I very much enjoyed the opportunity to interview at Google and to see some of the inside of the campus, but articles like this seem disingenuous to me.
My first interview on-site was delayed due to room reservation issues, so it started late, and this continued as a theme throughout the day.
That's anecdata, but I have to wonder whether whatever schema and/or processing pipeline are allegedly in place to remove human bias would be able to understand issues like this or of other kinds - i.e. environmental and/or human failures outside the scope of the process. These systems don't tend to critique and monitor the environment, just the data that is entered into them afterwards.
This plus the admission from a few Googlers that personal recommendations do really make a big difference make me a little jaded when reading articles like this - I'd much prefer to see admissions of honest weaknesses alongside all the positives, but I guess we're still some way from treating anything except severe security breaches that way in the software/marketing industries (this article is in the latter industry).
Edit: I feel like I should add a bit of context about why I feel the article is misleading, given that my post was inspired by personal experience.
The misleading aspect is that the article tends to portray the process as striving towards an unbiased science, whereas my perception is that bias is still part of the decision-making process (arguably for good -- personal recommendations can be very positive indicators, as long as they're not from an old-boys-style network), and I feel that there is insufficient measurement and understanding of interview factors to make it a science (i.e. exhaustion/travel factors, cultural differences, personal factors, etc - which I don't think affected me, but are still a real part of interviewing).
NB: When I say old-boys network, I imply any kind of non-meritocracy which simply aims to get people 'in the door' without full vetting; I believe this is possible regardless of gender, but just that's the term I know to describe it
My first interview on-site was delayed due to room reservation issues, so it started late, and this continued as a theme throughout the day.
That's anecdata, but I have to wonder whether whatever schema and/or processing pipeline are allegedly in place to remove human bias would be able to understand issues like this or of other kinds - i.e. environmental and/or human failures outside the scope of the process. These systems don't tend to critique and monitor the environment, just the data that is entered into them afterwards.
This plus the admission from a few Googlers that personal recommendations do really make a big difference make me a little jaded when reading articles like this - I'd much prefer to see admissions of honest weaknesses alongside all the positives, but I guess we're still some way from treating anything except severe security breaches that way in the software/marketing industries (this article is in the latter industry).
Edit: I feel like I should add a bit of context about why I feel the article is misleading, given that my post was inspired by personal experience.
The misleading aspect is that the article tends to portray the process as striving towards an unbiased science, whereas my perception is that bias is still part of the decision-making process (arguably for good -- personal recommendations can be very positive indicators, as long as they're not from an old-boys-style network), and I feel that there is insufficient measurement and understanding of interview factors to make it a science (i.e. exhaustion/travel factors, cultural differences, personal factors, etc - which I don't think affected me, but are still a real part of interviewing).
NB: When I say old-boys network, I imply any kind of non-meritocracy which simply aims to get people 'in the door' without full vetting; I believe this is possible regardless of gender, but just that's the term I know to describe it