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Gamut AI Gamut AI Docs

Media, entertainment & creative

Media, entertainment and creative organisations sit at the centre of the generative-AI debate: synthetic content, recommendation, moderation and the cultural and rights questions that come with them. Gamut gives editorial, legal, trust-and-safety and risk teams a way to govern this AI responsibly, addressing transparency, provenance and cultural impact alongside the usual controls.

AI systems typically in scope

Section titled “AI systems typically in scope”
  • Generative content tools (text, image, audio, video).
  • Recommendation and personalisation engines.
  • Content moderation and trust-and-safety AI.
  • Synthetic media and voice, including likeness and deepfake detection.
  • Audience, rights and localisation AI.

Governance drivers

Section titled “Governance drivers”
  • Transparency and provenance. Disclosure of AI-generated or AI-assisted content.
  • EU AI Act. Transparency obligations for generative and synthetic media.
  • Cultural and creative-sector impact. Heritage, local-language and creative-rights considerations, signals Gamut intake captures directly.
  • Rights and likeness. Documented controls around consent, rights and synthetic likeness.

Use cases

Section titled “Use cases”

Govern a generative content tool with transparency and provenance

Section titled “Govern a generative content tool with transparency and provenance”

How Gamut solves it: register and model-card the tool, run intake flagging creative-sector, cultural-significance and local-language signals, route to GTSAF and the EU AI Act, and evidence disclosure and provenance controls.

Assess cultural and creative-sector impact

Section titled “Assess cultural and creative-sector impact”

How Gamut solves it: intake’s cultural-significance, heritage and creative-sector flags feed the risk tier and route deeper assessment, with NAGF available where decoloniality and local-context expectations apply.

Govern moderation AI accountably

Section titled “Govern moderation AI accountably”

How Gamut solves it: route to GTSAF and capture oversight, appeal and fairness evidence through control tests, with the audit log proving the history.

Quick start

Section titled “Quick start”
  1. Register the AI in AI System Records with a model card.
  2. Run intake, flag creative-sector, cultural and transparency signals, and confirm the tier.
  3. Route to GTSAF, EU AI Act and, where relevant, NAGF.
  4. Evidence transparency, provenance and oversight in the Evidence Tracker.
  5. Track gaps on the Remediation Roadmap.
  6. Produce assurance and board reporting from reporting.

Evidence priorities and reassessment

Section titled “Evidence priorities and reassessment”

Prioritise provenance, rights and licensing, creator consent, synthetic-media disclosure, moderation, misinformation, cultural impact, recommender effects and complaint handling. Reassess after content type, audience, training source, model, distribution or monetisation change. See the common assessment method.

Frameworks that apply

Section titled “Frameworks that apply”

GTSAF, EU AI Act, NAGF and NIST AI RMF.

Next

Section titled “Next”