What Reducing Risks Posed by Synthetic Content: An Overview of Technical Approaches to Digital Content Transparency requires
This report examines the existing standards, tools, methods, and practices for authenticating content, tracking its provenance, labeling synthetic content through techniques like watermarking, and detecting synthetic content. It also addresses methods for preventing generative AI (GAI) from producing harmful content such as child sexual abuse material or non-consensual intimate imagery of real individuals. The focus is on digital content transparency, which refers to the process of documenting and accessing information about the origins and history of digital content. The goal is to manage and reduce risks related to synthetic content by recording and revealing provenance, providing tools to identify AI-generated content, and mitigating the production of specific illegal and harmful materials. The document provides an overview of technical approaches for provenance data tracking and synthetic content detection, alongside a review of current testing and evaluation techniques. It emphasizes that no single technique offers a comprehensive solution; their value is use-case and context-specific, relying on effective implementation and oversight. While the report focuses on technical approaches, it acknowledges the importance of normative, educational, regulatory, and market-based approaches. The technical methods described serve as building blocks to improve trust in digital content by indicating where AI has been used to generate or modify content.
Pillar: AI Governance & Law · Authority: National Institute of Standards and Technology · Version: 1.0.0 · Last updated:
Primary source: https://nvlpubs.nist.gov/nistpubs/ai/NIST.AI.100-4.pdf
SHA-256 integrity: 4d41038b236639ef32cfbf02d06342b1f696ee324756dedc81ad4a8125a69575
Primary Citations — 9 traced to source
- {"citation":"Section 1","text":"In this document, following Executive Order 14110, "synthetic content" refers to "information, such as images, videos, audio clips, and text, that has been significantly altered or generated by algorithms, including by AI.""}
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