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EU-AI-Act

Regulation (EU) 2024/1689 — Artificial Intelligence Act

EU Version 1.0 334 obligations
Showing 1–25 of 334 obligations

Title I — General Provisions

Title II — Prohibited AI Practices

Title III — High-Risk AI Systems

Chapter 1 — Classification of AI Systems as High-Risk

Chapter 2 — Requirements for High-Risk AI Systems

Article 10. Data and data governance

13 obligations

EU-AIA-10-01 Data Governance

Use quality training, validation and testing data sets

High-risk AI systems using training techniques must be developed using training, validation and testing data sets that m

EU-AIA-10-02 Data Governance

Implement appropriate data governance and management practices

Training, validation and testing data sets must be subject to data governance and management practices appropriate for t

EU-AIA-10-03 Documentation

Document relevant design choices

Data governance practices must concern the relevant design choices for training, validation and testing data sets.

EU-AIA-10-04 Documentation

Document data collection processes and origin

Data governance practices must document data collection processes and the origin of data, including the original purpose

EU-AIA-10-05 Documentation

Document data preparation processing operations

Data governance practices must document relevant data-preparation processing operations, such as annotation, labelling,

EU-AIA-10-06 Documentation

Formulate and document assumptions about data

Data governance practices must include the formulation of assumptions, particularly with respect to the information that

EU-AIA-10-07 Data Governance

Assess data availability, quantity and suitability

Data governance practices must include an assessment of the availability, quantity and suitability of the data sets that

EU-AIA-10-08 Risk Management

Examine data for possible biases

Data governance practices must include examination for possible biases that are likely to affect health and safety, nega

EU-AIA-10-09 Risk Management

Implement bias detection, prevention and mitigation measures

Data governance practices must include appropriate measures to detect, prevent and mitigate possible biases identified i

EU-AIA-10-10 Data Governance

Identify and address data gaps and shortcomings

Data governance practices must include identification of relevant data gaps or shortcomings that prevent compliance with

EU-AIA-10-11 Data Governance

Ensure data sets are relevant, representative and error-free

Training, validation and testing data sets must be relevant, sufficiently representative, and to the best extent possibl

EU-AIA-10-12 Data Governance

Ensure data sets have appropriate statistical properties

Data sets must have appropriate statistical properties, including, where applicable, as regards the persons or groups of

EU-AIA-10-13 Data Governance

Account for geographical and contextual characteristics in data sets

Data sets must take into account, to the extent required by the intended purpose, the characteristics or elements partic

Chapter 3 — Obligations of Providers and Deployers of High-Risk AI Systems and Other Parties

Chapter 4 — Obligations of Deployers of High-Risk AI Systems

Chapter 5 — Notifying Authorities and Notified Bodies

Title IV — Transparency Obligations for Providers and Deployers of Certain AI Systems

Title V — General-Purpose AI Models

Chapter 1 — Classification Rules

Chapter 2 — Obligations for Providers of General-Purpose AI Models

Title VIII — Post-Market Monitoring, Information Sharing and Market Surveillance

Chapter 1 — Post-Market Monitoring

Chapter 2 — Sharing of Information on Serious Incidents

Title X — Codes of Conduct and Guidelines

Title XII — Penalties

Article 100. Administrative fines on Union institutions, bodies, offices and agencies

7 obligations

Article 101. Penalties for providers of general-purpose AI models

4 obligations

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