3 ms·

I'm sorry, but this is completely wrong. In 2021, 9% of computer science graduates were black (1). 18% were women (2). These numbers are the ceiling of what yo

I'm sorry, but this is completely wrong. In 2021, 9% of computer science graduates were black (1). 18% were women (2). These numbers are the ceiling of what you might expect for a senior pipeline, since women attrit at a higher rate than men (3). In a typical senior hiring pipeline for a Microsoft-scale company, while you'll have loads of applicants, you might have a dozen who make it through initial screening and are at least qualified on paper. I've been a hiring manager at companies slightly larger, and slightly smaller, than MS, and this was true at both. So of those 12, you'd expect perhaps 1 to be black, and perhaps 2 to be women - optimistically. But every company, but especially high-profile fortune 100s, are trying to increase their D&I numbers. Qualified minority candidates rarely come through applications - instead, they're recruited, since everyone wants to somehow turn that 18% into 30% in order to get their D&I-linked bonus. Blaming a hiring manager or company for their "pipeline" when they fail to hit impossible targets is absurd, and mathematically dishonest. 1. https://www.pewresearch.org/science/2021/04/01/stem-jobs-see-uneven-progress-in-increasing-gender-racial-and-ethnic-diversity/ https://www.pewresearch.org/science/2021/04/01/stem-jobs-see... 2. https://www.computerscience.org/resources/women-in-computer-science/ https://www.computerscience.org/resources/women-in-computer-... 3. http://edge.berkeley.edu/wp-content/uploads/2017/08/WomenInTech.pdf http://edge.berkeley.edu/wp-content/uploads/2017/08/WomenInT...

runako 4y ago
There are a few common problems in your analysis: - as is frequently noted here, programming positions do not always require CS degrees. - companies that produce software typically are composed of lots of roles. Microsoft has 100k engineers, but even more of their staff is not engineers. (That is: less than half the jobs at Microsoft are "engineers," and some of their engineers do not have CS degrees.) Many/most of those other roles translate quite well into tech. Just to take a few functional examples, the Finance function under the CFO, the HR function under the top people officer, the sales function, and the marketing function are not typically run by CS grads or staffed with programmers. Companies do not have to hit their DEI targets solely in their Engineering functions. But back to your assertions, you seem to agree with me. > So of those 12, you'd expect perhaps 1 to be black, and perhaps 2 to be women - optimistically. Yes, if this is your slate for a programming role (again, assuming you are not somehow running a pipeline that somehow misses the enormous Latino population), you are probably doing okay. (Microsoft et. al. are able to aim for better than okay, but that's a business decision.) Edit: I want to expand a little on the Latino/Hispanic component as well, as it's common in debates on this site to exclude them. But add them back in using the numbers on your first link. So we could expect 1 Black applicant, 1 Latino applicant, and 2 women (optimistically!). That's a third of your set of 12, using your data sources, for a programming role. This is optimistic, but nobody managing a F100 is asking their leadership to do easy things. But it does sound like you generally agree that if you get sets of 12 applicants and they are all consistently white men in each set that there is a process defect? Similarly, if you are hiring for another role, your definition of a "diverse" set of applicants would be different. > Qualified minority candidates rarely come through applications - instead, they're recruited This is the activity that management is trying to encourage. Given industry history, it is not surprising that companies have to put in extra effort to try to change the perception of who is welcome. Microsoft is not new to this, having spent tons of money rehabilitating the image of Windows as an insecure, unreliable OS. Fixing a business process takes work, this is not surprising.
- strix_varius 4y ago
  > But add them back in using the numbers on your first link. So we could expect 1 Black applicant, 1 Latino applicant, and 2 women (optimistically!). That's a third of your set of 12, using your data sources, for a programming role. Let's please keep this conversation mathematically honest. I don't know if you're intentionally trying to misrepresent statistics, or if you don't understand them, but: - for three non-mutually-exclusive groups (black, latino, female) - given participation in a set (1, 1, 2) - you cannot sum their independent participation (4) to yield "a third" Beyond that, you appear to intentionally miss the key terms "ceiling" and "optimistically." Given a sample size of one pipeline (the OP), if you optimistically might get a single applicant that meets a given DI quota, it's very likely that you'll get zero. The original article explicitly stated zero, and the numbers make it clear that zero is a very likely result. That's the trouble with small sample sizes. I'm not sure what point you're trying to make by arguing that, in some other circumstance, maybe it could have been one... or even two!
  - runako 4y ago
    > given participation in a set (1, 1, 2) When the set is of 12, that's 4 of 12, which is exactly one third, assuming independent participation (which obviously is what makes the number optimistic/ a ceiling). > Given a sample size of one pipeline Fair! If the OP only ever hires one person, you are correct. At Microsoft's scale, they are more like "the house" at a casino, and so their ratios should more closely approximate the population. I am making the larger point that yes, in one instance, this hiring manager could have experienced a challenge building a diverse pipeline, but that this experience is not generalizable to Microsoft or the industry as a whole. And the related takeaway that if your pipeline is routinely not presenting you with the significant plurality represented by "diverse" candidates, then you have a solvable process problem.
    - strix_varius 4y ago
      > When the set is of 12, that's 4 of 12, which is exactly one third, assuming independent participation (which obviously is what makes the number optimistic/ a ceiling). I think this misunderstanding of statistics may be at the core of our disagreement. Yes, 4 is one-third of 12. No, you cannot expect overlapping, non-mutually-exclusive sub-populations of 9% and 18% to equal 27% of a total population. If you're interested in learning why, read (1), but the TL;DR is: given three people, A: black female, B: white male, C: white male, if you sum sub-populations as you're trying to do, you'll get (1 black + 1 female = 2) from a population of 3, and you'll extrapolate (incorrectly) that 2/3rds of this population meets your criteria. I hope that helps explain why your expectation of the gender & racial diversity of CS graduates is inaccurate. 1. https://stats.libretexts.org/Bookshelves/Introductory_Statistics/Book%3A_Introductory_Statistics_(OpenStax)/03%3A_Probability_Topics/3.03%3A_Independent_and_Mutually_Exclusive_Events https://stats.libretexts.org/Bookshelves/Introductory_Statis...

