ANALYSIS

Related analysis

AI-Generated Content Provenance: How to Document Origins Without Confusing Them with a License
GUIA

AI-Generated Content Provenance: How to Document Origins Without Confusing Them with a License

A workflow for recording how an image, video, or audio file is created, modified, and published—and for interpreting provenance credentials with care.

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AI-Generated or Library Sound Effects: How to Evaluate Stable Audio 3.0 Before Integrating It
COMPARATIVA

AI-Generated or Library Sound Effects: How to Evaluate Stable Audio 3.0 Before Integrating It

A protocol for comparing Stable Audio 3.0 with licensed-library sound effects—without mistaking an impressive sample for a reliable workflow. Includes listening criteria, time, editing, and rights.

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Generative Video in Production: How to Validate Continuity Between Shots, Actions, and Objects Before Publishing or Editing a Sequence
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Generative Video in Production: How to Validate Continuity Between Shots, Actions, and Objects Before Publishing or Editing a Sequence

A generated shot can be convincing on its own and still be unusable when edited with others. This guide proposes a protocol for evaluating visual, spatial, and narrative continuity in generative-video sequences, recording their traceability, and deciding which clips are approved, which require intervention, and which must be discarded.

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Localized AI image editing: how to verify that the model changes only what was requested and preserves the rest of the asset
GUIA

Localized AI image editing: how to verify that the model changes only what was requested and preserves the rest of the asset

A generative edit that is useful in production is not validated merely because the requested change looks correct. This guide proposes treating every retouch as a preservation contract: define what may change, what must remain, how to measure it, and when to require human review.

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Synthetic Voices in Production: How to Demonstrate Consent, Control Likeness, and Remove a Voice Without Losing Traceability
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Synthetic Voices in Production: How to Demonstrate Consent, Control Likeness, and Remove a Voice Without Losing Traceability

Using a synthetic voice responsibly requires more than a checkbox or a convincing demo. This guide proposes an operating system for linking each audio asset to a specific authorization, controlling the risk of resemblance to identifiable people, disclosing its nature where appropriate, and removing assets when the terms of use change.

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AI Image and Video Provenance: When a C2PA Credential Is Evidence—and When It Is Not
GUIA

AI Image and Video Provenance: When a C2PA Credential Is Evidence—and When It Is Not

C2PA credentials can provide cryptographically verifiable evidence about provenance statements and transformations of a file. On their own, they do not prove that an image is true, may be legally reused, or depicts people who gave their consent. This guide sets out a method for assessing, preserving, and communicating that evidence without overstating its conclusions.

22 Sep 2026