The only problem with blind selection, is that, sooner or later, the race/gender/sexual orientation/religion/fitness/attractiveness/age (I'm an old fart, so I can tell you a thing or two about ageism in tech) becomes apparent.
I have heard story after story from peers (around my age), about passing numerous rounds of phone and test interviews, only to see the interviewer's face fall, as soon as they walk in the door. It's happened to me, but, thankfully, before being flown out (if it's a contract application, then we're on the hook for the cost), and revealing the age.
It happens with highly qualified older white guys, so I'm sure that it will happen with other distinguishing characteristics.
The simple fact of the matter is, is that people have certain traits they are looking for, and the final call is always a "gut feeling."
I've learned to just avoid all the agita by making it clear that I'm "of a certain age," right up front. I don't get many offers, but at least I don't have those blasted recruiters, gushing about my résumé, only to shred my contact card, as soon as they find out I'm old (I guess the industry is crawling with 32-year-olds with 30 years' experience).
I don't think it's a good idea to have AIs do the selection (as has been suggested numerous times -usually by folks in the AI business). Humans need to work with humans. If an AI puts someone into a situation where they are treated like garbage by their managers and/or co-workers, then they will be miserable (and unproductive); especially if they have done something like uproot their lives to move somewhere (I have also heard many stories from people that have uprooted their lives to go to "the perfect" job, only to come back, a few months later, broken and cynical).
If the people involved don't want to work with someone like me, then I don't want to work with them. That's easy for me to say, though. It can really stink, when you're hungry and need the work.
Happened to me I aced everything and when the interview walked into the room I saw it on their face (too old). Thankfully that only happened once and the company wen under at some point thereafter so good thing I didn't get hired.
This is absolutely one of my nightmares. I'm turning 40 soon and I know my opportunities of being paid to write software will become more and more limited.
I'm noticing it now. I'll also be 40 this year. Getting through to the offer stages of the process has become impossible for me today, despite how well the phone screens, zoom calls, take-home tests, and technical interviews have gone. To be fair, I'm not actively seeking employment but I have had about a dozen job opportunities land on my lap this year that I have not outright rejected. I'm in the process of interviewing for yet another company. Like many of the others, I was recommended for the position internally by a former colleague but I assume it will go the same as the others.
> The only problem with blind selection, is that, sooner or later, the race/gender/sexual orientation/religion/age becomes apparent.
Changing the emphasis of your statement slightly, I think one of the gaps of focusing on blind selection is that by attempting to work around assumed biases within the org, even if it works perfectly in the hiring process, it does nothing for employees once hired (when presumably several of the traits you listed are not going to remain hidden). Blinding part of the hiring process doesn't help employees have equal access to projects, growth opportunities, involvement in decision-making, etc.
I think that it is sort of "darwinian." If a corporation doesn't establish a culture of excellence (whatever the measure may be), then they will get not-excellent results.
"Cultural fit" is important, but, as a former manager that had to make many accommodations for highly-qualified and diverse employees, it's also important for a team/company to be prepared to adjust their culture to get that excellence.
Oof that sucks and is scary, since we will all be older at some stage. Personally, I prefer having people older than me on my team (I'm 35) because they tend to have experience I and younger members don't have and that experience can save quite a lot of problems in the long run.
Sure, maybe older people aren't caught up on the latest fad tech, but most of that is BS anyway, so no biggy...
This is a really helpful framing of the same problem that hopefully everyone can relate to. You can be great at your job but still have fewer opportunities because of how you're perceived by the majority group.
Getting the hiring biases out of the way early makes sense to me. The downside is that this doesn't change the broader situation or challenge it in anyway. It just says: "go ahead and apply your biases if you have them". It think, in some ways, this practice could make things a lot worse overall. It allows companies to massage their diversity metrics in ways that are acceptable and not at all challenging to the notion of what "acceptable diversity" looks like.
This is why I actually believe there should be hiring quotas. Tell departments that at least XX% of their hires are expected to be woman, or older than 50, or racial minorities, or whatever else. Set the percentage based on the pool of applicants, minus a bit to allow wiggle room. (And if there are legal blockers, let's change the law!)
It feels wrong to me too, I know it does! But if hiring happens based on gut, and if our gut is biased, then we need a way to systematically counteract our biases.
Why do we need to systematically counteract our biases? Why is that right thing to do? And who decides what is right?
I was biased when I married, I’m biased when I pick people I’ll spend time with, I’m biased when I apply for a job, and wouldn’t like it to be any other way... Of course, unless it’s me deciding for everyone else what they should optimize for their decision making process.
Well this might be taking it a step too far. The first, obvious step would be simply to compare the actual hires (workers) with the available pool... almost nobody actually does that. People keep claiming that e.g. Google is sexist because they hire so few women, without regard to the fact that their worker pool has about the same distribution as their hiring pool (CS graduates). The UK passed a law requiring companies to disclose average salaries by sex etc. with no regard on the actual job / education level / level of employment.
We can't even begin to talk about solutions if all the media / researchers / activists keep pushing misleading statistics.
There is an alternative explanation to the biases people are seeing here, unfortunately, and it would render gender and age confounding variables.
It's known that Valley tech firms of the type studied in this paper have a large left wing contingent amongst employees. We know that being female with a degree correlates quite well with being left wing, as does being young. In contrast being an older white male correlates somewhat with being conservative.
If the actual discrimination here is against "people likely to be conservative" - which is absolutely likely to be happening given what's going on in these firms - then setting quotas for gender and age wouldn't be addressing the underlying problems, only symptoms.
> The only problem with blind selection, is that, sooner or later, the race/gender/sexual orientation/religion/fitness/attractiveness/age (I'm an old fart, so I can tell you a thing or two about ageism in tech) becomes apparent.
This too is a problem we can solve with technology:
I've been thinking of making sure that my age is clear on my LinkedIn/resume/etc., for just this reason. Even then, it's clear that quite a few interviews I've gone on have been "fake", in the sense of being useful for EEOC stats, but with no bona fide intention to hire. Which is frustrating, because at the end of the day, interviews are themselves unpaid work.
These days, I've "solved" the problem by just taking lower-paying jobs. No one I work with really understands what I do--they just know that when they bring me the harder problems, they generally get solved. It's kind of nice in a way to be king, even if it is in a puddle.
Fair or not, the market always wins. And if the market tells you that you're not wanted, best to go elsewhere.
This is one of the worst case scenario, but there's any variation where it works better than the traditional method.