runako 4y ago

There are a few common problems in your analysis: - as is frequently noted here, programming positions do not always require CS degrees. - companies that produce software typically are composed of lots of roles. Microsoft has 100k engineers, but even more of their staff is not engineers. (That is: less than half the jobs at Microsoft are "engineers," and some of their engineers do not have CS degrees.) Many/most of those other roles translate quite well into tech. Just to take a few functional examples, the Finance function under the CFO, the HR function under the top people officer, the sales function, and the marketing function are not typically run by CS grads or staffed with programmers. Companies do not have to hit their DEI targets solely in their Engineering functions. But back to your assertions, you seem to agree with me. > So of those 12, you'd expect perhaps 1 to be black, and perhaps 2 to be women - optimistically. Yes, if this is your slate for a programming role (again, assuming you are not somehow running a pipeline that somehow misses the enormous Latino population), you are probably doing okay. (Microsoft et. al. are able to aim for better than okay, but that's a business decision.) Edit: I want to expand a little on the Latino/Hispanic component as well, as it's common in debates on this site to exclude them. But add them back in using the numbers on your first link. So we could expect 1 Black applicant, 1 Latino applicant, and 2 women (optimistically!). That's a third of your set of 12, using your data sources, for a programming role. This is optimistic, but nobody managing a F100 is asking their leadership to do easy things. But it does sound like you generally agree that if you get sets of 12 applicants and they are all consistently white men in each set that there is a process defect? Similarly, if you are hiring for another role, your definition of a "diverse" set of applicants would be different. > Qualified minority candidates rarely come through applications - instead, they're recruited This is the activity that management is trying to encourage. Given industry history, it is not surprising that companies have to put in extra effort to try to change the perception of who is welcome. Microsoft is not new to this, having spent tons of money rehabilitating the image of Windows as an insecure, unreliable OS. Fixing a business process takes work, this is not surprising.

strix_varius 4y ago
> But add them back in using the numbers on your first link. So we could expect 1 Black applicant, 1 Latino applicant, and 2 women (optimistically!). That's a third of your set of 12, using your data sources, for a programming role. Let's please keep this conversation mathematically honest. I don't know if you're intentionally trying to misrepresent statistics, or if you don't understand them, but: - for three non-mutually-exclusive groups (black, latino, female) - given participation in a set (1, 1, 2) - you cannot sum their independent participation (4) to yield "a third" Beyond that, you appear to intentionally miss the key terms "ceiling" and "optimistically." Given a sample size of one pipeline (the OP), if you optimistically might get a single applicant that meets a given DI quota, it's very likely that you'll get zero. The original article explicitly stated zero, and the numbers make it clear that zero is a very likely result. That's the trouble with small sample sizes. I'm not sure what point you're trying to make by arguing that, in some other circumstance, maybe it could have been one... or even two!
- runako 4y ago
  > given participation in a set (1, 1, 2) When the set is of 12, that's 4 of 12, which is exactly one third, assuming independent participation (which obviously is what makes the number optimistic/ a ceiling). > Given a sample size of one pipeline Fair! If the OP only ever hires one person, you are correct. At Microsoft's scale, they are more like "the house" at a casino, and so their ratios should more closely approximate the population. I am making the larger point that yes, in one instance, this hiring manager could have experienced a challenge building a diverse pipeline, but that this experience is not generalizable to Microsoft or the industry as a whole. And the related takeaway that if your pipeline is routinely not presenting you with the significant plurality represented by "diverse" candidates, then you have a solvable process problem.
  - strix_varius 4y ago
    > When the set is of 12, that's 4 of 12, which is exactly one third, assuming independent participation (which obviously is what makes the number optimistic/ a ceiling). I think this misunderstanding of statistics may be at the core of our disagreement. Yes, 4 is one-third of 12. No, you cannot expect overlapping, non-mutually-exclusive sub-populations of 9% and 18% to equal 27% of a total population. If you're interested in learning why, read (1), but the TL;DR is: given three people, A: black female, B: white male, C: white male, if you sum sub-populations as you're trying to do, you'll get (1 black + 1 female = 2) from a population of 3, and you'll extrapolate (incorrectly) that 2/3rds of this population meets your criteria. I hope that helps explain why your expectation of the gender & racial diversity of CS graduates is inaccurate. 1. https://stats.libretexts.org/Bookshelves/Introductory_Statistics/Book%3A_Introductory_Statistics_(OpenStax)/03%3A_Probability_Topics/3.03%3A_Independent_and_Mutually_Exclusive_Events https://stats.libretexts.org/Bookshelves/Introductory_Statis...