moderation to better govern these platforms.