At first contact you could have been packed in the "meh" group, but by virtue of coming out of the recruiting process your peers won't stop at that first reaction and take time to make it work.
Even if you were to be dismissed at the first face to face with a manager, it seems to me it's still better than if it was by some random HR intern that would have had no impact on your day to day work.
Dismissing blind test/interviews because there can still be later discrimination would be throwing the baby with the bath water IMO.
This paper is a prime example of not accounting for Simpson's paradox:
"These numbers suggest that women and White applicants are proportionally more likely to get hired compared to their counterparts."
No, you haven't given us the men/women breakdown by ethnicity. It may actually be that there is an over-representation of women in the white category compared to other ethnicities, and therefore the bias towards hiring females carries with it a bias towards hiring white.
However it's possible that if you compare ethnicities separately between men and women you might find no racial discimination exists.
(and vice versa for ethnicity vs gender).
The fact that they don't show these breakdowns is a major weakness of this study.
Or strength. Depending on whether the desired metric is scientific correctness, or political marketability.
There's a fascinating study on orchestra auditions, where it was found that performing blind auditions (where the interviewee's identity is hidden to the interviewer) led to more equitable gender representation: https://gap.hks.harvard.edu/orchestrating-impartiality-impac...
IMHO, if the tech industry wants to live up to its narrative of meritocracy, this is one obvious improvement over existing processes. No, it won't take care of pipeline problems; no, it won't solve the "tipping point" problem (i.e. where candidates of underrepresented groups are dissuaded by a lack of pre-existing representation, making it very hard to go from zero to one, so to speak). That said, we're uniquely positioned as an industry to do this - technical interviews are similar to auditions in that they hinge on skill-based performance - so why not? It can't be any less arbitrary than asking random questions about manhole covers and light bulbs.
I'd posit that even the "show your thinking process" parts could be done in this way - e.g. via text chat, or inline comments, or maybe even using voice obfuscation and/or neutral avatars.
You'll see news outlets claiming that black and white drug use rates are the same, but they're going off of the "Have use ever used X?" questions while completely ignoring the ones about how often they've used X, which shows a clear racial discrepancy. That's before you get into issues like the study being based on self reporting, or the vast majority of drug crimes that result in jail time being ones related to dealing and not mere use, etc.
To believe that blind applications would help increase female representation presupposes that they're being discriminated against right now, when TFA shows that women are getting preferential callbacks. That completely jives with my experience: most female candidates are highly, highly sought-after, and are quickly hired by top tech companies (leaving smaller companies looking bad in the process, despire their equal desire for female candidates).
Blind applications would probably hurt female representation. It's possible it would help minority representation.
It seems to me that if you choose something that is completely equitable in who is able to participate, then the rest of it sounds like manufacturing dissent by companies or corporations that want a "leg up" on the competition in the D&I category, which is all the rage these days in terms of marketing. Maybe there are other reasons women don't want to enter these fields, but prefer to wholly dominate others, and maybe that we should turn the conversation to this being OK. We've spent so many cycles trying to "figure this out" when there is research after research that just shows women don't prefer the "rat race" as much as men, and gravitate towards roles that focus on helping, nurturing, and community, hence why they dominate roles where those are highlighted: teachers, administrators, nurses, psychologists, etc.
There's never going to be a feeling of "service" or caring when you are writing ad-tech for a FAANG. It's just not going to happen, no matter how many D&I articles you write.
There has been research on demographics pertaining to college majors and their career opportunities in the context of why some demographics make less money than others after graduating with a 4 year degree. One of the main factors that came up in the interviews was, like you said, the lower earning demographics wanted to have a bigger community impact, but that those jobs simply paid less money (like social workers).
I once went to a members-only hackerspace that was very open and equitable, at least in theory. To join, you had to get a recommendation from another member and support from one more. They held regular open days and were very welcoming but definitely had an established subculture that didn't include much diversity. Joining really meant being the friend of a member or possibly a friend of a friend. If you were an outsider, you'd really need to show them you were already a part of their sub-culture before they'd consider you. Openness to diversity really meant openness to conforming to an existing culture before joining.
Diversity and inclusion is an extremely hard thing to get right or even to agree on what "right" means. I don't think anybody would agree that diversity issues are fixed now and so it can't be "time to turn the conversation to this being OK". As I pointed out in my story above, lots of people can't even see that there is a present and persistent problem despite the good intentions around fixing it. That's exactly why we need to pay more attention to studies like this.
You seem keen to switch to a conversation about nature instead of having one about nurture/culture (there were a few historical arguments about race that took a similar approach). Perhaps these two are so intimately bound that it's not helpful to make observations about one in the abstract. Instead, should we not simply focus on those things we can change and try our best to ensure the inequalities of the past aren't reflected in the culture of today? It's not about some set of absolute outcomes, its about the absence of bias - an outcome I'd hope we were all on-board with.
> Openness to diversity really meant openness to conforming to an existing culture before joining.
Why is this a problem? I've been progressing most of my life, but I came to software development relatively late in life. The culture was dramatically different from that of my prior profession.
Harvard's argument is that selecting candidates based on merit means we discriminate against those who had a harder time building merit and is therefore racist/sexist.
Some people believe girls don't study CS in large numbers because programming is "a boys' job" which is a self-perpetuating cycle; and a limited period of substantial positive discrimination could turn it into a gender-neutral job that appealed to men and women equally.
Other fields, like medicine, law and chemistry have radically changed gender composition since the 1940s so it's not unprecedented for an industry to lose its gender bias.
Personally I think it's far from certain such an effort would work - or that it wouldn't.
> most female candidates are highly, highly sought-after, and are quickly hired by top tech companies
Let's say we believe that women are on average equally as capable of men, and we know there are maybe 10-20% as many women in the industry.
Are those 10-20% women roughly as good as the average man, or are they roughly as good as the top 10-20% of men? Have they had the same experience as average men, or have they fought through and survived discriminatory barriers?
Even if we suppose the answer is somewhere in-between, it wouldn't be surprising that women are highly sought-after. Because with these assumptions, the women in the industry are generally likely to be better on average.
Maybe we don't observe discrimination against women in this specific context* (post-application and pre-salary negotiation), but that doesn't mean it isn't occurring elsewhere.
*The summary data includes non-technical hires at tech companies
Your assumption relies on the women getting into the field are the best women. I don't see why that would be true. The fields with many women like law, medicine or psychology are much harder to get into than computer science or engineering so most of the best women likely ends up there.
