Model that stops learning after deployment
An insurer deploys a trained model that ranks claims by complexity. After deployment the model learns nothing new; the supplier retrains only periodically in a controlled release, so its behaviour is entirely stable between releases.
The official source remains authoritative. This is general information about obligations and not legal advice. See this object on the map
Address and citation
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- Identifier
praxikon:eu:ai-act:example:example-model-bevroren-na-uitrol- Payload hash (sha256)
8a1ada45cda845e74037fba5b19ffbe0faa783b4e5418e0db9651eca6f28137d
Citation line
Praxikon, "Model that stops learning after deployment", praxikon:eu:ai-act:example:example-model-bevroren-na-uitrol@1.0.0, dataset praxikon:sys:registry:dataset:ai-act-implementation-graph 2.1.0 (schema 1.4.0), effective_at 2026-08-08T00:00:00.000Z, known_at 2026-08-14T00:00:00.000Z, sha256 8a1ada45cda845e74037fba5b19ffbe0faa783b4e5418e0db9651eca6f28137d- Version
- 1.0.0
- Legal time (effective_at)
- 8 August 2026
- Knowledge time (known_at)
- 8 August 2026
- Closed on
- Not closed
- Topics
- examples
Review status: Placed against the official source (8 August 2026). Next check due by 4 February 2027. The check date is the knowledge date of this version; no later recheck has been recorded.
What this object links to
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The obligation this hangs off
1 of 1 shown
The object belongs to this obligation. The source line it hangs off sits there.
Source
Official fact on this object, with its locator.
Guidelines on the definition of an AI system, C(2025) 5053 final
Locator: Commission Guidelines C(2025) 5053 final, 29.7.2025, borderline cases under the definition in Article 3(1)
praxikon:eu:ai-act:source:commission-ai-system-definition-guidelines
Open official source
Via
No condition or exception recorded on this object.
Consequence
ObligationArticle 4: AI literacy
praxikon:eu:ai-act:obligation:article-4-ai-literacy
What this object is about
2 of 2 shown
The object is about this role. Undifferentiated: it does not follow that the duty rests on this role.
Source
Official fact on this object, with its locator.
Guidelines on the definition of an AI system, C(2025) 5053 final
Locator: Commission Guidelines C(2025) 5053 final, 29.7.2025, borderline cases under the definition in Article 3(1)
praxikon:eu:ai-act:source:commission-ai-system-definition-guidelines
Open official source
Via
No condition or exception recorded on this object.
Consequence
ActorDeployer
praxikon:eu:ai-act:actor:deployer
praxikon:eu:ai-act:actor:provider
What this object states
Official fact
Attributable to a named primary source, with a locator. Where they differ, the official source prevails.
The Commission guidelines on the definition of an AI system use this case to draw the line between software that does and does not fall under the regulation. The document is non-binding.
- Locator: Commission Guidelines C(2025) 5053 final, 29.7.2025, borderline cases under the definition in Article 3(1)praxikon:eu:ai-act:source:commission-ai-system-definition-guidelinesOpen official source
Our interpretation
Our own reading. It can change without the law changing, and it is not the position of a supervisory authority.
Self learning behaviour after deployment is optional and not a ground for exclusion, so a frozen model that stays entirely stable between releases does not escape the definition on that basis.
- Locator: Commission Guidelines C(2025) 5053 final, 29.7.2025, borderline cases under the definition in Article 3(1)praxikon:eu:ai-act:source:commission-ai-system-definition-guidelinesOpen official source
When this applies
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When this does not apply
No exception recorded on this object.
Referring to this object
Citation block
Copy this reference into your advice, article or file. The identifier, the version and the hash keep the statement findable later, even once the dataset has moved on.
Reference
Praxikon, "Model that stops learning after deployment", praxikon:eu:ai-act:example:example-model-bevroren-na-uitrol@1.0.0, dataset praxikon:sys:registry:dataset:ai-act-implementation-graph 2.1.0 (schema 1.4.0), effective_at 2026-08-08T00:00:00.000Z, known_at 2026-08-08T00:00:00.000Z, sha256 8a1ada45cda845e74037fba5b19ffbe0faa783b4e5418e0db9651eca6f28137d, https://www.praxikon.com/en/verkenner/example/example-model-bevroren-na-uitrol (https://www.praxikon.com/api/v1/entities?id=praxikon%3Aeu%3Aai-act%3Aexample%3Aexample-model-bevroren-na-uitrol&effective_at=2026-08-08&known_at=2026-08-08&lang=en, accessed 2026-08-25)
Short form
praxikon:eu:ai-act:example:example-model-bevroren-na-uitrol@1.0.0 (sha256 8a1ada45)
BibTeX
@misc{praxikon-eu-ai-act-example-example-model-bevroren-na-uitrol-1-0-0,
author = {{Praxikon}},
title = {Model that stops learning after deployment},
year = {2026},
version = {1.0.0},
number = {praxikon:eu:ai-act:example:example-model-bevroren-na-uitrol},
howpublished = {AI Act Change \& Evidence Graph, dataset 2.1.0, schema 1.4.0},
note = {effective_at 2026-08-08T00:00:00.000Z; known_at 2026-08-08T00:00:00.000Z; sha256 8a1ada45cda845e74037fba5b19ffbe0faa783b4e5418e0db9651eca6f28137d},
url = {https://www.praxikon.com/en/verkenner/example/example-model-bevroren-na-uitrol},
urldate = {2026-08-25},
language = {en}
}CSL JSON
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"type": "dataset",
"title": "Model that stops learning after deployment",
"container-title": "AI Act Change & Evidence Graph",
"publisher": "Praxikon",
"version": "1.0.0",
"number": "praxikon:eu:ai-act:example:example-model-bevroren-na-uitrol",
"URL": "https://www.praxikon.com/en/verkenner/example/example-model-bevroren-na-uitrol",
"language": "en",
"issued": {
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"accessed": {
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"note": "dataset praxikon:sys:registry:dataset:ai-act-implementation-graph 2.1.0; schema 1.4.0; effective_at 2026-08-08T00:00:00.000Z; known_at 2026-08-08T00:00:00.000Z; sha256 8a1ada45cda845e74037fba5b19ffbe0faa783b4e5418e0db9651eca6f28137d; retrieved_from https://www.praxikon.com/api/v1/entities?id=praxikon%3Aeu%3Aai-act%3Aexample%3Aexample-model-bevroren-na-uitrol&effective_at=2026-08-08&known_at=2026-08-08&lang=en; licence https://www.praxikon.com/nl/legal/terms"
}
]How to verify a reference later is set out in the methodology. Terms
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