How many women did they have with the same qualifications as the men? How many women work the same amount of hours? How many women even applied for the job?
My local kindergarten also only has women. Guess why?
If diversity would achieve it, then do that, if homogeneity would achieve that, then do that.
Personally, I think they need to figure out what their main goal is. Is it diversification in this one area, or is it parity/supremacy in this one area and then go from there. One cannot serve two masters.
You are comparing two completely different things as if they are related.
Is there something about computers and AI that men have a knack for?
As usual, we have men outraged about a more even playing field.
- Sex differences in human neonatal social perception, Connellan Et. Al.
Boys are more interested in things, girls are more interested in people. Men preferentially grow up to work with things, women preferentially grow up to work with people. It's not about skill, its about what they instinctually find interesting.
So: “Solve the problem at the left.”†
This means for most leverage, meaning best results with least cost and least waste, intervene in a system at the earliest stage that can make a difference.
† The metaphor is assuming production lines flow left to right. RTL cultures can say "solve the problem at the right" which has the advantage of both metaphor and pun!
1. There is a relatively stable job opening with diversity requirements. The 'diverse' hire is made.
2. The 'non-diverse' candidates for the position end up not getting the job. While seemingly inconsequential on its own, this has the effect of 'non-diverse' candidates being over-represented among those who are overqualified for their current position.
3. In order to get a more suitable position for their abilities, these 'non-diverse' candidates are forced to work on higher risk projects, maybe lacking the same prestige, as the position in (1).
4. Due to their ability, these riskier projects take off. Now the risk was higher, so the reward is commensurately higher.
5. As these projects mature and grow and attract more money, they start to have job openings similar to 1.
6. Charges of discrimination are made when only 'non-diverse' candidates seemed to have benefited from this novel technology. And likely those same candidates in 2 are now forced out as more jobs like 1 are opened up in the projects they grew in 4. Then the start at step 3 again.
Personally, I have absolutely seen this play out with AI. I was in the industry before all the LLM / NVDA buzz. Many people thought it was crazy, a pipe dream, etc. Now... everyone wants in and is retconning their stories to talk about how they always supported it. Give me a break.
Maybe a weaker player with a different perspective makes the team stronger than would another homogenous superstar.
I just don’t know.
If we want different perspectives, then let's look for people that are urban vs suburban, religious vs atheist, short vs tall, active vs sedentary, sports fans vs those who would rather read a book, listeners of classical music vs country, those who served in the military vs pacifists, and so on. Why tell ourselves that the most important "diversity" we need is to be found in sex/gender and race?