Given that as a woman you don’t benefit from the “competency bias” and constantly has to prove yourself (which is not necessarily bad), combined with the fact that many women simply walk out of careers in computer science and physics because of sexism/harassment, you could consider that the women left are indeed more competent than the average man in the industry.
Women do benefit from likeability bias though, and likeability is certainly a factor when hiring and firing.
As for fake resume studies, the problem with those is that male and female resumes are evaluated differently. If they made a male looking resume and sent it out with a female name it will do badly. But a female looking resume with a male name will also do badly.
What does a male/female looking resume mean? (Genuinely asking. I can't imagine that a female engineering accomplishment is vs a male engineering accomplishment.)
I'm curious also, but anecdotally, women were over-represented in my engineering school's societies and probably under-represented in design competitions.
There are plenty of research done on gendered words. Like highlighting your own personal excellence or skill is more masculine etc. There are also of course that men and women tend to have different hobbies and therefore spends their free time doing different things. So one new grad might have done some leadership roles in a horse club while the other maybe did some chess competitions.
Does this mean if you're a woman and you highlight your own personal excellent in your resume you're statistically likely to be treated worse? Similarly if you're a man and you have a leadership role at a horse club you're statistically likely to be treated worse?
Thought experiment: These biases are mostly shared among people so you got them in yourself. Instead of thinking "What is the ideal software engineer", think "what is the ideal feminine software engineer" and "what is the ideal masculine software engineer". The picture in your head will be very different. If you are a woman you will be compared to the ideal feminine engineer while as a man you get compared to the ideal male one.
The prime example is the term "bossy", women get called this since they are expected to be much more cooperative than men. I think a very big issue right now is that we use men as a standard and say "when women use male strategies they get pushback for being too masculine", instead to gain individual success they should try to be like successful women. In an ideal society this wouldn't be the case, but as is these biases exists and so you have to work with them.
And as a personal anecdote, when I looked for jobs as a new grad when I used more cooperative and less personal excellence I didn't get any callbacks. I got lots of callbacks when I focused on personal excellence though. Its as if companies assumed I was less competent just because I talk about teamwork, because their ideal masculine software engineer wouldn't talk like that. You can see here how it works:
Edit: The moral of the story is that when we tell men to be more feminine and women to be more masculine we just hurt them. Men and women aren't evaluated by the same metrics. People told me "Companies expects you to be a teamplayer, try to highlight that!", but it was clearly wrong and didn't help me at all.
That's the opposite of what happens. My own experience has been that women benefit dramatically from a "being a woman" bias that makes them much more likely to be hired - exactly what this study now quantifies - and in addition be basically unfireable even if they have severe skills or attitude problems.
The whole idea that there's a competency bias towards men is false. What's actually being observed is that women are hired even when they aren't competent, to please feminists and diversity advocates, which then by definition would make men "appear" more competent even if they were of only average competency.
Wouldn't you need to have evidence of discrimination before you start to discriminate against other groups in the name of women? Women might actually get a backlash for that and you have the classic self-fullfilling prophecy. Why not try a revolutionary approach and treat people equally, everyone to their best ability as their conscience allows?
We would need to scrap esoteric models about bias and have very simple rules that everybody understands?
And if people responsible for awarding research grants within tech decide not to investigate whether there is discrimination against women, or tech companies decline to give full access to their data.
Then the quality of evidence that you demand can't exist - in that case, should nothing be done about it?
Maybe it is hard to generate, but without it you have no basis to justify your discrimination. I think that people specifically denied policies that allows it by intrinsic discrimination is a very good and sensible step and should continue to be regarded as the better approach.
If you want to discriminate without sufficient evidence, I am plainly not with you on this.
It is the simplest form of power play to treat people differently because it breeds jealousy. Jealously can lead to discrimination as well. You can do that as a team leader and be sure that people are more concerned with each other than holding you accountable. This is actually a common behavior in corporate office culture which had many tech flee the premises because they had a choice.
But there is quite simple and obvious evidence of discrimination: the percentage of technical jobs which go to women.
Not accepting this as evidence and demanding that your own standards for evidence are met (without saying exactly what that would involve, so you could later reject any other evidence that is provided) before allowing any corrective action, is yet another way that this discrimination is perpetuated.
When I studied CS and electrical engineering we started with 120 students. 5 were women. 15 students made it in regular time from which 1 was a women.
You conclusion isn't obvious, on the contrary, there are contradictions. Where should the women in tech have come from?
Would you also think that nurses discriminate against men? No, you only think discrimination is an issue in spaces where men are overrepresented. That is sexism.
> allowing any corrective action
If the reasoning is already that bad, I have very little faith in this corrective action.
> Would you also think that nurses discriminate against men? No, you only think discrimination is an issue in spaces where men are overrepresented. That is sexism.
Ah yes, the hallmark of good faith discussion asking a question and answering it for them.
A rhetorical question is not a bad faith approach to discussions contrary to leveling the accusation itself. The argument is still there if you want to have a go at it.
> When I studied CS and electrical engineering we started with 120 students... 15 students made it in regular time
That sounds like a shockingly badly organised course with many barriers to success. Such barriers to success are likely to fall harder on women and minorities (who are more likely to have caring duties, less support in their social network, and will face general discrimination).
With even the facts you have given, it would be unsurprising to me that disproportionately few women bother to apply: even ridiculously fewer women start than on a typical course.
I would be embarrassed if I were an educator or organiser for that course.
> Would you also think that nurses discriminate against men?
No. Although this is not directly analogous to anything I have said, I am giving a good faith answer. I think that nursing is an underpaid profession because it is seen as women's work - just as caring work is often unpaid. I'm not aware that men face significant barriers when they choose to enter nursing.
The careers in which men are over-represented and women are under-represented tend to be highly-paid and/or prestige jobs. So, that's quite a different situation and points to societal discrimination by gender against women.
Computer Science as an industry is relevant here in that: women were initially over-represented, until it came to be seen as a prestige career and started garnering higher pay, and now they are increasingly under-represented.
I agree that it is undervalued and maybe because it is seen as a women's job, but that part is speculation. I live in a country with stronger social systems and there are countless interests that keep the pay as low as possible. You would not find a single person that says that nursing isn't important.
As I said, you if you want to have a tech job, you currently almost can choose where to work. Men and women alike, so I cannot see that many barriers.
I don't buy into the prestige argument at all, it feels far removed from reality. I didn't pick my profession because of prestige and I don't think many people do. This isn't the showbusiness. Do you know what people with strong affinity to tech were called? Nerds. The good payrate is very recent, as are the gender discussions btw.
