Bias

Bias usually arises from training data that represents the world one-sidedly – for example when an application filter learns from past decisions in which certain groups were disadvantaged. Image generators also often reproduce stereotypes.

Countermeasures include diverse data, testing across different groups, transparent criteria, human oversight and consciously questioning results.