Bridging the Gap in XAI-Why Reliable Metrics Matter for Explainability and Compliance
PositiveArtificial Intelligence
- The article discusses the importance of reliable explainability in AI governance, emphasizing the need for standardized evaluation metrics to assess trustworthiness in high
- Standardized metrics are proposed as governance primitives that can enhance auditability and accountability within AI systems, crucial for private oversight by auditors, insurers, and certification bodies.
- The ongoing debate around AI transparency highlights the potential risks and benefits of disclosing AI roles in various applications, raising concerns about brand quality and consumer trust while underscoring the necessity for responsible AI practices.
— via World Pulse Now AI Editorial System