> where candidates of underrepresented groups are dissuaded by a lack of pre-existing representation
I don't understand this persepective from candidates. The job market must be really good if they can use this as a metric for pursuing a job opportunity. I was the only person from my country when I joined my current employer. It never even crossed my mind that it could be an issue.
There was also a post on HN a few months ago that said asking minorities to attend things like recruiting fairs in order to show the diversity of the employer was unfair.
At my company, you have a leg up if you fit one of the diversity metrics and are applying for a job.
I've worked on teams where I'm the only one of my race. I've been on group projects where I'm the only one of my gender. Based on the conversations I've heard on some of the teams I've been on, I have a minority political view and culture/lifestyle as well. It's almost never a problem unless you believe or think it is a problem. There can be rare cases where you get someone who is actively trying to make it a problem, but that tends to be rare. So I don't see it as a chicken or egg issue, I see it as mindset problem.
By 'chicken and egg' I meant that employers can't really do much about minority candidates not accepting a job offer because there aren't any/enough of that candidate's gender/race already employed.
Thank you. Your experience in not suffering from discrimination clearly invalidates all of the millions of people who do. It's clearly all in their head.
It boggles my mind on people's basic inability to realize that not everyone has the same experiences in life as them. And rather than accept other peoples experiences as valid, it's always the same argument of "I haven't had to deal with this therfore they don't either."
Yes they want to be in a situation where they can just ignore it and it won't be an issue, the problem is they don't have that luxury. It's great that you do, but that doesn't change their circumstances.
I never said it doesn't exist. I'm sure there are people who are victims of discrimination. Where's your proof of the millions who do suffer from workplace discrimination in tech every year? More specifically, how do you see the chicken and egg problem posed in the parent comment not being a mindset issue?
I've actually seen women on twitter say something like "if your company doesn't already have women, we're not interested, stop your pretending to care about diversity and women's issues" or something to that effect. How will the situation ever change, then, though? Its most definitely a chicken and egg problem for employers.
We talk a big game about merit, capability, qualifications and such.
Ultimately though, nearly all actual selection processes are are subjective or ilegible... depending on how you see these things. How an interviewer feels about you intuitively matters a lot, maybe the most. Actual tests of skill are usually intuitive as well. An interviewer tries to gauge your skills, but it's rarely designed to be an objective test of skill. If it is an objective test of skill, it's rarely the primary decision driver.
Blind auditions enforce a certain kind of objectivity. But, I think we can read into the fact that musicians "audition" while employees "interview." You perform an audition.
Blind auditions would be a radical change to hiring/selection. The big advantages/disadvantages of the approach are like those of standardised testing. They measure the easily measurable, and bury everything else.
I'm curious, what do you want to test? The classic "memorize how to bubblesort" interview questions which so many people complain about because they don't show anything except that someone has prepared? Isn't it better to just look over the code of applicants and check if they are aware of general structures etc?
Obviously some familiarity with algorithms etc is required and it should be checked if that's there, but with tests you can't really test if someone understands the bigger picture and did not just memorize the answer. I know more than enough people who can solve problems just fine but their code is absolutely atrocious and I'd never hire them. Interviews where one can ask them why they write code the way they do are probably far more effective.
By saying nothing years ago when "diversity" became popular and people started arguing there weren't enough women in computing. I'm as guilty as anyone, in the beginning it all seemed harmless enough. It wasn't, it was based on sexism from day one, and now we see the consequences: proven and massive bias towards women at an institutional level. And good luck trying to fix it.
The people advocating for more representation almost invariably are not interested in removing discrimination on arbitrary characteristics, which is a near universally laudable objective, but rather work backwards from the demographic representation they'd like to see.
If you think that the diversity and equity initiatives within companies are currently working towards anything resembling a blind hiring process, I get the impression that you're not particularly up to date on the objectives of the modern left.
Women: +9 to +10% chance of callback relative to men
Black, Hispanic, and Asian: -8 to -13% chance of callback relative to White people.
I wish they had broken out the other ethnicities separately in the abstract. The reasons that Black and Hispanic people might be getting fewer callbacks relative to whites are likely quite different from the reasons that Asian people might be getting fewer callbacks.
I'm making my way through the main paper but there's a lot of tables in there that would take me a lot of reading to decipher and it's really not clear which are best to use for any purpose. The tables do break out the separate ethnicities separately though (along with callback/interview/offer rates, not just callback) and it does appear that Black, Hispanic, and Asian very much do not have the same experience. In particular, the graph on page 22 seems to show that, when it comes to receiving offers, female candidates have a 29.5% advantage in receiving offers, Black 4%, -21% Asian, and -24% Hispanic. The previous column (received interview) is much worse for Asian, Black, and Hispanic applicants though; all were significantly less likely to receive interviews than whites.
Anyway, there's lots of potentially good data in here, assuming you trust their methodology, but I personally feel like I need someone who knows this stuff better to write up a longer abstract based on all this data to really explain it to me properly.
As far as I can tell, the paper doesn't seem to control for citizenship or immigration status. It seems likely that Hispanic and Asian job-seekers, especially in Silicon Valley, would be much more likely to be from overseas and therefore require a work visa.
I don't know about Hispanic per se but I definitely see that being true of Asians, and yes, it's a potential confounding factor. Would love to know if the longer paper addresses it.
At this one job, we had only two remotely viable candidates for an open position. I was on the hiring committee, as I often was in those days.
Candidate A: Had worked in the industry, had all of the qualifications, already chock-full of some interesting ideas I wanted to hear more of from the interview alone. Excited at the prospect.
Candidate B: Had never worked in the industry, had only a handful of qualifications, barely responsive. Seemed indifferent to getting the job. Additionally, not too fluent in English, to the point where it was more than a little difficult to communicate.
Candidate A was a white man, Candidate B was a recent immigrant and a woman. The immediate supervisor for the position -- a woman -- wanted Candidate A, as did most others. However, the person running the show said, out loud I might add, that our group already had "too many pale males." I would like to repeat that: too many pale males. A significant glance was then cast at me and the guy in the wheelchair on the hiring committee, both being not-particularly-dark men. Presumably by "virtue" of our disabilities we would automatically be down for the Diversity Squad.
Candidate B was hired and turned out exactly as she was in the interview: disinterested in doing the job, lacking even some bare understanding of how to accomplish many things, always trying to find ways to do her grad school homework while on the job and pushing off her duties on someone else, rather than trying to learn her tasks. Her poor English was a significant barrier. She remained a leaden weight until she went off to be someone else's problem. She wasn't a drag due to her skin color or sex, but she was hired because of those things.
