It does not vary wildly between countries. The overwhelming majority of countries fall into the range of 10-30% of tech roles filled by women and the remaining

It does not vary wildly between countries. The overwhelming majority of countries fall into the range of 10-30% of tech roles filled by women and the remaining 70-90% by men. I don't think that a wide variety of countries falling into a band of ~20% is what most people would characterize as "varies wildly". Regardless, the cause of the disparity is not relevant to the discussion at hand. The real world population of people involved in technology is disproportionately of one gender, so an unbiased machine learning model meant to associate terms with genders will associate technology terms with men at higher rates. Sure, some may claim that the reason why disproportionately more men go into technology is because society is biased. But the AI's role was not to model a hypothetical world with no biases. Its role was to model the real world. As I wrote in my root comment, some may see value in biasing their models to achieve results that fit what they see as an ideal worldview. But the point remains: to do this is to deliberately introduce biases, not remove them.