These articles always pull the same tricks. They invent a new racial category, "white or Asian", to avoid stating that only 61% were white - i.e. slightly underrepresented compared to the 63.7% white 2010 US demographics [1]. Although by 2014 the white % had probably dropped enough that they are neither over- nor under-represented at Google (the 2020 census reports non-Latino whites as only 57.8% of the US - a 5.9% drop in only 10 years [2]).
But you wouldn't know this from "91% white or Asian". Maybe they can make the problem go away entirely by saying Google is "32% Black or Asian"?
[1] https://en.wikipedia.org/w/index.php?title=Demographics_of_t...
[2] https://en.wikipedia.org/w/index.php?title=Demographics_of_t...
Especially with admission scandals at top schools, there seems to be an unspoken systemic bias against asians perpetuated by some activists.
It was fashionable in France for some time, and it was even attempted. It backfired however. Researchers realized that hires were less diverse when using anonymized resume.
> replace experience on resumes with "random corp 1", random corp 2, random school 1 etc.
That would remove one of the best predictors of future performance. Especially in CS, not all internships or schools are created equal.
Now, with all the "affirmative action" going on, these should be interpreted with a grain of salt. Asians, for example, need much better scores to get into Ivies than some other minorities. And YouTube was caught trashing all white and Asian applicant’s resumes a while ago [0].
[0] https://www.theverge.com/2018/3/2/17070624/google-youtube-wi...