My guess is that this kind of discrimination (I use that word specifically) goes on all the time in at least some segments of the industry.
I always try to give the recruiter no indication of race or gender. Frankly, if we all did that it would remove the bias.
The challenge is, I suspect they ask for race & gender is intentionally requested to add bias. I’ve worked with recruiters and part of the job is indeed targeting “under represented” groups to improve the figures.
> Race might be obtained, but honestly even that is questionable
If you mean "irrevocably determined with a 100% certainty" maybe...
But you know, most people who think their name doesn't give away their race, are a certain race...
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Funny that this is really such an uncomfortable truth for some people here... I'm a black guy with a Ghanaian name, so I laughed out loud reading the comment.
It's not like black people aren't allowed to have "euro-centric" names, but, surprise surprise, Caucasians represent a large majority of people with those names
Likewise there are names that almost no Caucasians have (like mine)
If someone is reading your resume intent on being biased, a name like "Austin Walters" is going to appear as... a white guy.
There black guys named Austin Walters but they're also not conducting a census... if someone really wants to discriminate against you based on race, your name is plenty to go on.
Again, they're not conducting a science study, an 80% chance is plenty for the kind of person trying to discriminate...
Likewise, someone who reads my name, which uses consonants in a way that English doesn't usually ( causing people to mispronounce my very simple last name even when reading it verbatim) will instantly assume I'm black.
It's something I accept as a person with a very black name, it tells you the main audience of HN is this is really such a revelation for some of you lol
Unfortunately, the study finds that the bias persists even past the initial stages:
> These outcome gaps do not cancel-out in the later stages, as female and White applicants are more likely to receive an interview and offer.
Though it does at least help candidates avoid bias in getting a callback:
> To further address endogeneity concerns, we perform quasi-experimental analysis involving applicants whose race and gender are ambiguous to the recruiter in the initial application review stage, but are later revealed in the phone screen stage. We find that ambiguity in applicants’ race and gender attenuates the main effects of race and gender on receiving a callback – that is, the outcome gap in callback disappears for applicants whose race and gender are ambiguous to the recruiter
Me too, I sound white too. I've noticed reactions when a Hispanic looking guy shows up.
I have 6 kids, their mother is white. I've heard stories from each of them that range from kids asking, "why is your dad brown and you're pink?" to "My parents were surprised when that brown guy showed up to pick you up."
I can confirm that at least two FAANG companies explicitly give diversity points to recruiters. That is, hiring a "diverse" candidate is worth ~1.5x as much to them as a non-diverse candidate for the same role.
They are cagey about the exact details of who is included at a given time. But I do know it varies by rule.
It would be nice if we could just hire people based on the necessary experience and regardless of how people were born or how they look; features they have no control over
Unfortunately seems like a pipe dream for the human race right now, cheers to those who try though.
Based on the research paper, it doesn't look like they're biasing towards underqualified minority candidates.
In the paper they controlled for "years of experience, average tenure, past employment at a talent competitor, education, university rank, referral status, and skills." Even with the initiatives you mention, Black (-6%), Hispanic (-9%), and Asian (-13%) applicants are less likely to be called back.
Got hired into a company that did everything possible to avoid hiring straight white men.
Everything was completely dominated by not offending anyone over anything. Unless you were the aforementioned group.
Turns out there simply isn’t a lot of the right race/gender/sex. I’m sure that’ll be different as time progresses, but for now there is clearly some catching up to do.
So it was all jr developers. A couple of which truly cared about technology, and I see good things in their future.
The rest were the most arrogant sexist bigots imaginable.
Most days were filled with hatred. Full rant fest about how evil “my kind” were. But it wasn’t personal as I was clearly one of the good ones...
So yeah, n=1 personal experience. But crude that echo chamber was scary.
So what you're saying is that.. I am responsible for my happiness, and that other people are not to blame for the choices I made in regards to my behavior and life, especially straight white men?
Wow, that's a hard cookie to swallow.
(for the ones who read this far, what I wrote is sarcastic).
That's one of the reasons I left tech and went to work for an investment bank. At least here no one pretends to be in it to "make the world a better place" or whatever agenda tech companies are selling nowadays. YMMV
Ugh, that's one thing I really hate about much of tech: supposedly everyone is in it to make the world a better place, somehow, by actually making it worse through advertisement and destroying privacy and getting people addicted to social media.
That your post is on the top shows the "white male" bias in hackernews audience. People are up-voting your personal anecdote and your "I am a white male victim" post more than the discussions about the actual results on the original article.
The post reveals the hackernews bias against discrimination in all forms, regardless of whether it is targeted at minorities or white males. Meritocracy baby!
I totally agree. But shouldn't we trust the data more than one person's anecdote? The original article clearly did not find any discrimination against white male. Rather than discussing that result, we are here commenting about one person's anecdote.
The demographic working in CS nearly reflects demographics that study CS or other relevant degrees. Ever asked yourself if it may be your bias that is the root of the accusations for discrimination? Because with the evidence available you can make that case.
Worked in a group that did everything possible to avoid hiring, acknowledging, and rewarding women's contributions.
Everything was completely dominated by one-upmanship and crude jokes. Unless you were in the in-group, you were screwed.
I don't doubt your annecdote. I guess all I can say is, welcome to the club? Being part of the "out group" in a toxic workplace sucks. I've had men come up to me and say, "Wow now I get it." Because in their entire lives they had only worked on male dominated teams, and working on a toxic non hetero non male dominated team made them really uncomfortable, they were fine working on toxic hetero male dominated teams. All the norms had changed and they didn't know what to do. But until they experienced it themselves didn't get "what the big deal" is.
I stay in tech because I don't want to be forced to take a lower salary because of cultural attitudes that women being around "ruins the atmosphere". But yes if I had a pile of FU money, I would bail in a second, not because I'm busy taking care of children or whatever excuse, but because people are insecure, emotionally immature and create a great deal of toxicity.
And once again a race study that doesn't list Native Americans at all. It would be nice if they remembered 2% of the US population, since certain policies ("Actual Name") have discriminated against Native Americans because of the ignorance of silicon valley firms. AIHEC and American Indian College Fund (collegefund.org) could really use the help to get placements for students.
They don't care about you because you're not a politically influential demographic.
Notice how the demographic that dominates this debate is the second most privileged and influential demographic in the country: white women; yet they are portrayed as being some powerless minority.
It's always powerful demographics fighting each other. Nobody cares about the actual minorities that have no representation. That is almost tautological.
