Key terms in this module(15)
Quick definitions for the terms used here. Open any term for the full entry.
- AI Model
Economic participant in the rights ecosystem, distinct from "AI tool" framing. Models are themselves trained on rights-bearing material (engaging Training Rights), and produce outputs (engaging Output Rights). The framework treats AI Models as economic actors with rights-engagement obligations on both sides of their input/output.
- Article 53
EU AI Act Article 53. Governs general-purpose AI provider obligations including training-data documentation and TDM opt-out respect.
- CDPA 1988
Copyright, Designs and Patents Act 1988 (UK). The foundational UK statute governing copyright, design rights, and related areas. Engaged by AI ingestion through Section 29A (text and data mining for non-commercial research) and Section 296ZA-ZF (technical protection measures).
- 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.
- cip.md
The framework's declaration file format. A plain-text Markdown file at https://[domain]/.well-known/cip.md declaring rights, consent, and certification status in machine-readable form. Specified in the v3.18 consolidated cip.md Specification page; AI Generation field set added v3.24.
- Collective
Rights exercised jointly by groups of creators or rights-holders, often via CMOs, collecting societies, or unions, typically for licensing at scale (music, broadcasting). Distinct from individual rights administration.
- Copyright
Legal protection for original works, the foundational rights regime the framework operates within. Per-jurisdiction variation in scope, duration, and exceptions; UK CDPA 1988 / US 17 U.S.C. / EU Information Society Directive provide the framework's primary jurisdictional anchors.
- 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.
- 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.
- DUA Act
Data (Use and Access) Act 2025 (UK). Establishes the UK's post-Brexit data governance framework including the AI training opt-out provisions. Requires either licence or explicit permission for commercial AI training; rights holders may opt out using machine-readable signals.
- Licensing
Permission to use IP under conditions, the operational mechanism for rights monetisation. Distinct from sale (which transfers ownership).
- 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.
TDM and Training Data Law
This specialist module provides in-depth analysis of text and data mining (TDM) law as it applies to AI training. It covers the three major jurisdictions and their interaction through contracts and enforcement.
UK: Data (Use and Access) Act 2025
The UK DUA Act 2025 replaced the earlier proposed TDM exception (which would have allowed commercial TDM without consent) with a balanced regime:
- A TDM exception exists for non-commercial research purposes (carried over from CDPA 1988 s.29A).
- Commercial TDM (including AI training) is subject to a rights-holder opt-out mechanism.
- The opt-out must be expressed in a machine-readable form accessible to the AI operator.
- Content carrying a valid opt-out signal is excluded from the exception — any use requires explicit licence.
The CIP framework's cip.md declaration satisfies the machine-readable requirement when deployed at the domain root with CIP-Training-Ingestion: Prohibited. The Act does not prescribe a specific format, but the Government's technical guidance references "standardised machine-readable signals" — which cip.md implements.
EU: AI Act Article 53 and Copyright Directive
The EU framework operates through two complementary instruments:
- Copyright Directive Article 4: A TDM exception for commercial purposes, subject to a rights-reservation mechanism. Rights holders who "appropriately" reserve their rights are excluded from the exception.
- AI Act Article 53: Imposes transparency obligations on general-purpose AI model providers, including a requirement to "put in place a policy to comply with Union copyright law, and in particular to identify and comply with reservations of rights expressed pursuant to Article 4(3) of Directive (EU) 2019/790".
The combined effect: AI operators must actively check for and respect rights reservations. The "appropriate" reservation for online content must be machine-readable. The CIP cip.md format satisfies this requirement.
US: Fair use four-factor analysis
The US has no statutory TDM exception or opt-out mechanism. The primary legal framework is the fair use doctrine under 17 U.S.C. § 107, which requires analysis of four factors:
- Purpose and character of the use — is the AI training use "transformative"? Courts have reached different conclusions on this.
- Nature of the copyrighted work — creative works receive stronger protection than factual works.
- Amount and substantiality of the portion used — AI training typically ingests entire works, which weighs against fair use.
- Effect on the market for the original — does AI training (and AI-generated outputs) substitute for the original? This is the most contested factor.
The NYT v. OpenAI/Microsoft litigation (1:23-cv-11195, S.D.N.Y.) is the most significant active case. The April 2025 motion-to-dismiss ruling allowed most claims to proceed, and the case is now in expert-discovery. No final ruling on fair use in AI training has been issued by a US federal court.
Jurisdiction selection in contracts
The jurisdiction clause in a content licensing contract determines which TDM regime applies. This is a strategic drafting decision:
- UK jurisdiction: Gives the rights holder access to the DUA Act 2025 opt-out mechanism and statutory remedies.
- EU jurisdiction: Gives access to the AI Act Article 53 compliance framework and Copyright Directive rights-reservation regime.
- US jurisdiction: Relies on fair use arguments (uncertain) but provides access to federal copyright statutory damages under 17 U.S.C. § 504(c).
The CIP framework recommends that UK and EU rights holders include a UK or EU jurisdiction clause in content licensing agreements, giving them access to the statutory opt-out mechanisms. US rights holders may prefer US jurisdiction for the statutory damages regime despite the fair use uncertainty.
Enforcement pathways
- UK: Statutory damages under DUA Act 2025 for breach of opt-out; additional damages under CDPA 1988 s.97(2); injunctive relief through the Intellectual Property Enterprise Court or High Court.
- EU: Injunctive relief through national courts implementing the Copyright Directive; Article 53 enforcement through national AI supervisory authorities; GDPR enforcement where personal data is involved.
- US: Statutory damages under 17 U.S.C. § 504(c) ($750–$30,000 per work, up to $150,000 for wilful infringement); actual damages and profits; injunctive relief through federal district courts.
Collecting society coordination
Collecting societies can coordinate Training Data Dividend claims at scale through their existing mandates. The CIP framework supports this through:
- CDR records that identify collecting society membership (PRS, MCPS, DACS, etc.)
- Revenue waterfall routing that can direct Training Data Dividend payments through existing collecting society infrastructure
- Collective licensing negotiations that societies can conduct on behalf of their members using CDR-documented rights exposure data
For rights holders not represented by a collecting society, the Rights Registry provides direct enforcement support and Training Data Dividend distribution.
Summary
Key Takeaways
- UK DUA Act 2025 provides a statutory TDM exception with an opt-out mechanism — machine-readable opt-out signals must be respected
- EU AI Act Article 53 and the Copyright Directive require rights reservation to be honoured — opt-out must be in machine-readable form for online uses
- US fair use analysis for AI training remains unsettled — NYT v. OpenAI and related cases are still in litigation
- Jurisdiction selection in contracts determines which TDM regime applies — this is a strategic drafting decision
- Enforcement pathways differ materially: UK statutory damages, EU injunctive relief through national courts, US damages through federal copyright litigation
- Collecting societies can coordinate Training Data Dividend claims at scale through existing mandates
Self-check
Check Your Understanding
- What does the UK DUA Act 2025 require for a valid TDM opt-out?
- How do EU AI Act Article 53 and the Copyright Directive interact on TDM?
- Why might a UK rights holder prefer UK jurisdiction in a content licensing agreement?