Article 6: Classification rules for high-risk AI systems
agent:eu:ai-act:art-6 · sha256 450338e74605559a
Turnover framework under the act
- Art. 99(3): up to the higher of EUR 35,000,000 / 7 % of worldwide annual turnover
- Art. 99(4): up to the higher of EUR 15,000,000 / 3 % of worldwide annual turnover
- Art. 99(5): up to the higher of EUR 7,500,000 / 1 % of worldwide annual turnover
- The framework follows from article 99.
Affected roles
Not in the register yet.
Affected industries
Not in the register yet.
Obligations
Not in the register yet.
Article text
1. Irrespective of whether an AI system is placed on the market or put into service independently of the products referred to in points (a) and (b), that AI system shall be considered to be high-risk where both of the following conditions are fulfilled:
(a)
the AI system is intended to be used as a safety component of a product, or the AI system is itself a product, covered by the Union harmonisation legislation listed in Annex I;
(b)
the product whose safety component pursuant to point (a) is the AI system, or the AI system itself as a product, is required to undergo a third-party conformity assessment, with a view to the placing on the market or the putting into service of that product pursuant to the Union harmonisation legislation listed in Annex I.
2. In addition to the high-risk AI systems referred to in paragraph 1, AI systems referred to in Annex III shall be considered to be high-risk.
3. By derogation from paragraph 2, an AI system referred to in Annex III shall not be considered to be high-risk where it does not pose a significant risk of harm to the health, safety or fundamental rights of natural persons, including by not materially influencing the outcome of decision making.
The first subparagraph shall apply where any of the following conditions is fulfilled:
(a)
the AI system is intended to perform a narrow procedural task;
(b)
the AI system is intended to improve the result of a previously completed human activity;
(c)
the AI system is intended to detect decision-making patterns or deviations from prior decision-making patterns and is not meant to replace or influence the previously completed human assessment, without proper human review; or
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