If it makes you feel better, you're not alone - middle eastern is never broken out either. In fact - we're grouped with white people. Some of us are white passing - some of us are very much not. Fun article about it... https://www.latimes.com/projects/la-me-census-middle-east-no...
I can tell ya - after 9/11 - being middle eastern sure didn't feel like being white!
I knew someone who worked as a recruiter at Boeing a few years ago, and she told me the pressure from higher ups to give preferential treatment to female applicants was crazy. She said they couldn't explicitly discriminate, but would use things like "Women in Tech" events to try to increase their female applicant pool.
Surprising study results regarding women being more likely to receive a callback than men. From personal experience and the teams I've been on, women have always been in the minority, along the lines of 8-10 men for every two women. However, I am not in Silicon Valley.
We need more studies in this area. I'd also like to see studies that include other possible sources of discrimination (gender identity, age) that are known to exist in some areas. Without those other sources included in the data it's possible those sources could be skewing the data.
One scenario might be that most of the women were young (20s-early 30s), while many of the men were older (late 30s to early 50s). Just one possible scenario, I'm not saying that was the case. But in that scenario the bias could be against older candidates rather than for female ones.
The graph on page 13 was interesting. The gender distribution of applicants stays about the same, but the gender distribution for hires has dropped for men and risen for women. So were the women previously dropping out of the workforce? Do we now have men dropping out of the workforce? Or are they simply being reshuffled among the various companies within the industry? I ask this because there are other studies that say the industry in the US is facing a shortage of tech workers, so it seems unlikely to be that a significant number of people would be dropping out, or that this study accurately represents the industry as a whole.
That could be. I have seen women managers in charge of hiring who had a more balanced team. However, my anecdotal experiences are nowhere near enough of a sample to draw real conclusions from.
If there are fewer women going into tech, that also may represent a problem. Here I have more personal experience, as my daughter is interested in digital graphic design and programming. She has faced criticism for this choice from peers, and from teachers, and online. Several people commented that the tech world is too hard for women. Perhaps fewer women are going into tech because they are being discouraged at a young age, if this pattern of discouragement turns out to be widespread.
There are some efforts to fix this that have been getting more attention, including Girls Who Code [https://girlswhocode.org].
Also, thanks for the s/majority/minority catch. I've edited the original post to fix.
In my anecdotal experience the split happens pretty early, in early high school at the latest. All the people who were interested in computers in my grade 9 class were male.
"We need more studies in this area. I'd also like to see studies that include other possible sources of discrimination"
I'd love to see this based on culture and personality too.
I've been on teams that seem to look down on you if you live within your means and thus aren't able to fully participate in discussing the latest gadgets, like people's new Tesla's and BMWs when you drive a no-frills work truck that doesn't even have blue tooth. I actually had a manager tell me I need to discuss gadgets and sports more with my coworkers. Even if I like gadgets, I like the lower cost and hands on stuff like setting up a Zoneminder server rather than installing a Ring.
I'm also a quiet person who tries to focus on work when at work. I speak up when I have ideas or can help out. Yet I'm constantly being told to speak up and form stronger relationships with my team. I feel we have a good working relationship. Why can't I value them as a coworker and have them value me based on our work interaction?
You mentioned personality, which would be an awesome study to see.
I knew a manager once who insisted every person who joined his large project take a Myers-Briggs Type Indicator (MBTI) personality profile test [https://www.myersbriggs.org/my-mbti-personality-type/mbti-ba...] and give him the results. No idea if that's allowed, but as far as I know nobody refused. He was government, I'm hesitant to try it as a contractor team lead. I also don't have a big enough team where I need to do that, and prefer to let folks self-organize organically. My job is to remove friction, not add it.
He then used that information to organize his teams with the goal of improving collaboration and team performance, and it seemed to work well.
Okay, honest question coming from ignorance. In computing at least, there's a well known diversity disparity going back to STEM graduation rates.
It seems financial is a similar boat: Wells Fargo recently claimed a “limited talent pool" but got criticized by AOC
for lacking "talent to recruit Black workers".
Obviously society, including industry, could do more to get kids into school. But right now, in the resume pile, what should employers be doing, and why is "not enough X talent" not a good defense?
The pipelines have problems for sure but this study was about whether or not a focus on diversity in hiring was effective.
I think the important bit is here:
> Our results in light of these considerations suggest that the push for diversity without any effort towards inclusion is unlikely to be sustainable in the long term.
There's a lot of implicit assumptions around this stuff that actually matter a lot, and the demographics of the actual candidate pool [0] as opposed to the general population is a huge one. I would venture that most people pushing diversity agenda want representation to match the general population, but that may not be supported the candidate pool.
As you point out, it's well studied that women don't graduate with STEM degrees at a rate that matches the general population. That means that for every company that matches general population for women in STEM fields, there's other companies that literally cannot unless they hire unqualified women from outside the candidate pool.
[0] I'm defining this as the group of all possible people who are qualified to be hired into a role.
I'm reminded of a quip I came across in the conversation around the George Floyd killing - "Being a black man in America is like being a man only more so".
I guess in the case of SV hiring outcomes, this is literally true!
So according to this, high-potential women are receiving a pay premium. But I thought the BLS listed tech jobs as one of the few industries that does have an actual wage gap favoring men?
Searched the article for "visa" and "migrant" found no results, surely that hugely skews the data with respect to Asians?
I fully imagine there is bias towards Asians within SV but it'd be heavily weighted towards recent arrivals who either have uncertain visa status or aren't yet at native speaking English proficiency surely? Whereas you'd have to imagine the vast majority of black applicants meet both of those requirements with ease.
It's the same with truly blind dating, isn't it? If you deprive yourself from the knowledge of the gender of your candidate for partner, you'd become a truly inclusive pansexual astral being in the dating scene.
> Using matched sample
analyses and controlling for a rich set of job and applicant attributes found in applicants’ resumes and LinkedIn profiles, we find that women are 9-10% more likely to receive a callback
compared to men, whereas Black, Hispanic, and Asian applicants are 8-13% less likely to receive
a callback compared to White applicants. These outcome gaps do not cancel-out in the later
stages, as female and White applicants are more likely to receive an interview and offer
How accurate this is, however, depends a lot on how well controlling for applicant attributes worked.
