The fundamental problem with most stereotypes is that there is generally much more information available by asking the individual.
eg. Instead of assuming women are more conservative, just ask the candidate, ask questions surrounding their risk profile.
There are great tools one can use from the finance industry to assess an individuals risk profile and tailor an employment package that meets their profile. Some candidates like myself (a guy) want more time off because we'd rather spend time with family than coding.
If you can create a tailored work environment you'll have no problem attracting talent that's diverse, instead of just a bunch of people who like to work 80 hours a week.
If you offer one size fits all employment you will hire people only for who that size fits. If you offer bespoke employment you'll hire bespoke individuals.
In a world of perfect information, that would work. In a Bayesian world (ours), it doesn't work.
Say that you have two types of widgets, widget A and widget B. Both have tolerances that fall along the same normal distribution but with different means. The mean for widget A is off by 0.1mm, and the mean for widget B is off by 0.2 mm.
Now, say that you measure each widget before accepting it, using a perfect measuring function. In this case, it doesn't matter whether you use widget A or widget B.
However, in the real world, you have an imperfect measuring function. Say that it gives you an answer along a normal distribution with some standard deviation.
Does this make the case for widget A or widget B different? Yes, you'll have more widgets fall within tolerances if you only use widget A.
To further improve the model, you would want to know the rejection cost of using an incorrectly sized widget and the supply-demand costs involved in only using widgets of type A. The results of the optimization problem would tell you how much of widget A versus widget B to use.
eg. Instead of assuming women are more conservative, just ask the candidate, ask questions surrounding their risk profile.
There are great tools one can use from the finance industry to assess an individuals risk profile and tailor an employment package that meets their profile. Some candidates like myself (a guy) want more time off because we'd rather spend time with family than coding.
If you can create a tailored work environment you'll have no problem attracting talent that's diverse, instead of just a bunch of people who like to work 80 hours a week.
If you offer one size fits all employment you will hire people only for who that size fits. If you offer bespoke employment you'll hire bespoke individuals.