When they had not seen the statistical model perform on the trial runs, the majority of subjects bet on the model being more accurate in the money-earning round—they chose to tie their earnings to its performance rather than the human’s. But if they had seen it perform, the majority bet on the human. That’s despite the fact that the model outperformed the humans in every comparison, by margins ranging from 13 to 97 percent. Even when people saw the performance of both the model and the human in the trial runs, and saw that the model did better, they still tended to tie their winnings in the earnings round to the human over the model. They were more accepting of the human’s mistakes.