Results of the Mann-Whitney U test and the t-test comparing the size of class-1 blind spot for the three forms of iterated algorithmic bias with class-dependent human action probability ratio 10:1.

The effect size is calculated as (Boundary|t = 0 − Boundary|t = 200)/standard.dev. The negative effect size for filter bias shows that it increases the size of the class-1-blind spot. Random selection decreases the blind spot size, while active learning does not have a significant effect.