> An obvious set of confounders
is the applicant’s objective qualifications such as years of experience, educational attainment, and
field of study, all of which affect the outcome of an application. It is widely known that many of
these attributes differ across demographic groups – for example, women are less likely to major in
STEM subjects, Asian Americans are more likely to have graduate degrees (Camilie Ryan and Kurt
Buaman 2015). To account for these confounds, we control for total years of experience, average
tenure, educational attainment (associate or less, bachelors, masters, and doctorate), field of study,
and rank of the university attended (Top 10, 21-50, 51-10, ). For experience controls, we use the total number of years of experience at the time of application parsed from resume text. For average
tenure, we divide the total years of experience by the number of jobs held. For university rank, we
parse the Education section of the applicant’s LinkedIn profile and join this against the U.S News
Global University Rankings list. If an applicant attended multiple universities, we take the lowest
rank. For the field of study, we parse the Education section of the applicant’s LinkedIn profile
and bucket them into one of the following categories: Technical – mathematics, computer science,
engineering, economics, etc. Business – business administration, finance, accounting, marketing,
etc. Law – law and legal studies. Science – natural sciences such as biology, chemistry, etc. Other
– all other majors.
> An applicant’s professional and social network is another important signal that employers use
to screen applicants (Fernandez and Weinberg 1997; Sterling 2014). Since one’s network tends
to be demographically homogeneous, the effect of gender and race could be confounded by these
affiliations. We control for this in two ways. First, we use a Referral indicator from the ATS,
which indicates whether an applicant has a referral from an existing employee of the firm. Second,
we identify whether an applicant has worked at the company’s talent competitor. We identify a
company’s talent competitors by taking the top 10 companies from which its current employee
pool comes from based on all of LinkedIn data. For example, to identify Company A’s talent
competitors, we first search for all the employees of Company A using all of LinkedIn data. Once
these employees are identified, we look at the previous company these employees worked at before
joining Company A. We then aggregate these previous companies by count, and take the top 10
companies from which Company A’s current employee pool comes from.
> Finally, an applicant’s skills, previous job responsibilities, and fit for the job to which they
applied are perhaps the most important factors in determining the success of an application. We
operationalize this using a text-analytics method called Word2Vec to measure the similarity between
skills and competencies listed in the applicant’s resume and the job description (Mikolov et al.
2013). To do so, we first train a Word2vec model on a corpus of resumes. Using this model, we
transform each document (i.e resumes and job descriptions) into a vector representation based on
skills listed in each document, and measure the cosine similarity between the resume vector vR and
job description vector vJ . The higher the cosine similarity between the job description and resume vector, the better the fit. This type of approach is often used in automatic application screening
tools
I'm skeptical that this actually captures what hiring managers or recruiters care about when looking at resumes, which means I'm not sure I trust the callback numbers. Submitting identical resumes with different demographic characteristics seems like a much more appropriate experimental approach here?
As for whether candidates receive an offer, they don't have anything here where they have actually evaluated the candidates' skills. I've given over 200 technical interviews, and resumes are just not that good a predictor of technical competence. It really doesn't seem to me like they have good enough controls to run this as a correlational experiment.
> I'm skeptical that this actually captures what hiring managers or recruiters care about when looking at resumes,
You're in the tech industry and you honestly are skeptical that recruiters and hiring managers at most companies aren't extremely eager, to say the very least, to hire female candidates?
But regardless of whether the outcome fits your priors or not, you may wish to know whether the study has decent evidence, or is just noise.
And GP has a good point. The authors have some automated scheme for grading how well-qualified people are. The recruiters also have some such scheme. If these two schemes differ, and the distributions aren't identical between the groups being compared, then you will detect group differences like what they see. To label these differences bias in the recruiter's process, you must be confident that you have less bias in your process. The details of this correction are going to be crucial.
Yes, it's a good point. I made a snap response, and was wrong to do so. I just get tired of the ideological nonsense I see so often propogated by a certain group in the tech industry.
Yes, but the list of criteria they use for controls is pretty reasonable and more importantly, unbiased by woke ideology. We all know many firms have a very strong bias towards women that grades them as more well qualified (desirable to hire), so we'd expect a re-run using purely objective metrics to detect that. The outcome of this study isn't a surprise, the only surprise is that the bias is "only" 10%.
That the bottom line results be plausible is not enough. It matters whether the study is a good source of evidence for its claims. Otherwise none of us have any reason to update our views in response, and the study has no value as information.
They do in their model. Being Asian carries with it the worst relative odds of being hired, though it is not responsible for the overall negative non-white male coefficient (Black and Hispanic applicants also have negative coefficients in the logit)
Seems to make sense relative to each other. D&I initiatives often times target Black and Hispanic candidates, but not Asian since they are not underrepresented.
And also separating out Indian, Chinese, and Other Asian. The majority of many tech workforces are broadly Asian, along with over half of the global population. It doesn't make sense to lump them all in together. It may be acceptable in other industries in the US where Asian representation is in line with the US standard of ~6%, but certainly not in tech. If a single bucket accounts for more than half of your entire sample, and that bucket can trivially be broken down further into sub-buckets, then you should absolutely do so.
This is something that tech in particular just keeps getting wrong over and over. E.g. look at the 2019 Google diversity report [1] -- on page 52 it shows that 55.5% of new tech hires in the most recent year were Asian, vs 0.7% for the smallest category (Native American). Break out that 55.5%, please!
If the medicine has more side effects than the indication, it might be time for an honest review.
In my experience there is little discrimination in tech. I am located in Europe and maybe other factors apply. But here you could be a raccoon and if you have an affinity for tech, you can almost get the job you like.
edit: On the contrary, I think these talk about discrimination drives people away, but I hold back my criticism because I think people mean well.
Yes, fashionable in that suggesting we live in a deeply unequal society(not true) shows that you're one of the "good guys". Its just a social signal and at this point people have been hearing/saying it for so long that most probably believe people should be judged by the color of their skin, rather than your personality.
These callback rates are relative to the number of applicants, so if the pool of applicants is predominantly Asian, the hires could still be predominately Asian, just slightly less so.
The only problem with blind selection, is that, sooner or later, the race/gender/sexual orientation/religion/fitness/attractiveness/age (I'm an old fart, so I can tell you a thing or two about ageism in tech) becomes apparent.
I have heard story after story from peers (around my age), about passing numerous rounds of phone and test interviews, only to see the interviewer's face fall, as soon as they walk in the door. It's happened to me, but, thankfully, before being flown out (if it's a contract application, then we're on the hook for the cost), and revealing the age.
It happens with highly qualified older white guys, so I'm sure that it will happen with other distinguishing characteristics.
The simple fact of the matter is, is that people have certain traits they are looking for, and the final call is always a "gut feeling."
