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Is There a Bias in Data?
Trying to articulate whether someone is a good or bad labeller is fundamentally the wrong approach. All our labels are inherently probalistic by nature, so you can have probabilities at our hundred % or zero%. But that allows for a hundred and one degrees of freedom in your label space which then hopefully yields a model that will learn a richer relationship between the input and the output. So it's a long way of saying, yea, i think you could build better hand labelling systems, i just haven't seen it yet.