EC Artificial Intelligence Act
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  • EC Artificial Intelligence Act
  • EC AIA - Compliance Requirements
  • Article 09 - Risk Management System (ART09)
    • 09.01 - Risk Management System in Place
    • 09.02 - Risk Management System Capabilities and Process
    • 09.03 - Risk Management Measures
    • 09.04 - Testing
    • 09.05 - Residual Risks
    • 09.06 - Consideration of Children
    • 09.07 - Credit Institutions
  • Article 10 - Data Governance (ART10)
    • 10.01 - Define Sets
    • 10.02 - Dataset Governance Policies
    • 10.03 - Dataset Design Choices
    • 10.04 - Data Source Information
    • 10.05 - Dataset Annotations Information
    • 10.06 - Dataset Labels Information
    • 10.07 - Dataset Cleaning
    • 10.08 - Dataset Enrichment
    • 10.09 - Dataset Aggregation
    • 10.10 - Dataset Description, Assumptions and Purpose
    • 10.11 - Dataset Transformation Rationale
    • 10.12 - Dataset Bias Identification
    • 10.13 - Dataset Bias Mitigation
    • 10.14 - Dataset Bias Analysis Action and Assessment
    • 10.15 - Dataset Gaps and Shortcomings
    • 10.16 - Dataset Bias Monitoring - Ongoing
    • 10.17 - Dataset Bias Special/Protected Categories
  • Article 11 - Technical Documentation (ART11)
    • 11.01 - Technical Documentation Generated
    • 11.02 - Additional Technical Documentation
    • 11.03 - Technical Details
    • 11.04 - Development Steps and Methods
    • 11.05 - Pre-trained or Third Party Tools/Systems
    • 11.06 - Design Specification
    • 11.07 - System Architecture
    • 11.08 - Computational Resources
    • 11.09 - Data Requirements
    • 11.10 - Human Oversight Assessment
    • 11.11 - Pre Determined Changes
    • 11.12 - Continuous Compliance
    • 11.13 - Validation and Testing
    • 11.14 - Monitoring, Function and Control
    • 11.15 - Risk Management System
    • 11.16 - Changes
    • 11.17 - Other Technical Standards
    • 11.18 - Ongoing Monitoring System
    • 11.19 - Reports Signed
    • 11.20 - Declaration of Conformity
  • Article 12 - Record Keeping (ART12)
    • 12.01 - Logging Capabilities
    • 12.02 - Logging Traceability
    • 12.03 - Logging - Situations that may cause AI Risk
    • 12.04 - Logging - Biometric Systems Requirements
  • Article 13 - Transparency and provision of information to user (ART13)
    • 13.01 - Transparency of the AI System
    • 13.02 - Instructions for Use
  • Article 14 - Human Oversight (ART14)
    • 14.01 - Human Oversight mechanism
    • 14.02 - Human Oversight details
    • 14.03 - Human Oversight - Biometric Identification Systems
  • Article 15 - Accuracy, Robustness and Cybersecurity (ART15)
    • 15.01 - Accuracy Levels
    • 15.02 - Robustness Assessment
    • 15.03 - Continuous Learning Feedback Loop Assessment
    • 15.04 - Cyber Security Assessment
  • Article 17 - Quality Management System (ART17)
    • 17.01 - Quality Management System in Place
    • 17.02 - Compliance Strategy Stated
    • 17.03 - Design processes
    • 17.04 - Development and QA processes
    • 17.05 - Test and Validation Procedures
    • 17.06 - Technical Standards
    • 17.07 - Data Management Procedures
    • 17.08 - Risk Management System
    • 17.09 - Ongoing Monitoring System
    • 17.10 - Incident Reporting Procedures
    • 17.11 - Communications with Competent Authorities
    • 17.12 - Record Keeping Procedures
    • 17.13 - Resource Management Procedures
    • 17.14 - Accountability Framework
  • Article 61 - Post Market Monitoring System (ART61)
    • 61.01 - Post Market Monitoring System in Place
    • 61.02 - Data Collection Assessment
    • 61.03 - Post Market Monitoring Plan
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Article 14 - Human Oversight (ART14)

Previous13.02 - Instructions for UseNext14.01 - Human Oversight mechanism

Last updated 2 years ago

High-risk AI systems shall be designed and developed in such a way, including with appropriate human-machine interface tools, that they can be effectively overseen by natural persons during the period in which the AI system is in use.

Human oversight shall be ensured through either one or all of the following measures ():

  1. identified and built, when technically feasible, into the high-risk AI system by the provider before it is placed on the market or put into service;

  2. identified by the provider before placing the high-risk AI system on the market or putting it into service and that are appropriate to be implemented by the user.

The human oversight provisioned by the above integration/provisioning shall enable the individuals to do the following ():

  1. fully understand the capacities and limitations of the high-risk AI system and be able to duly monitor its operation, so that signs of anomalies, dysfunctions and unexpected performance can be detected and addressed as soon as possible;

  2. remain aware of the possible tendency of automatically relying or over-relying on the output produced by a high-risk AI system (‘automation bias’), in particular for high-risk AI systems used to provide information or recommendations for decisions to be taken by natural persons;

  3. be able to correctly interpret the high-risk AI system’s output, taking into account in particular the characteristics of the system and the interpretation tools and methods available;

  4. be able to decide, in any particular situation, not to use the high-risk AI system or otherwise disregard, override or reverse the output of the high-risk AI system ;

  5. be able to intervene on the operation of the high-risk AI system or interrupt the system through a “stop” button or a similar procedure.

For biometric applications for identification of natural person ():

  1. no action or decision is taken by the user on the basis of the identification resulting from the system unless this has been verified and confirmed by at least two natural persons.

Below is the list of controls/checks part of Article 14.

14.01
14.02
14.03
14.01 - Human Oversight mechanism
14.02 - Human Oversight details
14.03 - Human Oversight - Biometric Identification Systems