How much do Big Tech companies discriminate against white people?
It depends how many white people they hire and whether open borders is discrimination
Big Tech companies are famously woke and diverse, meaning our prior that they discriminate against white people in hiring to some degree should be high. More than 70% of their workers are on H1B visas, and this depresses the wages of white software engineers by as much as $90,000 per year. From reasonable starting assumptions, this can already be construed as anti-white discrimination. But from open-borders assumptions, who is to say they just aren’t hiring the best talent from around the world? This is what we will address in this article, using data on American and world demographics and population IQ.
How white is Big Tech?
In this article we will mostly focus on FAANG companies. This is what we mean by “Big Tech.” These are the top companies, with top pay, who claim to hire the world’s top talent for software engineering.
Obviously, some FAANG companies may be whiter than others. Most do not have demographic information available. However, I have worked at one FAANG company, and at that company I could see a directory of all employees.
The racial makeup of that company was as follows:
24% white
32% Indian
42% East Asian
2% other races
Note that the top positions were whiter, and these workers were older. I’m talking about vice presidents and so on. The racial makeup of non-management software developers was as follows:
12% white
41% Indian
44% East Asian
3% other races
It would seem FAANG has gotten more racist over time, which is not surprising. Software developers in the 90s were extremely privileged, making millions off of trivial websites, free of wage depression from Asian mass immigration.
Data which appears to be from Meta backs this up:
Look how the white% has dropped. Also note that in this data, it is unclear if white includes Indians, who are Caucasoids technically speaking. So the real “white” percent is likely less than 7% here, down from over 27% in 2014 before the Great Awokening.
Above are Google’s numbers, which tell a similar story.
How smart are Asians and Indians?
To see if Asians and Indians should be the overwhelming majority of FAANG software engineers, we need to estimate their IQ distributions.
It is currently popular to believe in Smart Asian Theory, the idea that Asians are significantly higher IQ than whites. This is a strange idea, since India and China are shit-holes with very little intellectual track record. This would be like if Ghana were allegedly 104 IQ. Something is wrong here.
Whereas Smart Jew Theory is backed up by Jewish invention (and, in particular, it is European Ashkenazi Jews which are responsible for this), Chinese and Indians hardly invent anything ever.
One way of dealing with the Asian IQ paradox is assigning Asians reduced variance. This lowers their concentration of high smart individuals relative to whites, helping to explain why Asians might have a slightly higher mean but significantly less population-level achievement.
We can see evidence of this above. See how at the 50th percentile of SES, Asian IQ is higher than whites, but it converges on whites at the tail. This is lower variance at work.
However, lower Chinese variance does not seem to be a consistent finding.
It is possible that Chinese immigrants to the US have higher means and lower standard deviations than Chinese overall. Some hypothesize that the lack of Chinese invention is due to conformist personality traits, as opposed to IQ.
Asian Americans, which are Chinese, Indian, and other, had SAT scores 0.48 SDs higher than white Americans. If we take the new SAT to be correlated with general intelligence at about 0.7, we get that Asian Americans are 105 IQ, as opposed to 102 IQ in China. We find no evidence of smaller variance.
Finally, Chinese gene scores predict population IQs of 102 to 105 depending on their location.
We will therefore take the overall Chinese mean IQ to be 102, and the Asian-American mean IQ will be 105. We will assume that the variance is the same as whites for both populations.
The national Indian IQ is quite lower. Above, you can see Pakistani GWAS results put them at a genetic IQ of 87 or so. This is similar to the observed scores of Indians. So we will take an average Indian IQ of 87, with a standard deviation of 15. This makes massive H1B immigration from India a very strange puzzle.
How many Chinese, Indians, and Whites?
We will perform two analyses, one at the global scale and one at the scale of the US.
Globally, the population is about 17% Indian, 17% Chinese, and 16% white. We have mean IQs of 87, 102, and 100 respectively. Thus, when sampling for tech workers from the global population of Indians, Chinese, and whites, we would expect to mostly see Chinese and Whites, and some Indians.
In the US, “Asian-American”, which includes Indians and Chinese, are about 6% of the population. We give them an average IQ of 105. Meanwhile, whites are 59% of the population, with an average IQ of 100.
How anti-white is FAANG?
