[eridius]

Of course, depending on why you're asking the question in the first place, a free input field can be a problem, because there can be many ways of expressing the same concept. So if you have a free-form input, you're going to need to figure out how to analyze that data to produce the groupings that you really want. But if you are capable of doing that, then absolutely, a free-form input field is the best way of avoiding unintentionally discriminating against anyone.

There's also a distinction here between questions that are objective vs subjective. Many would argue gender is objective, but they'd be wrong, it's subjective. You can't look at a person and tell them what their gender is; it's something only they can decide. So a free-form input field for Gender would be great, because everybody can feel fairly represented. But if you're asking for, say, Age, that's objective, and you can get away with letting the user choose from a set of ranges without any risk of discrimination (assuming you cover the full range of ages of all possible users).

[brudgers]

So if you have a free-form input, you're going to need to figure out how to analyze that data to produce the groupings that you really want.

That suggests the root of the problem. Presumably the model is based on identifying a particular feature of the world as worth measuring [e.g. gender]. But boxing gender [e.g. masculine | feminine ] is not a feature of the world and the boxing means that the model does not correspond to the world in regard to gender, even though that was the purpose of capturing gender in the model. The idea of "getting the groupings I want" means my methods are suboptimal scientifically. The objective truths are in the data not in my interpretation.