Comment by gp90
12 hours ago
How do we draw the line between whatever -ism and Bayesian inferences? You are seasoned manager for years, you found that your fellow countrymen are much more likely to follow your leadership style than any other group of different cultural background. Let's say it's a fact that you identified through years of trial and error. Based on this fact, you decide to hire only certain groups. How is this racism? How is this different from a university has a college list. Any graduate who does not graduate from the list will not have an interview with your company -- It's super narrow minded and it can considered discrimination, but is that some kind of -ism?
If you're a seasoned manager, you have learned to work across cultural differences. Being a lazy manager who doesn't want to understand how to work with others is shortsighted on its own and is not an excuse for being a racist.
> you found that your fellow countrymen are much more likely to follow your leadership style than any other group of different cultural background
Two points.
First: a good, seasoned manager adapts their leadership style to their employees. So the premise is a bit backwards.
But second, let's suppose we use something more valid like "ability to follow instructions". And suppose there are real differences in groups. You still don't stereotype on groups, because lower-performing groups still have high-performing members. So you have your interview examine the actual skill you need on an individual basis. You don't make assumptions based on group membership.
Now, for practical reasons candidates need to be reduced to a reasonable number to interview. That should be done according to personal accomplishments and experience, not groups.
The college you went to is tricky. Only hiring from a select group is not very defensible mainly because it's a bad signal. It reflects mostly your high school test scores and grades, which was years ago. On the other hand, some colleges teach in certain departments better or worse, your grades might matter and depend on the college, etc. So you need to calibrate for a bunch of achievement-based signals where the college name can matter, rather than whitelist only certain colleges.
Because, in general, there is more variance within groups than across groups, so you are generalizing that an individual person within a group is more talented / capable / whatever than an individual person from outside that group. Ergo, you are treating that second person "unfairly" due to his / her group membership or lack thereof.