Key definitions

A machine-based system designed to operate with varying levels of autonomy, that may adapt after deployment, and that infers from the input it receives how to generate outputs such as predictions, content, recommendations or decisions that can influence physical or virtual environments.

The combination of the probability of an occurrence of harm and the severity of that harm.

Anyone who develops an AI system or general-purpose AI model, or has one developed, and places it on the market or puts it into service under their own name or trademark, whether for payment or free.

Anyone using an AI system under their authority, except in a personal non-professional activity.

An EU-based person mandated in writing by a non-EU provider to carry out its obligations under the Act on its behalf.

An EU-based person who places on the market an AI system bearing the name or trademark of someone established outside the EU.

Anyone in the supply chain, other than the provider or importer, who makes an AI system available on the EU market.

A provider, product manufacturer, deployer, authorised representative, importer or distributor.

The first making available of an AI system or general-purpose AI model on the EU market.

Supplying an AI system for first use directly to the deployer, or for own use, in the EU for its intended purpose.

The use for which the provider intends the AI system, including the context and conditions, as set out in its instructions, promotional material and technical documentation.

Use not in accordance with the intended purpose, but which may result from reasonably foreseeable human behaviour or interaction with other systems.

A component of a product or AI system that fulfils a safety function, or whose failure endangers the health and safety of people or property.

A change after market placement, not foreseen in the initial conformity assessment, that affects compliance or changes the intended purpose. It makes the modifier a provider.

All activities by providers to collect and review experience from AI systems they have placed on the market, to identify any need for corrective or preventive action.

Data used to train an AI system by fitting its learnable parameters.

Personal data from specific technical processing of a person's physical, physiological or behavioural characteristics, such as facial images or fingerprints.

An AI system for identifying or inferring emotions or intentions of people from their biometric data.

An AI system for identifying people, without their active involvement, typically at a distance, by comparing biometric data with a reference database.

An incident or malfunction of an AI system that directly or indirectly leads to death or serious harm to health, serious and irreversible disruption of critical infrastructure, infringement of fundamental rights obligations, or serious harm to property or the environment.

AI-generated or manipulated image, audio or video content resembling existing people, objects, places, entities or events that would falsely appear to a person to be authentic or truthful.

An AI model, including one trained on large data with self-supervision at scale, that displays significant generality and can competently perform a wide range of distinct tasks, and can be integrated into many downstream systems.

Capabilities that match or exceed those of the most advanced general-purpose AI models.

A risk specific to the high-impact capabilities of general-purpose AI models, with significant impact on the EU market due to their reach or actual or foreseeable negative effects on public health, safety, security, fundamental rights or society, that can spread at scale.

An AI system based on a general-purpose AI model that can serve a variety of purposes, used directly or integrated into other systems.

Skills, knowledge and understanding that let providers, deployers and affected people make informed use of AI systems and be aware of the opportunities, risks and possible harm.

A controlled framework set up by a competent authority that lets providers develop, train, validate and test innovative AI under supervision for a limited time.

A document describing the objectives, methodology, geographical, population and temporal scope, monitoring, organisation and conduct of testing in real-world conditions.