EU AI Act Art. 53(1)(c): copyright policy honouring text-and-data-mining reservations

GPAI providers put in place a policy to comply with Union copyright law, incl. identifying and complying with reservations of rights under Art. 4(3) of Directive (EU) 2019/790

By Jorge García Aibar Reviewed 2026-09-24

From clause to evidence Build the artefact, then file every output it produces as a record that names AIGE-OBL-EUAIA-ART53-1C. Drawn from chapter 08.

Text alternative

Clause: EU AI Act, Art. 53.
Duty holder: GPAI provider.
Applies from: 2025-08-02, In force.
Artefact: Versioned copyright policy.
Layers: Layer 01, Layer 02, Layer 05.
Evidence record: Vendor due-diligence response, +2 more.
Record schemas: Vendor due-diligence response , Dataset card , Model card .
The same topic in 15 other frameworks; the crosswalk section below links each clause.

When this obligation applies The first date in the row's status, then each later step: filled once its date has passed, outlined while it is still ahead of the review date.

Data table: the dates

Dates of AIGE-OBL-EUAIA-ART53-1C
Date	Step	Detail
2025-08-02	In force	Obligations from 2025-08-02; enforcement from 2026-08-02
2026-08-02	Later step	Commission enforcement powers apply
2027-08-02	Later step	GPAI models placed on the market before 2025-08-02 comply by this date (Art. 111(3))

Id

AIGE-OBL-EUAIA-ART53-1C

Instrument

EU AI Act (post-Omnibus) law

Compared side by side

ISO 42001 vs EU AI Act · NIST AI RMF vs EU AI Act

Clause

Art. 53(1)(c)

Duty holder

GPAI provider

Authority

AI Office

Applies from

2025-08-02 In force · Obligations from 2025-08-02; enforcement from 2026-08-02

Later dates

2026-08-02 Commission enforcement powers apply
2027-08-02 GPAI models placed on the market before 2025-08-02 comply by this date (Art. 111(3))

System class

GPAI model

The artefact that evidences it

Versioned copyright policy; crawler decision logs; training-data rights ledger with the reservation-check result.

What this obligation connects to Solid edges are direct relations, dashed ones looser (a case that cites the same article, a framework whose clauses only touch the topic); patterns and controls take the colour of their stack layer. Select a node to open it; the lists below give every relation in full.

Data table: every relation

Relations of AIGE-OBL-EUAIA-ART53-1C
Family	Item	Relation
Patterns	AIBOM	Direct
Patterns	Training-Data Rights Ledger	Direct
Patterns	Vendor / Model Due-Diligence Gate	Direct
Open controls	AIGE-CTL-DATA-003 Training-Data Rights Ledger Row per Source	Direct
Cases	The Garante's ChatGPT order: launch before a lawful basis	Cites the article
Same crosswalk topic	AI Verify 8.1.1, 8.2.1	Core clause
Same crosswalk topic	CSA AICM DSP-20, DSP-21	Core clause
Same crosswalk topic	China Deep Synthesis DeepSyn Art. 14	Core clause
Same crosswalk topic	China GenAI Measures GenAI Art. 7, GenAI Art. 8, GenAI Art. 11	Core clause
Same crosswalk topic	EU AI Act Art. 10, Art. 10(2)(f)–(g), Art. 4a, Art. 53, Art. 5(1)(e)	Core clause
Same crosswalk topic	GAO AI Accountability 2.1, 2.2, 2.4, 2.5	Core clause
Same crosswalk topic	GB/T 45654 GB/T 45654 Corpus security	Core clause
Same crosswalk topic	GDPR Art. 5(1)(c), Art. 25, Art. 9	Core clause
Same crosswalk topic	ISO 42001 A.7, A.7.3, A.4	Core clause
Same crosswalk topic	Singapore GenAI GenAI 2	Core clause
Same crosswalk topic	TC260 Framework 3.0 TC260 2.1.3, TC260 5.1	Core clause
Same crosswalk topic	UK ATRS ATRS 2.4.3	Core clause
Same crosswalk topic	GPAI Code Copyright 1.1–1.5	Related clause
Same crosswalk topic	NIST AI RMF MAP 2, MEASURE 2.10, MEASURE 2.11	Related clause
Same crosswalk topic	OWASP LLM LLM05:2026	Related clause

Patterns that build it

AIBOM (layer 2)
Vendor / Model Due-Diligence Gate (layer 2 and 5)
Training-Data Rights Ledger (layer 2)

The same topic in other frameworks

From the topic crosswalk: the clauses filed under the same topics as this one. Mappings are illustrative, not a claim of conformity.

