Reducing risk posed by synthetic content an overview of technical approaches to digital content transparency
Year: 2024
Type: report
Abstract: This report examines the existing standards, tools, methods, and practices, as well as the potential development of further science-backed standards and techniques, for: authenticating content and tracking its provenance; labeling synthetic content, such as using watermarking; detecting synthetic content; preventing generative AI (GAI) from producing child sexual abuse material or producing non-consensual intimate imagery of real individuals (to include intimate digital depictions of the body or body parts of an identifiable individual); testing software used for the above purposes; and auditing and maintaining synthetic content.
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
OpenAlex ID: W4394803802