True, but we need to ask valid questions like "Why do we have a bunch of diversity in this vector, but not this other vector? If tech was fundamentally intolerant of diversity in general like many claim, wouldn't we lack diversity in all vectors? Why causes might contribute to the disparity between these two diversity vectors with different representations?

Overall, I rarely if ever see anyone arguing for diversity asking hard questions like "Why are there many Asians and Indians even though there aren't many Women, Hispanics/Latinos and Black people?". What are these successful identity groups doing differently that is affording them much success in being well represented or even over represented? How might the under represented groups adopt the same approaches to achieve the same success?

I'm not saying that we shouldn't solve unconscious bias as well, but I'm less inclined to first consider solutions that address unconscious bias if those solutions are proposed by someone who hasn't also considered other explanations and solutions because they aren't applying the null hypothesis in their thought process.

Also, how about some multi-variate analysis to determine which factors most greatly contribute to the diversity gap for each underrepresented group? We can't adequately fix what we don't measure and I really don't see a lot of measurement going on. For example, all successful startups understand and apply concepts of a user acquisition funnel and pipeline, but then people complain loudly in simplistic terms that the "pipeline problem is a myth". I don't understand how you can the former technique with great success and hold the latter incongruous thought in your head at the same time.

https://medium.com/life-tips/the-null-hypothesis-loves-you-a...