If FAANG only sampled Americans, and sampled from people over 2 SD IQ, it should be 69% white gentile and 7% Jewish, meaning 78% “white” overall. It would only be 15.6% Asian. Consequently, the demographics of FAANG can definitely be said to be un-American.
Globally, FAANG would be about 38% White, 57% Chinese, and 3.8% Indian.
This means Indians are definitely overrepresented in FAANG, likely at the expense of whites. Official numbers are unclear on what “white” is. Unless teams are statistically segregated by race, I cannot believe that more than 20% of FAANG is actually white. They seem to be inflating their “white” numbers in their statistics somehow, likely by lumping in their Indians. However, if this is not the case, then perhaps whites are represented as expected if the hiring process were global.
We can conclude that FAANG is definitely un-American, basically abusing American hospitality while hiring Americans no more frequently than open borders economics would predict. This should be shut down by drastically reducing their work visa allowance, or else the leadership of these companies should be forced to relocate to Delhi or Beijing, places I doubt they want to live even though they are so keen on importing the people from there in vast quantities to work for cheap.
Whether or not they discriminate against whites given open borders depends how white their workforce actually is. Official numbers seem to indicate race blindness given open borders, but it is unclear what “white” actually means in their data.
Hunh? The tech firms probably are not hiring the average Indian. They are hiring IIT graduates. How high are their IQ's? Higher than ours, probably
There's much to consider here, but I wanted to speak on this quote in particular:
"...This is a strange idea, since India and China are shit-holes with very little intellectual track record."
This assumption is what happens when you treat intelligence quotient as being much holistic in its scientific validity than it actually is. It's more than possible for intelligence quotient, and I wouldn't be opposed to say this in reality, that software engineering and what have you deals much more in the type of aspects you'd come to expect with intelligence quotient tests -- software engineering largely deals more in a priori reasoning, dealing largely with more deductive and predictable scenarios, as does intelligence quotient tests with geometric patternization, language-based patternization (such as anagrams), mathematical patternization, and the list will go on. In other words, and forgive my inability to word this precisely, but it's more arborescent, a more "pen on paper" approach if you will. For many reasons, this "pen on paper" doesn't speak to how well you're able to decipher socioeconomic and sociopolitical patterns in thorough detail. This isn't to say there's no overlap, but it would be quite folly to think that disjunctive, often-times pithy questions dealing with a sectioned series of patterns, hardly phenomenological ones, are enough to understand what may be a requirement of ten years worth of information that would be required to understand the interplay of societies (both from a phenomenological account, but you could even extend this to a slightly more "pen and paper" approach in historical learning). It's more than feasible that "Asians" could be more intelligent when placed in these scenarios, but that doesn't mean it has to translate beyond anything more than that, because intelligence quotient may not be as thorough as some wish for it to be.
The other issue is that intelligence quotient is, more or less, more accurate when you subject everyone to similar questions and what have you. It wouldn't make a whole lot of sense to ask completely disparate questions for one person when contrasted to another, but then compare them under the same conditions. So intelligence quotient tests are much more equiponderant, whereas socioeconomic/sociopolitical (and feel free to use whatever other qualifiers to explain your point) phenomena tends to be much less equiponderant given what may be a series of complex socioeconomic/sociopolitical conditions. Could we say that given the personal cultivation and years and years worth of embedded structurization, conditions might be more favorable or more facile to do well in to those who are "white" than "Asian?" I cannot say for certain myself, but I think it's just as important to raise this point in a cautionary manner.
The third aspect that is quite a bit of a concern is that intelligence quotient tests exist in an autotelic vacuum -- that is to say that they largely measure the individual. Sure, we could say that there are elements of interaction involved -- if had to comprehend a story or something along those lines, but that is far from what I am referencing. However, you're not going to let someone else influence your test results in the same room (or ideally so) -- the point is to understand how you act unto yourself if that makes sense. Socioeconomic and sociopolitical elements, at least in today's global economy, are largely subject to economic interdependence. To think that one's socioeconomic/sociopolitical outcomes is as representative of that country as it would be of an intelligence quotient test is highly problematic. This isn't to say such a thing couldn't, in some senses, reach a more autotelic point, but there's much more beyond the surface that needs to be researched.
Lastly, do I need to explain why, "Chinese and Indians hardly invent anything ever..." is so asinine? I really hope you were just being intentionally obtuse for the sake of it because I'd love to go into this point myself.
Either way, I think there's much more work that needs to be done.