It is stated that they use the same annotators that trained/filtered chatGPT’s output. I would assume its a rather large group (my company has 10 auditors in Nicaragua). The label biases are mostly stemming from that group and - as suggested - could be removed by using experts in each field to annotate the labels. But given some responses here by experts, I am sure those expert labels would have their very own biases :p