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Explainability and Transparency: The Right to Understand AI Decisions
April 10, 2026by Dr Dawkins Brown
The Explainability Imperative Explainability — the capacity to provide a meaningful account of why an AI system produced a specific output — is one of the most contested and commercially consequential dimensions of AI governance. It creates tension between the opacity of high-performing machine learning models (the ‘black box’ problem) and the legitimate expectations of...
