When the task is choosing between two choices (in this case: AI/Human), the worst you can do in average is not 0% correct, but 50%, which is a coin flip. If a model—whether it's an ML one or is inside human's mind—achieves 40% accuracy in a binary prediction, it can increases the accuracy to 60% by just flipping the answers.
The more interesting numbers are precision and recall, or even better, a confusion matrix. It might turn out that the false AI score and the false human score (in the sense of false positive/negative) differ significantly. That would be a more interesting report.