Content provenance defines verifiable media origins and edits

The guide contrasts provenance with AI detection, warning that conflating the two can mislead buyers, researchers, and operators. It emphasizes testing under real-world conditions, not just polished demonstrations, and stresses the need for failure modes—like false positives or delays—that could undermine trust. Provenance matters as AI systems gain more context, modalities, and decision-making power, where small details can impact security, accountability, or legal risks. The article also outlines evaluation criteria, including measurable bottlenecks, baseline comparisons, and recovery mechanisms to ensure provenance delivers tangible benefits beyond theoretical claims.