Results of the Mann-Whitney U test and t-test comparing the size of the all-classes-blind spot for the three forms of iterated algorithmic bias.

The effect size is conducted as (BlindSpot|t = 0 − BlindSpot|t = 200)/standard.dev. The negative effect size shows that filter bias increases the class-1-blind spot size. On the other hand, both active learning and random selection have no significant effect.