| name | KSB-D10-K0041 |
| description | AI Risk Classification Frameworks: Comprehensive understanding of AI risk classification frameworks applicable to pharmacovigilance inc... |
| version | 1.0.0 |
| domain | D10 |
| domain_name | Benefit-Risk Assessment |
| type | Knowledge |
| proficiency_level | L4 |
| bloom_level | evaluate |
| triggers | ["explain ai risk classification frameworks","what is ai risk classification frameworks","evaluate ai risk classification frameworks"] |
| epa_mapping | EPA-03, EPA-05, EPA-08 |
| cpa_mapping | CPA-02, CPA-03 |
| regulatory_refs | |
KSB-D10-K0041: AI Risk Classification Frameworks
Overview
Domain: D10 - Benefit-Risk Assessment
Type: Knowledge
Proficiency Level: L4 (Proficient - Independent practice)
Bloom Level: Evaluate
Description
Comprehensive understanding of AI risk classification frameworks applicable to pharmacovigilance including CIOMS WG XIV risk-based approach, EU AI Act high-risk classification criteria, FDA risk-based validation expectations, and organizational risk assessment methodologies. Knowledge of factors determining AI risk level: safety impact, autonomy level, reversibility of decisions, and affected population characteristics.
Context
- Major Section: AI Risk Assessment and Benefit-Risk Integration
- Section: Risk-based AI Implementation
EPA Mapping
- EPA-03:3006-3008
- EPA-05:3011-3012
- EPA-08:3018-3019
CPA Pathway
Regulatory References
Instructions
When this skill is activated, Claude should:
- Demonstrate L4 proficiency in ai risk classification frameworks
- Apply evaluate level cognitive skills to evaluate the topic
- Reference relevant regulatory guidance (general PV standards)
- Connect to related EPAs: EPA-03, EPA-05, EPA-08
Key Competencies
- Comprehensive understanding of AI risk classification frameworks applicable to pharmacovigilance including CIOMS WG XIV risk-based approach, EU AI Act high-risk classification criteria, FDA risk-based validation expectations, and organizational risk assessment methodologies. Knowledge of factors determining AI risk level: safety impact, autonomy level, reversibility of decisions, and affected population characteristics.
Assessment Criteria
- Can evaluate core concepts independently
- Demonstrates understanding of regulatory context
- Applies knowledge appropriately to PV scenarios
Related Skills
- Other D10 skills in Risk-based AI Implementation
- Cross-domain integrations per DAG architecture
Generated from PV KSB Framework v1.0 | 2025-12-31
