Safeguarding video evidence
How can you check whether an edit can be distributed and retain the evidence supporting that decision?
3500 € per session, excl. VAT
In short
In two days, totalling 14 hours excluding breaks, design a prototype for checking audiovisual assets: rights, consents, provenance and disclosures relating to synthetic content. You will build an evidence register, test blocking rules and prepare a measurable pilot, with human validation of sensitive decisions.
Why this training?
A file available in a media library is not necessarily cleared for use: an expired licence, an excluded territory, music not covered by the licence or permission to use someone's image that is incompatible with the edit may prevent its distribution. Generative AI can help extract and compare clauses, but proves neither ownership of rights nor the authenticity of a video. The system links every decision to a verified document and provides for escalation. Running case study: The fictitious organisation Avelune Scénographies is preparing a 90-second promotional film combining interviews, licensed music, archive material and a synthetic avatar. Several supporting documents are missing; a decision on the edit is required before distribution on the website and social media. Transfer to the workplace: Launch a pilot on a single edit, with an editorial lead and a legal contact; measure missing evidence, detected anomalies and revised decisions before any expansion.
Objectives of this training
- Map the rights required for each asset and use.
- Structure evidence of consent and provenance.
- Prototype a validation workflow with blocking rules.
- Test the checks against prepared anomalies.
- Define the measurements and responsibilities for the pilot.
Who is it for and what are the prerequisites?
Roles and tasks concerned
- Audiovisual production and post-production managers
- Contacts responsible for communications, compliance or media asset management
Prior skills
- Be familiar with a video production and distribution workflow.
- Have experience using structured prompts with generative AI.
- Know how to organise a tabular register and supporting documents.
What you will work on
Define the scope of uses
Objective: Identify the areas to be checked. Media, territories, duration, adaptations and versions of the edit.
Reconstruct the rights
Objective: Link each use to an authorisation. Copyright, related rights, music, archive material and licences.
Assess consents
Objective: Identify inadequate authorisations. Image, voice, purpose, vulnerable people; distinction between authorisation and the lawful basis for data processing.
Trace provenance
Objective: Document the transformation chain. Sources, versions, metadata; a digital fingerprint proves integrity, not lawful origin.
Establish safeguards for synthetic content
Objective: Decide on distribution precautions. Deepfakes, voice imitation, explicit consent, disclosures according to context and applicable law.
Define the rules
Objective: Formalise the possible decisions. Validation, reservation, blocking and legal escalation.
Assemble the prototype
Objective: Make the checking process executable. Identifiers, documents, restricted access, retention and responsible persons.
Test anomalies
Objective: Measure the system's errors. Expired licence, incomplete consent, unknown source, missing disclosure.
Correct and retest
Objective: Verify the corrections. Contractual ambiguities, incorrect quotations, untraceable decisions.
Prepare the pilot
Objective: Organise a limited trial. Scope, human approvals, acceptance thresholds and stopping.
What you take away
- Register of assets, uses and evidence
- Decision and disclosure matrix
- Validation workflow prototype
- Test report and pilot plan
Method and assessment
- Short instructional inputs followed by immediate practice on the case study used throughout.
- Individual work followed by work in pairs, with reciprocal review of the outputs.
- Guided group discussion: what works, what needs correcting and what remains a human decision.
- Preparation: Prepare fictitious or anonymised contracts, permissions and assets; exclude all sensitive data from the exercises. Check access to a tool authorised by your organisation and gather the internal distribution rules.
Observable criteria: Each asset refers to supporting evidence or an explicit blocking issue. ; Uses are checked against the authorised durations, territories and media. ; Synthetic content has a documented decision on disclosures. ; Detected and missed anomalies are counted against the answer key. ; Each sensitive judgement has an owner and an audit trail..
Frequently asked questions
Does AI provide legal approval for the edit?
No; it assists the review, while judgements remain with humans.
Is a disclosure enough for a deepfake?
No; rights, consent and risks must also be examined.
Can we use our rushes?
The exercises use only fictitious or anonymised cases, in a tool authorised by your organisation.
Will the system be deployed in two days?
No; you leave with a tested prototype and a pilot plan.
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