EU-AIA-15-05
Requirement
15 — Accuracy, robustness and cybersecurity
Eliminate or reduce biased feedback loops in learning systems
Description
High-risk AI systems that continue to learn after being placed on the market or put into service must be developed to eliminate or reduce as far as possible the risk of possibly biased outputs...
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-15-01
Requirement
Design and develop for appropriate accuracy, robustness and cybersecurity
EU-AIA-15-02
Transparency
Declare accuracy levels and metrics in instructions
EU-AIA-15-03
Requirement
Ensure resilience to errors, faults and inconsistencies
EU-AIA-15-04
Requirement
Implement technical and organisational resilience measures
EU-AIA-15-06
Requirement
Address feedback loops with appropriate mitigation measures
EU-AIA-15-07
Requirement
Ensure resilience against unauthorized third-party alteration
EU-AIA-15-08
Requirement
Implement appropriate cybersecurity technical solutions
EU-AIA-15-09
Requirement
Address AI-specific vulnerabilities with technical solutions
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