Your point takes a narrow view on correctness and also shows why you need to take the systemic view on the issue.
The problem is not that the AI is "inaccurate". The problem is the second order effect: when you build systems on top of this AI's predictions, you cement the input social biases into future systems in a way that is very hard to remediate.
The real problem is how to avoid accidentally creating systems that amplify existing social biases.
I'm very specifically using the term "social bias" to distinguish from "bias" as a term in ML, because they are very different problems.