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

The effect size is calculated as (Gini|t = 0 − Gini|t = 200)/standard.dev. The negative effect size for filter bias shows that it increases the inequality. Both active learning and random selection decrease the inequality.