EU-AIA-10-01
Data Governance
10 — Data and data governance
Develop high-risk AI systems using quality-compliant data sets
Description
Full Analysis & Evidence Requirements
Sign in to view the full obligation text, AI-generated applicability analysis, evidence checklists, and compliance mapping.
Sign In to ViewRelated Obligations
EU-AIA-10-01-superseded-20261013
Data Governance
Use quality training, validation and testing data sets
EU-AIA-10-02
Data Governance
Implement appropriate data governance and management practices
EU-AIA-10-02-superseded-20261013
Data Governance
Implement appropriate data governance and management practices
EU-AIA-10-03
Risk Management
Examine data sets for possible biases affecting health, safety, rights, or discrimination
EU-AIA-10-03-superseded-20261013
Documentation
Document relevant design choices
EU-AIA-10-04
Risk Management
Implement measures to detect, prevent and mitigate identified biases
EU-AIA-10-04-superseded-20261013
Documentation
Document data collection processes and origin
EU-AIA-10-05
Documentation
Identify and document data gaps or shortcomings
EU-AIA-10-05-superseded-20261013
Documentation
Document data preparation processing operations
EU-AIA-10-06
Data Governance
Ensure data sets are relevant, representative, error-free and complete
Map this obligation to your AI systems
ReguLume automatically maps regulatory obligations to your system inventory, identifies compliance gaps, and generates remediation plans.
Get Started