From my conversations with other male employees I find that guys like to try to make statistical arguments against “preferential” treatment of women in tech, but they can’t answer high-school level statistics questions. This can be generalized to everyone regardless of background. Has there ever been an A/B test of different “strategies” of preferential treatment? If not, how can anyone make any claims in any direction? For all we know the whole industry could become more productive if we adopted some strategy X that would seem nonsensical a priori without an A/B test. I get the feeling that all current measures of productivity are based on a very narrow and ultimately harmful definition. We have entire buildings full of early 20s dudes up on adderall working insane hours and we can’t even develop systems that do simple arithmetic. In my mind diversity is not genetic but diversity of mode of thinking. The incentive structure was designed to reward said men and even with significant hiring of women in tech according to “preferential” treatment, we would end up with a bunch of miserable women and no measurable increase in “productivity.” The incentive structure was designed with the belief that it maximizes productivity, and people believe it without any evidence, in the same way medieval doctors believed in leeches because they had no statistical tools.
Congratulations you figured out the problem.
I agree with some part. In particular, Current metrics may be flawed. Do you have an objective alternative? Certainly quota incentives based entirely on genital configuration or skin color can’t be the solution. That is a hack that doesn’t solve the root cause.
We don’t ever actually need to worry about “root cause” because the root cause it likely too complex for anyone to theorize about. But it can be discovered via A/B testing. If you engage in A/B testing, then you will need to undergo a period where people are hired and promoted according to arbitrary control criteria. Otherwise you will never have clean data.
So your argument is “too hard so we don’t need to do it”? I find that absurd. Scientists spent many many years trying to find the root cause to the world, if you will. Hypothesis testing and stats were partly developed so we can get at the root cause. Funny you bring up a/b testing. Before you even do a/b testing, you need to have a metric right? Otherwise how will you evaluate effectiveness of treatment? What is the metric? And on that note, it’s clear that a/b testing hasn’t been done on these diversity policies. Why have we begun to deploy them? Why are some feminists pushing to deploy untested policies? How do you feel about deploying a model without first doing an a/b test?
Dont get yourself fired with a manifesto
*claps* Not to mention that women were historically the first computer programmers :)
Have they invented an internet as well by any chance?
Intel, So you think only big government universities and the military can invent things of worth? Typical commie. Grrrrrr.
Interesting...women quit interviewing sooner than men and therefore performed worse due to more adverse reactions to failure. My experience was 5 months of rejection before finding a great gig. I learned a lot through interviewing, especially the failures. Eventually I just got good at interviewing! Woman here. Not sure why the others kept quitting sooner...
The statistics (and especially the extrapolation) are completely meaningless. Are they measuring the testers, or are they measuring the test itself?
What the fuck? Was there a beginning, middle, and end here that I missed?
Wait, I don’t get it. Why can’t women code for 20+ hours on adderall?
If there was an actual argument made here I must have missed it
It’s a rant. I will summarize for you: “Men are dumb” Done. Could have saved a lot of typing.
Word soup. There is a lot of professional, highly qualified and vetted analysis on diversity in and out of tech, and the effects thereof on decision making and productivity and creativity of teams. “Diversity of thought” is NOT statistically tied to those things. Actual diversity is. Go buy a poli sci professor a beer and ask them to talk to you about the Cuban missile crisis. We’re close to a bunch of universities, they drink and know things. If you don’t know why I’m bringing up the Cuban missile crisis in response to a rant about diversity, then you REALLY need to go learn a thing.
JFK and Groupthink: Lessons in Decision Making https://probe.org/jfk-and-groupthink-lessons-in-decision-making/ (Remembered from undergrad psych and history...thanks for the reminder)
👏👏👏👏👏