Key terms in this module(14)
Quick definitions for the terms used here. Open any term for the full entry.
- CDR
Core Data Record. A structured record capturing key information about a creative asset, including the rights, consent, and provenance information attached to it. The CDR is the primary provenance infrastructure for AI pipeline entry.
- Data Dividend
Payment for use of personal or contributed data, broader than Training Data Dividend (which is AI-specific). Includes general data-monetisation patterns where individuals receive remuneration for their contributed data.
- Derivative
Transformation, adaptation, remixing, translation, or AI-generated variation based on the original. The foundational rights category for AI-generated outputs derived from training data.
- Distribution
Dissemination, sale, licensing, or transfer of copies to the public. Includes movement of content through APIs, feeds, search, recommendation systems, syndication. Foundational rights category.
- Music
Audio compositions and recordings, sector category engaging neighbouring rights, multiple CMO administration, and v3.20 CR-AII music-vertical calibration (50% / 25% / 70% threshold profile).
- NILP
Name, Image, Likeness, Publicity. Rights over the commercial use of a person's identity markers, name, face, voice, persona, likeness. Engaged by voice cloning, deepfakes, AI-generated likenesses, synthetic impersonation.
- NILP Downstream Obligation
The framework's position that commercial deployers of AI-generated identity content carry the rights-holder claim where the deployment proceeds without explicit consent verification. The obligation flows downstream from training-data ingestion through output generation to commercial deployment.
- Output
Generated content instance, text, image, audio, action. The single-instance unit produced by inference.
- Platform
System that hosts models + applies governance, policies, ranking logic, and monetisation rules. Distinct from Model Provider (which makes the model) and Host (which serves it).
- Provenance
The documented history of where content comes from and how it has been transformed. Captured in the Core Data Record and evidenced through the Rights Registry.
- Revenue Waterfall
Order of payment distribution, the contractual or algorithmic sequence determining who gets paid in what order from a revenue stream. Operationally significant for multi-contributor outputs.
- Rights Registry
The verification system used to confirm rights-related status, credentials, and recognised outputs. Five capabilities: (1) lookup by CDR ID, (2) historical verification at timestamp, (3) operator-identity verification, (4) provenance-chain resolution, (5) bulk URL-to-rights-position lookup.
- Training Data
Inputs used to train models, the operational input category that engages training-data liability. CIP-AI-Training-Data-Source field declares the operator's position.
- Training Data Dividend
TDD. The compensation owed to a rights holder whose creative work has been used as training data. CIP's training markets pay per contribution path rather than per dataset inclusion.
6.1 The Training Data Dividend
The Training Data Dividend is the compensation owed to a rights holder whose creative work has been used as AI training data. The CIP approach is pay-per-contribution-path: each creator is compensated based on their specific contribution to the training corpus, not just dataset inclusion.
This requires CDR infrastructure — the Rights Registry tracks which assets went into which training corpus, enabling asset-level compensation rather than dataset-level approximation.
6.2 The revenue waterfall
When a licensed training event occurs, compensation flows through the revenue waterfall:
- Platform payment — the AI company pays a Training Data Dividend to the rights pool
- Pool distribution — distributed to individual rights holders based on CDR provenance records
- Rights holder receipt — the creator or their authorised representative receives payment
- Reporting — automated reporting through the Rights Registry records the payment event
For creators working through agencies, the waterfall may include an intermediary step where the agency receives payment and distributes to the creator under the terms of their representation agreement.
6.3 NILP Downstream Obligations as royalty triggers
When AI-generated content involving a person's identity is commercially distributed, the NILP Downstream Obligation creates a royalty trigger that runs from the AI company through to the rights holder — regardless of how many commercial intermediaries were involved.
A brand that used an AI platform to generate a voice advertisement using a synthesised celebrity voice owes a NILP Downstream Obligation to that celebrity — even if the brand paid the AI platform and none of those payments reached the celebrity.
6.4 Mechanical licences in AI contexts
A mechanical licence is the traditional royalty mechanism for reproducing a musical composition. In AI contexts, mechanical licences may apply where AI-generated music is based on a specific copyrighted composition or where an AI output is determined to be a derivative work.
Summary
Key Takeaways
- Training Data Dividend: compensation per contribution path, not per dataset inclusion
- Revenue waterfall: AI company → pool → rights holders via CDR provenance records
- NILP Downstream Obligations create royalty triggers for commercial identity use in AI outputs
- CDR registration is the practical prerequisite for receiving Training Data Dividend payments
Self-check
Check Your Understanding
- What is the Training Data Dividend?
- What compensation model does the CIP framework use for the Training Data Dividend?
- In the CIP revenue waterfall, what enables asset-level compensation to individual rights holders?
- A brand uses an AI platform to generate advertising with a synthesised celebrity voice. Who bears the NILP Downstream Obligation?
- What is the practical prerequisite for receiving Training Data Dividend payments?