How can disclosure support harm mitigation methods for AI-generated Child Sexual Abuse Material?
- Child Sexual Abuse Material (CSAM) poses a unique challenge when it comes to mitigating harm from generative AI models – the harm is done as soon as the content is created, unlike other synthetic content categories which cause harm only when shared.
- However, both direct and indirect disclosure can still be helpful to a number of non-user audiences that seek to mitigate harm from this content such as Trust and Safety teams, researchers, and law enforcement.
- Although bad actors have little incentive to disclose AI-generated CSAM, direct and indirect disclosure should still be incorporated by Builders into their models in order to mitigate harm from such content.
This is a case submission by researchers Riana Pfefferkorn and Caroline Meinhardt of Stanford HAI as a supporter of PAI’s Synthetic Media Framework. Explore the other case studies