Figure 2
From: Explainable AI improves task performance in human–AI collaboration
Results of manufacturing experiment. The boxplots compare the task performance between the two treatments: black-box AI and explainable AI. The task performance is measured by the balanced accuracy (A) and the defect detection rate (B) based on the quality assessment of workers and the ground-truth labels of the product images. A balanced accuracy of 50% provides a naïve baseline corresponding to a random guess (black dotted line). The standalone AI algorithm attains a balanced accuracy of 95.6% and a defect detection rate of 92.9% (orange dashed lines). Statistical significance is based on a one-sided Welch’s t-test (***\(P<0.001\), **\(P<0.01\), *\(P<0.05\)). In the boxplots, the center line denotes the median; box limits are upper and lower quartiles; whiskers are defined as the 1.5x interquartile range.
