EU AI Act Art. 50: transparency for certain AI systems

Transparency for certain AI systems: chatbot disclosure; marking and labelling of synthetic content

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-ART50. Drawn from chapter 08.

Text alternative

Clause: EU AI Act, Art. 50.
Duty holder: Provider + deployer.
Applies from: 2026-08-02, In force.
Artefact: Content labelling and machine-readable….
Layers: Layer 04, Layer 02.
Evidence record: Deployment decision record, +1 more.
Record schemas: Deployment decision record , Classification decision record .
The same topic in 20 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-ART50
Date	Step	Detail
2026-08-02	In force	marking grace for existing systems to 2026-12-02
2026-12-02	Later step	Marking grace for existing systems ends

Id

AIGE-OBL-EUAIA-ART50

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. 50

Duty holder

Provider + deployer

Authority

National MSA

Applies from

2026-08-02 In force · marking grace for existing systems to 2026-12-02

Later dates

2026-12-02 Marking grace for existing systems ends

System class

Transparency (Art. 50)

The artefact that evidences it

Content labelling and machine-readable marking (e.g. C2PA-style); chatbot disclosure banner.

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-ART50
Family	Item	Relation
Patterns	Disclosure & Notification Pipeline	Direct
Patterns	Downstream Use Register	Direct
Open controls	AIGE-CTL-AGENT-009 Approval log, bound to the call	Direct
Open controls	AIGE-CTL-AGENT-033 Approval requests a person can read	Direct
Open controls	AIGE-CTL-AGENT-015 Checkpoints on irreversible actions, failing closed	Direct
Open controls	AIGE-CTL-AGENT-034 Oversight audited per approver	Direct
Open controls	AIGE-CTL-DATA-012 Registered Downstream Consumers of Outputs	Direct
Cases	Moffatt v. Air Canada: the chatbot's answer is the company's answer	Cites the article
Cases	NYC MyCity: a government chatbot that advised breaking the law	Cites the article
Same crosswalk topic	AI Verify 1.1.6, 1.7.2, 1.1.1, 4.9.1, 4.9.2, 1.1.3	Core clause
Same crosswalk topic	CSA AICM MDS-03, MDS-04, MDS-09	Core clause
Same crosswalk topic	China AI Labelling Label Art. 4, Label Art. 5	Core clause
Same crosswalk topic	China Deep Synthesis DeepSyn Art. 16, DeepSyn Art. 17	Core clause
Same crosswalk topic	China GenAI Measures GenAI Art. 12, GenAI Art. 19	Core clause
Same crosswalk topic	CoE Convention CoE Art. 14(2), CoE Art. 15(2)	Core clause
Same crosswalk topic	EU AI Act Art. 11, Art. 13, Art. 53, Art. 86, Art. 18, Art. 43, Art. 53(1)(d), Art. 3(60)	Core clause
Same crosswalk topic	G7 Code G7 Action 3, G7 Action 7	Core clause
Same crosswalk topic	GAO AI Accountability 1.9, 3.5, 1.7	Core clause
Same crosswalk topic	GDPR Arts. 13–14, Art. 30	Core clause
Same crosswalk topic	GPAI Code Transparency 1.1, Transparency 1.2	Core clause
Same crosswalk topic	ISO 42001 7.5, A.6, A.8	Core clause
Same crosswalk topic	Korea AI Act Art. 31, Art. 34(1)(2)	Core clause
Same crosswalk topic	OECD AI Principles OECD 1.3	Core clause
Same crosswalk topic	Singapore GenAI GenAI 3, GenAI 7	Core clause
Same crosswalk topic	UK ATRS ATRS Tier 1, ATRS 2.2	Core clause
Same crosswalk topic	China Algo. Rec. AlgoRec Art. 16	Related clause
Same crosswalk topic	GB/T 45654 GB/T 45654 Content labelling	Related clause
Same crosswalk topic	NIST AI RMF MAP 1, MEASURE 2.8, MAP 1.6, MEASURE 2.9	Related clause
Same crosswalk topic	OWASP LLM LLM07:2026	Related clause

Patterns that build it

Downstream Use Register (layer 2 and 1)
Disclosure & Notification Pipeline (layer 5 and 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.

