Google 'segregates' women into lower-paying jobs, stifling careers, lawsuit says
theguardian.com
theguardian.com
>>But other male software engineers who were less qualified than Ellis or at the same level were promoted into Level 4 and higher positions, according to the suit.
What is the proof that this is the case? Did Google admit that these candidates were "less qualified" than Ellis, or is it just the perception?
Just because two people graduate at the same time from the same program and have similar experience does not mean they are equally qualified.
Again, I'm not saying Google is in the right - but just because something appears one way does not make it so.
>>But Pease herself was denied a promotion to a technical position, the complaint said: “Ms Pease’s two interviewers, both men, did not ask her any technical questions, and one interviewer did not even bother to take notes of the meeting with her.”
This is the part that carries the most weight imo. It's pretty clear that interviewing processes in tech are biased at best. Maybe the course of action here is to encourage more blind interviewing processes, or bring in a larger pool of interviewers.
Its sad to see that this rampant sexism is so prevalent, especially at one of the most publicly visible companies in the world.
My guess would be perception. Honestly though, is more "qualified" the absolute end goal of any job? Thinking back to extracurricular activities in high school or college, the most qualified person didn't always get the spot - whether it be a sport, band, cheerleading, whatever. Sometimes people who weren't the best today were still chosen because coaches and instructors saw greater potential in them. Or someone less qualified with a better personality and mindset about success and what it takes to achieve success is preferred over the more qualified person that could create division within the team. This extends to professional sports as well.
Why do we pretend likes there's one objective measure for "qualified" in employment?
But when you hinge your argument and lawsuit on objective qualification then the burden of proof would lie on the accuser to prove its true.
(This is tangential to the core thrust, but as an eng trying to do my part to make interviewing less of a pain, this stood out to me)
It's increasingly common at companies that have highly standardized/calibrated interview processes. Often, this is for the express purpose of avoiding discrimination. Interviewers have to ask approved questions, measure them according to specific criteria, then express their evaluation in terms of a number and be prepared to justify it. That allows the numbers for different candidates to be compared meaningfully, like to like. The downside is that it's impossible to do all that without taking notes.
I suppose as an alternative you could record the interviews, but then that sort of doubles the amount of work needed for each interview which is also a problem when you're doing a whole bunch of them.
Personal data point: I have a B.S. in Mathematics and a Master's in Bioinformatics (taken after 7 years of PhD study), and I had over three years of backend professional experience when I was hired at Google as a Level 3 in frontend engineering (I was told I was going to a backend position with "lots of math" when I first accepted the offer). Before I left Google I mentored a Noogler who was hired as a Level 3 despite having just finished a PhD in CS.
My point is that Google is filling slots with bodies, very smart bodies, but that it is incredibly common to come in for a level you are overqualified for and a role you are unsuited for.
I offer that people should be put in front of a machine with facial recognition and the most advanced AI available that can conduct a one on one interview with a person to determine if they meet the qualifications for the specific job they are applying to.
This would be controlled by a 3rd party who has no ties to any employer and would be used more as a data gathering tool that produces results of a person's interview and compares it to other people who interviewed as well, obscuring name obviously but providing gender and race breakdowns, among other things. people could possibly view this data after they've had the "real" interview with Google or whomever and compare with what was determined by their interview with the AI system. The 3rd party could provide this data to the public on a monthly or yearly basis so that everyone can know, possibly, if there is an incredible amount of bias that an interviewer may hold toward any particular people or groups of people.
Of course, there's 1000's of caveats to this and companies like Google would have to provide how they conduct their interviews to said 3rd party, as well as techniques and what they expect in a person's personality but wouldn't it at least be better than having people constantly reject the notion that there is a discrimination and bias problem in and out of the workplace? Not to mention it would all but eliminate the need for lawsuits for this kind of thing, unless one disagrees wholeheartedly with 3rd party AI results and actual interview results.
I wonder how this kind of information can be qualified other than a full transcript of everyone's interviews.
That said, at some point I think one would need to think carefully if their outcomes are strictly the product of institutional bias, or whether there's something they need to change in themselves. Perhaps be more assertive, step up into leadership positions, speak up when they normally wouldn't, etc.
Truth of the matter is, it's very easy to blame one's misfortune on somebody or something else, but this is also the least productive thing one can do, if the goal is to achieve something and not just solicit sympathy or a legal settlement. Contrary to popular belief, things don't just fall from the heaven on (most) white men. They have to work and put themselves in precarious and uncomfortable situations to get where they want to be too.
The recruitment pipeline does seek out women, but they are expected to pass the same hiring bar that everyone else does.