A responsible AI framework helps organizations move from AI experimentation to accountable, trusted deployment. This blog explains five key principles: clear ownership, real-world fairness testing, explainability, privacy and security by design, and continuous post-launch assurance to reduce risk, support compliance, and build stakeholder trust.
The post Responsible AI Framework: 5 Key Principles That Build Trust first appeared on TestingXperts.
