Explanation Quality Specifications: Metrics, Thresholds, and Acceptance Criteria for XAI

Key Points

• This research aims to develop comprehensive quality specifications for explanations generated by explainable AI systems.
• Identified and defined key metrics for evaluating explanation quality.
• Established thresholds and acceptance criteria for each metric.
• Reviewed existing literature to support the proposed specifications.
• Proposed a framework consisting of five key metrics for explanation quality assessment.
• Established metrics thresholds that improve the reliability and applicability of explanations.
• Indicated that adherence to these criteria leads to enhanced user trust in explainable AI outputs.