This paper proposes the RIGHT Framework, a comprehensive validity assessment framework for AI systems, addressing the multifaceted nature of validity in AI assessment. The framework includes five dimensions: Reliability, Integration, Generalization, Holistic validity, and Transparency, each with quantitative metrics for objective assessment.
Key findings
Proposes the RIGHT Framework for AI evaluation validity assessment.
Develops quantitative metrics for each of the five validity dimensions.
Presents a methodology for implementing these metrics with measurement protocols and aggregation functions.
Demonstrates the framework’s applicability through a detailed validation plan.
Limitations & open questions
The framework's effectiveness in diverse AI applications and domains needs further empirical validation.