Goal

A space to discuss thougtfully and amicably, if the topic of discrimination and bias should be addressed in the documentation (examples and user guide):

• bias in model
• bias in data

Non Goal

Endless and pointless discussions. So please, use every word wisely and sparingly.

Possible Solutions

Mention in example X that the data may contain bias and reference a link to a good source for further insights.
Discover model bias in example Y for a certain feature subspace and investigate a little.

References

The examples Poisson regression and non-normal loss and Tweedie regression on insurance claims use an insurance dataset, example Common pitfalls in interpretation of coefficients of linear models uses a wages dataset.
Some concern where pointed out in #16648 (comment).