Recently, I came across some threads asking why data labeling is difficult. (I have my biases as engineer) In my opinion, it's because labeling it essentially determining truth. But, truth requires context, interpretation, and domain knowledge. Sometimes it's easy (with caveats like dataset bias, labeler bias, taxonomy bias). But, for more complex labels, truth is not easily abstractable nor tractable.