Data governance

EU AI Act Art. 10 Data and data governance (core)
ISO 42001 A.7 Data for AI systems (core)
TC260 Framework 3.0 TC260 2.1.3 Data safety risks (core)
China GenAI Measures GenAI Art. 7 Training-data lawful sourcing (core)
China GenAI Measures GenAI Art. 8 Data-annotation standards (core)
China GenAI Measures GenAI Art. 11 Protection of user input and records (core)
China Deep Synthesis DeepSyn Art. 14 Training-data management (core)
GB/T 45654 GB/T 45654 Corpus security Training-corpus (data) security requirements (core) (clause not verified)
EU AI Act Art. 10(2)(f)–(g) Examination for possible biases; measures to detect, prevent and mitigate them (core)
GDPR Art. 5(1)(c) Data minimisation (core)
GDPR Art. 25 Data protection by design and by default (core)
ISO 42001 A.7.3 Acquisition of data (core) (clause not verified)
CSA AICM DSP-20 Data Provenance and Transparency (core)
UK ATRS ATRS 2.4.3 Development data specification (core)
Singapore GenAI GenAI 2 Data (core)
GAO AI Accountability 2.1 Sources: document sources and origins of data used to develop the models (core)
GAO AI Accountability 2.2 Reliability: assess reliability of data used to develop the models (core)
AI Verify 8.1.1 Data Governance: put in place measures to ensure data quality over time (core)
AI Verify 8.2.1 Data Governance: understand the lineage of data (origin, collection, curation, movement) through a data provenance record (core)
EU AI Act Art. 4a Special-category data for bias detection
ISO 42001 A.4 Resources for AI systems
NIST AI RMF MAP 2 MAP 2: Categorization of the AI system is performed
NIST AI RMF MEASURE 2.10 MEASURE 2.10: Privacy risk of the AI system is examined and documented
NIST AI RMF MEASURE 2.11 MEASURE 2.11: Fairness and bias are evaluated and results are documented
TC260 Framework 3.0 TC260 5.1 Model R&D safety guidelines
EU AI Act Art. 53 Obligations for providers of general-purpose AI models
EU AI Act Art. 5(1)(e) Prohibited: untargeted scraping of facial images
GPAI Code Copyright 1.1–1.5 Commitment 1: Copyright policy (Measures 1.1 to 1.5)
GDPR Art. 9 Processing of special categories of personal data
CSA AICM DSP-21 Data Poisoning Prevention & Detection
OWASP LLM LLM05:2026 Data and Model Poisoning
GAO AI Accountability 2.4 Variable selection: assess data variables used in the AI component models
GAO AI Accountability 2.5 Enhancement: assess the use of synthetic, imputed, and/or augmented data

Cases that cite this article

The Garante's ChatGPT order: launch before a lawful basis (2023)

Open controls that evidence it

Draft controls in the open control profiles that map to this row: each states a requirement and the evidence it must leave behind.

AIGE-CTL-DATA-003 Training-Data Rights Ledger Row per Source (Data admission and privacy profile)

Source

Chapter 08, section EU AI Act, post-Omnibus, checked against its sources on the review date above.

Machine-readable

This obligation: /api/v1/obligations/aige-obl-euaia-art53-1c.json
The register: /api/v1/obligations.json · CSV
Schema and stability promise: open data and API

Cite this obligation

García Aibar, J. (2026). EU AI Act Art. 53(1)(c): copyright policy honouring text-and-data-mining reservations (AIGE-OBL-EUAIA-ART53-1C). In AI Governance Engineering: The Thesis & Body of Knowledge (v0.5.0). https://doi.org/10.5281/zenodo.22956197. https://aigovernanceengineer.com/obligations/aige-obl-euaia-art53-1c. CC BY 4.0

BibTeX

@misc{aige2026obligation,
  author       = {Jorge García Aibar},
  title        = {{EU AI Act Art. 53(1)(c): copyright policy honouring text-and-data-mining reservations (AIGE-OBL-EUAIA-ART53-1C)}},
  howpublished = {In AI Governance Engineering: The Thesis \& Body of Knowledge},
  year         = {2026},
  version      = {0.5.0},
  doi          = {10.5281/zenodo.22956197},
  url          = {https://aigovernanceengineer.com/obligations/aige-obl-euaia-art53-1c},
  note         = {Version 0.5.0}
}