By name: "KSB-D08-K0041" description: "Algorithmic Bias Detection in PV Systems: Recognition and identification of algorithmic bias in pharmacovigilance AI systems including selecti..." version: "1.0.0" domain: "D08" domain_name: "Signal Detection & Management" type: "Knowledge" proficiency_level: "L3" bloom_level: "analyze" triggers: - "explain algorithmic bias detection in pv systems" - "what is algorithmic bias detection in pv systems" - "analyze algorithmic bias detection in pv systems" epa_mapping: "EPA-04, EPA-05" cpa_mapping: "CPA-02" regulatory_refs: ""
KSB-D08-K0041: Algorithmic Bias Detection in PV Systems
Overview
Domain: D08 - Signal Detection & Management Type: Knowledge Proficiency Level: L3 (Competent - Minimal supervision) Bloom Level: Analyze
Description
Recognition and identification of algorithmic bias in pharmacovigilance AI systems including selection bias from training data, confirmation bias in model outputs, demographic bias affecting underrepresented populations, and reporting bias from historical data patterns. Includes understanding of bias propagation mechanisms, intersectionality effects, and cumulative bias amplification across ML pipelines.
Context
- Major Section: AI Integration and Advanced Analytics
- Section: AI Fairness and Equity in Signal Detection
EPA Mapping
- EPA-04:3009-3010
- EPA-05:3011-3012
CPA Pathway
- CPA-02
Regulatory References
- General PV competency
Instructions
When this skill is activated, Claude should:
- Demonstrate L3 proficiency in algorithmic bias detection in pv systems
- Apply analyze level cognitive skills to analyze the topic
- Reference relevant regulatory guidance (general PV standards)
- Connect to related EPAs: EPA-04, EPA-05
Key Competencies
- Recognition and identification of algorithmic bias in pharmacovigilance AI systems including selection bias from training data, confirmation bias in model outputs, demographic bias affecting underrepresented populations, and reporting bias from historical data patterns. Includes understanding of bias propagation mechanisms, intersectionality effects, and cumulative bias amplification across ML pipelines.
Assessment Criteria
- Can analyze core concepts independently
- Demonstrates understanding of regulatory context
- Applies knowledge appropriately to PV scenarios
Related Skills
- Other D08 skills in AI Fairness and Equity in Signal Detection
- Cross-domain integrations per DAG architecture
Generated from PV KSB Framework v1.0 | 2025-12-31