Live data from Hacker News

Silicon Valley Is Using Trade Secrets to Hide Its Race Problem

bloomberg.com

151–158 of 158 posts

Re: Silicon Valley Is Using Trade Secrets to Hide Its Race Problem

#151

Earlier quoted context omitted.

> Cancer presents differently for different races for example. Ok, but ... you've been talking about Latino as if it is a race. Does the word Latino describe a race or a culture?

That’s a complicated question I don’t have a good answer for. There is definitely a racial component to it though.

And which race would Latino represent?

Re: Silicon Valley Is Using Trade Secrets to Hide Its Race Problem

#152
post #130

Earlier quoted context omitted.

My point is not that the best way to solve these problems is through racial diversity. My point is that they inevitably crop up due a lack of awareness when you do not have diversity.

Then we disagree. I'd much rather filter based on diversity of thought/experience/knowledge if I'm looking to cover all my gaps, then base it on race where there is a chance you'll end up with group think because they all have similar thoughts/experience/knowledge.

As a practical matter I think it's pretty hard to get diversity of thought/experience/knowledge without also getting racial diversity. The two are extremely correlated, because social groups are often racially homogenous. In addition, filtering based on diversity of thought is pretty difficult. It's already so hard to interview people well...

https://www.washingtonpost.com/news/wonk/wp/2014/08/25/three...

Re: Silicon Valley Is Using Trade Secrets to Hide Its Race Problem

#153
post #151

Earlier quoted context omitted.

That’s a complicated question I don’t have a good answer for. There is definitely a racial component to it though.

And which race would Latino represent?

If you're Latino you are much much more likely to be mestizo. Which basically means it's a confusing mix of Spanish, indigenous american, and African.

https://en.wikipedia.org/wiki/Mestizo

And I'm not sure it's easy to tell to what degree/how much of a mixture you are.

Re: Silicon Valley Is Using Trade Secrets to Hide Its Race Problem

#154
post #148

Earlier quoted context omitted.

The US numbers I pulled directly from a table in the EEOC report. The EEOC report says the data is from 2014, and the article's charts cite "Latest comparable data as of 2014", so I am not sure why there are minor discrepancies in the article's US numbers unless they didn't use 2014 data.

I can't find your numbers in the link you provided. Can you point me to the table you referenced?

Figure 5.

Re: Silicon Valley Is Using Trade Secrets to Hide Its Race Problem

#155

Earlier quoted context omitted.

It's certainly true that some minorities are underrepresented in tech. A lot of the irritation you're seeing comes from the repeated accusations and implications that this is due to some unspoken policy of discrimination at tech companies. Companies can and should make an effort to ensure they're hiring a diverse range of people. However, it needs to be done with the bigger picture in mind - otherwise it becomes a de…

So policies that result in under-representation of POC are neutral, but changing hiring & retention practices to improve diversity is a defacto quota system?

If it is literally a quota system...then yes, it is a quota system.

Re: Silicon Valley Is Using Trade Secrets to Hide Its Race Problem

#156

Earlier quoted context omitted.

Well, right. Corporations internally work towards their diversity goals, which are sensibly based on the pipeline and aim to eliminate bias in hiring. That's why they don't want to publicize their numbers; they know people like the Bloomberg reporter who wrote this article will incorrectly try to measure their efforts against the total number of minorities in the US.

The hiring pipeline is discussed explicitly in the article, and comparison to national demographics is legitimate.

Comparing hiring to national demographics is not legitimate. You should compare hiring to national graduates with CS degrees, controlling for institution. That will tell you if there is discrimination in the hiring step. If you want to see if there is discrimination in entrance to CS programs, you go a step earlier, etc. And you keep walking back until you find the source of the discrepancy. Where do women get off the CS pipeline? Is it at the hiring filter? The college major filter? Somewhere in high school? Even earlier? It's disingenuous to place the blame for the entire pipeline at the feet of the entities at the very end. Somewhere there is a bias, but it isn't necessarily at the corporate level.

Re: Silicon Valley Is Using Trade Secrets to Hide Its Race Problem

#157
post #151

Earlier quoted context omitted.

And which race would Latino represent?

If you're Latino you are much much more likely to be mestizo. Which basically means it's a confusing mix of Spanish, indigenous american, and African. https://en.wikipedia.org/wiki/Mestizo And I'm not sure it's easy to tell to what degree/how much of a mixture you are.

Judging by [0], the whites are most prevalent non mixed ethnicity in South America and if you also consider that Mestizos and Mulatos are half white that also means that means that large majority of the population is white to some degree.

[0] https://en.wikipedia.org/wiki/Demographics_of_South_America#...

Re: Silicon Valley Is Using Trade Secrets to Hide Its Race Problem

#158
post #157

Earlier quoted context omitted.

If you're Latino you are much much more likely to be mestizo. Which basically means it's a confusing mix of Spanish, indigenous american, and African. https://en.wikipedia.org/wiki/Mestizo And I'm not sure it's easy to tell to what degree/how much of a mixture you are.

Judging by [0], the whites are most prevalent non mixed ethnicity in South America and if you also consider that Mestizos and Mulatos are half white that also means that means that large majority of the population is white to some degree. [0] https://en.wikipedia.org/wiki/Demographics_of_South_America#...

Two things

1) if the first table is self identified data I would strongly expect it to underrepresent how many people are mixed. Unless you have gotten genetic testing, it’s hard to know like I mentioned. And there is social pressure to identify as white. 2) Even then, whites are still pretty much a minority in most countries, especially the ones that have more significant immigration to the US.

Post reply on HN