And many people don't. The difference is that I'm not asserting I have the one true definition, but rather recognizing that "bias" is a term with inherent political and moral content. And that pretending that this isn't (or shouldn't be) the case just because statisticians use the term in a technical setting is extraordinarily intellectually lazy.

Most people are not statisticians. No serious mathematician has ever asserted that the axioms of Real numbers settle all epistemological debates. Like-wise, I see no reason why a statistical term of art should be used to clear up the various denotations and connotations surrounding "bias" and "discrimination".

> that isn't bias in the statistical sense.

That depends on what the goal of the algorithm is.

If the goal is to accurately predict whether people will appear, then it's working.

But if the goal is to accurately predict when people will choose not to show up, then there's certainly a chance that it's not working. For example, in the case where there's some significant correlation between race and access to transportation infrastructure. (Which isn't so much the case today, but certainly was 60 or so years ago.)

The distinction between choice and circumstance isn't immaterial -- the latter is not a flight risk even if they gum up the legal system via delays. So if the judge is interpreting "90% won't show" as "90% flight risk" in the above hypothetical world, then there's a huge problem. You could argue that this is the judge's problem, and I won't necessarily disagree. But UI bugs are still bugs, and this particular form of UI bug is pretty specific to ML systems.

> And the people who try to conflate those things are doing this

Or, perhaps they're far better at mathematical modeling of complex systems than you give them credit for; e.g., by seeing ways in which locally statistically unbiased decisions can magnify the impact of bias that exists in other parts of a system.

We will never have a complete mathematical model of the world and the history of human civilization, so I don't see any reason why we should insist that all bias needs to be what a statistician calls bias in his workplace.

> The second thing is not only not bias, it's not morally objectionable

This is a separate discussion I don't want to have in this thread, because we're already barely on-topic.

But suffice it to say that conflating technical and non-technical definitions is not a reasonable defense of this position.