[AnthonyMouse]

> How do we correct for the bias if we don't know what the unbiased state would look like?

The goal isn't to choose some specific gender balance and then take whatever steps necessary to produce it, it's to eliminate unfair bias. The way to do that is to find it, not indirectly by looking at ratios, but directly by actually finding it.

High school teachers who say things like "women are no good at computers" to young women should be reprimanded etc. Poll women who didn't go into tech and ask them why not, and if any of the reasons are unjust then change them.

If no one can find anything like that then the gender balance at that point is what it's supposed to be. We're obviously not there yet, but the way we know is because we keep finding things like that, not because the gender balance is uneven.

[OscarCunningham]

I agree. But I notice that most discussions on sexism in technology companies focus on the outcomes; gender ratios and pay gaps. It would be interesting to try to measure the bias directly. Hide a bunch of microphones in offices and see if the number of sexist comments is larger at Google than it is at a law firm or a hospital.

Perhaps somebody has already done this. What would be the correct search terms?

[AnthonyMouse]

> But I notice that most discussions on sexism in technology companies focus on the outcomes; gender ratios and pay gaps.

It's a specific instance of the more general manage-by-metrics disease. The thing you actually want is hard to measure, but it correlates with something that is easy to measure. So instead of doing the hard work to understand what is actually happening in detail, they measure the easy thing and optimize for that instead. Even though doing that frequently breaks the original correlation.

The result is the bureaucracy edition of a paperclip maximizer. You get what you measure instead of what you really want. Or bang your head against the wall, if the thing you measured is actually stickier than the real problem.

> t would be interesting to try to measure the bias directly. Hide a bunch of microphones in offices and see if the number of sexist comments is larger at Google than it is at a law firm or a hospital.

To some extent this is just the same disease. Is sexism supposed to be alright if it turns out there are equally large amounts in both places? Should we be satisfied that it's the root of the problem if there is very little at Google but even less somewhere else?

Stop trying to measure things against other things and just consider them in their own right. Sexism is bad regardless of how common it is. You don't fight it because there is more of it over here than over there, you fight it everywhere because it exists when it shouldn't exist.

[OscarCunningham]

Sure, but knowing where it was most prevalent might give us information about how to promote a better culture.