Documentation and transparency

EU AI Act Art. 11 Technical documentation (core)
EU AI Act Art. 13 Transparency and provision of information to deployers (core)
EU AI Act Art. 53 Obligations for providers of general-purpose AI models (core)
ISO 42001 7.5 Documented information (core)
ISO 42001 A.6 AI system life cycle (core)
ISO 42001 A.8 Information for interested parties (core)
China AI Labelling Label Art. 4 Explicit labels for generated content (core)
China AI Labelling Label Art. 5 Implicit (metadata) labels (core)
China GenAI Measures GenAI Art. 12 Labelling of generated content (core)
China Deep Synthesis DeepSyn Art. 16 Implicit technical labels (core)
China Deep Synthesis DeepSyn Art. 17 Conspicuous labels for confusable content (core)
GPAI Code Transparency 1.1 Drawing up and keeping up-to-date model documentation (core)
GDPR Arts. 13–14 Information to be provided to the data subject (core)
CSA AICM MDS-03 Model Documentation (core)
Korea AI Act Art. 31 Transparency: prior notice, output labelling, realistic synthetic content (core)
UK ATRS ATRS Tier 1 Summary information (core)
Singapore GenAI GenAI 3 Trusted Development and Deployment (core)
CoE Convention CoE Art. 14(2) Documentation sufficient to contest decisions; complaint to authorities (core)
OECD AI Principles OECD 1.3 Transparency and explainability (core)
G7 Code G7 Action 3 Publicly report capabilities, limitations and domains of use (core)
GAO AI Accountability 1.9 Transparency: enable external stakeholders to access information on the design, operation, and limitations of the AI system (core)
GAO AI Accountability 3.5 Documentation: document the methods for assessment, performance metrics, and outcomes of the AI system (core)
AI Verify 1.1.6 Transparency: publicly report accuracy, intended use cases, limitations, risk assessment and mitigations to stakeholders (core)
AI Verify 1.7.2 Transparency: make model or system cards publicly available where warranted by public interest (core)
NIST AI RMF MAP 1 MAP 1: Context is established and understood
NIST AI RMF MEASURE 2.8 MEASURE 2.8: Risks associated with transparency and accountability are examined and documented
China GenAI Measures GenAI Art. 19 Disclosure to regulators
China Algo. Rec. AlgoRec Art. 16 Notice that recommendation is used
GB/T 45654 GB/T 45654 Content labelling Generated-content labelling requirements (clause not verified)
EU AI Act Art. 86 Right to explanation of individual decision-making
EU AI Act Art. 18 Documentation keeping
EU AI Act Art. 43 Conformity assessment
EU AI Act Art. 53(1)(d) Public summary of the content used for training
GPAI Code Transparency 1.2 Providing relevant information
GDPR Art. 30 Records of processing activities
NIST AI RMF MAP 1.6 MAP 1.6: System requirements are elicited from and understood by relevant AI actors. Design decisions take socio-technical implications into account to address AI risks
NIST AI RMF MEASURE 2.9 MEASURE 2.9: The AI model is explained, validated, and documented, and AI system output is interpreted within its context as identified in the MAP function to inform responsible use and governance
CSA AICM MDS-04 Model Documentation Requirements
Korea AI Act Art. 34(1)(2) Explanation plan: result, main criteria, training-data overview
UK ATRS ATRS 2.2 Description and rationale
CoE Convention CoE Art. 15(2) Notification of interaction with an AI system
GAO AI Accountability 1.7 Specifications: establish and document technical specifications
AI Verify 1.1.1 Transparency: design an in-house policy on communication to consumers that articulates the principles for transparency

Content provenance and deepfakes

Korea AI Act Art. 31 Transparency: prior notice, output labelling, realistic synthetic content (core)
Singapore GenAI GenAI 7 Content Provenance (core)
G7 Code G7 Action 7 Deploy content authentication and provenance mechanisms where feasible (core)
China AI Labelling Label Art. 4 Explicit labels for generated content (core)
China AI Labelling Label Art. 5 Implicit (metadata) labels (core)
China Deep Synthesis DeepSyn Art. 17 Conspicuous labels for confusable content (core)
AI Verify 4.9.1 Safety: establish policies for content provenance: identify provenance harms such as deepfakes and trace content origin (core)
AI Verify 4.9.2 Safety: evaluate content provenance mechanisms, including the effectiveness and reliability of watermarks (core)
AI Verify 1.1.3 Transparency: labelling or disclaimers so users know when they interact with an AI system and understand content lineage (core)
EU AI Act Art. 3(60) Definition of deep fake
CSA AICM MDS-09 Model Signing/Ownership Verification
OWASP LLM LLM07:2026 Misinformation
China GenAI Measures GenAI Art. 12 Labelling of generated content

Cases that cite this article

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-AGENT-009 Approval log, bound to the call (Agent runtime profile)
AIGE-CTL-AGENT-015 Checkpoints on irreversible actions, failing closed (Agent runtime profile)
AIGE-CTL-AGENT-033 Approval requests a person can read (Agent runtime profile)
AIGE-CTL-AGENT-034 Oversight audited per approver (Agent runtime profile)
AIGE-CTL-DATA-012 Registered Downstream Consumers of Outputs (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-art50.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. 50: transparency for certain AI systems (AIGE-OBL-EUAIA-ART50). 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-art50. CC BY 4.0

BibTeX

@misc{aige2026obligation,
  author       = {Jorge García Aibar},
  title        = {{EU AI Act Art. 50: transparency for certain AI systems (AIGE-OBL-EUAIA-ART50)}},
  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-art50},
  note         = {Version 0.5.0}
}