I've learned to just avoid all the agita by making it clear that I'm "of a certain age," right up front. I don't get many offers, but at least I don't have those blasted recruiters, gushing about my résumé, only to shred my contact card, as soon as they find out I'm old (I guess the industry is crawling with 32-year-olds with 30 years' experience).
I don't think it's a good idea to have AIs do the selection (as has been suggested numerous times -usually by folks in the AI business). Humans need to work with humans. If an AI puts someone into a situation where they are treated like garbage by their managers and/or co-workers, then they will be miserable (and unproductive); especially if they have done something like uproot their lives to move somewhere (I have also heard many stories from people that have uprooted their lives to go to "the perfect" job, only to come back, a few months later, broken and cynical).
If the people involved don't want to work with someone like me, then I don't want to work with them. That's easy for me to say, though. It can really stink, when you're hungry and need the work.
Happened to me I aced everything and when the interview walked into the room I saw it on their face (too old). Thankfully that only happened once and the company wen under at some point thereafter so good thing I didn't get hired.
This is absolutely one of my nightmares. I'm turning 40 soon and I know my opportunities of being paid to write software will become more and more limited.
I'm noticing it now. I'll also be 40 this year. Getting through to the offer stages of the process has become impossible for me today, despite how well the phone screens, zoom calls, take-home tests, and technical interviews have gone. To be fair, I'm not actively seeking employment but I have had about a dozen job opportunities land on my lap this year that I have not outright rejected. I'm in the process of interviewing for yet another company. Like many of the others, I was recommended for the position internally by a former colleague but I assume it will go the same as the others.
> The only problem with blind selection, is that, sooner or later, the race/gender/sexual orientation/religion/age becomes apparent.
Changing the emphasis of your statement slightly, I think one of the gaps of focusing on blind selection is that by attempting to work around assumed biases within the org, even if it works perfectly in the hiring process, it does nothing for employees once hired (when presumably several of the traits you listed are not going to remain hidden). Blinding part of the hiring process doesn't help employees have equal access to projects, growth opportunities, involvement in decision-making, etc.
Exactly.
I think that it is sort of "darwinian." If a corporation doesn't establish a culture of excellence (whatever the measure may be), then they will get not-excellent results.
"Cultural fit" is important, but, as a former manager that had to make many accommodations for highly-qualified and diverse employees, it's also important for a team/company to be prepared to adjust their culture to get that excellence.
Oof that sucks and is scary, since we will all be older at some stage. Personally, I prefer having people older than me on my team (I'm 35) because they tend to have experience I and younger members don't have and that experience can save quite a lot of problems in the long run.
Sure, maybe older people aren't caught up on the latest fad tech, but most of that is BS anyway, so no biggy...
This is a really helpful framing of the same problem that hopefully everyone can relate to. You can be great at your job but still have fewer opportunities because of how you're perceived by the majority group.
Getting the hiring biases out of the way early makes sense to me. The downside is that this doesn't change the broader situation or challenge it in anyway. It just says: "go ahead and apply your biases if you have them". It think, in some ways, this practice could make things a lot worse overall. It allows companies to massage their diversity metrics in ways that are acceptable and not at all challenging to the notion of what "acceptable diversity" looks like.
This is why I actually believe there should be hiring quotas. Tell departments that at least XX% of their hires are expected to be woman, or older than 50, or racial minorities, or whatever else. Set the percentage based on the pool of applicants, minus a bit to allow wiggle room. (And if there are legal blockers, let's change the law!)
It feels wrong to me too, I know it does! But if hiring happens based on gut, and if our gut is biased, then we need a way to systematically counteract our biases.
Why do we need to systematically counteract our biases? Why is that right thing to do? And who decides what is right?
I was biased when I married, I’m biased when I pick people I’ll spend time with, I’m biased when I apply for a job, and wouldn’t like it to be any other way... Of course, unless it’s me deciding for everyone else what they should optimize for their decision making process.
Because people in power have said you must or face financial ruin, freedom of association be damned.
Well this might be taking it a step too far. The first, obvious step would be simply to compare the actual hires (workers) with the available pool... almost nobody actually does that. People keep claiming that e.g. Google is sexist because they hire so few women, without regard to the fact that their worker pool has about the same distribution as their hiring pool (CS graduates). The UK passed a law requiring companies to disclose average salaries by sex etc. with no regard on the actual job / education level / level of employment.
We can't even begin to talk about solutions if all the media / researchers / activists keep pushing misleading statistics.
> The first, obvious step would be simply to compare the actual hires (workers) with the available pool... almost nobody actually does that.
I absolutely agree! (And that's also why I said in my post that the percentage should be determined by the applicant pool.)
There's a separate conversation to be had about why the applicant pool is skewed, but IMO that's well outside a given company's purview.
There is an alternative explanation to the biases people are seeing here, unfortunately, and it would render gender and age confounding variables.
It's known that Valley tech firms of the type studied in this paper have a large left wing contingent amongst employees. We know that being female with a degree correlates quite well with being left wing, as does being young. In contrast being an older white male correlates somewhat with being conservative.
If the actual discrimination here is against "people likely to be conservative" - which is absolutely likely to be happening given what's going on in these firms - then setting quotas for gender and age wouldn't be addressing the underlying problems, only symptoms.
> The only problem with blind selection, is that, sooner or later, the race/gender/sexual orientation/religion/fitness/attractiveness/age (I'm an old fart, so I can tell you a thing or two about ageism in tech) becomes apparent.
This too is a problem we can solve with technology:
https://www.dailymotion.com/video/xqrvzb
I've been thinking of making sure that my age is clear on my LinkedIn/resume/etc., for just this reason. Even then, it's clear that quite a few interviews I've gone on have been "fake", in the sense of being useful for EEOC stats, but with no bona fide intention to hire. Which is frustrating, because at the end of the day, interviews are themselves unpaid work.
These days, I've "solved" the problem by just taking lower-paying jobs. No one I work with really understands what I do--they just know that when they bring me the harder problems, they generally get solved. It's kind of nice in a way to be king, even if it is in a puddle.
Fair or not, the market always wins. And if the market tells you that you're not wanted, best to go elsewhere.
This is one of the worst case scenario, but there's any variation where it works better than the traditional method.
At first contact you could have been packed in the "meh" group, but by virtue of coming out of the recruiting process your peers won't stop at that first reaction and take time to make it work.
Even if you were to be dismissed at the first face to face with a manager, it seems to me it's still better than if it was by some random HR intern that would have had no impact on your day to day work.
Dismissing blind test/interviews because there can still be later discrimination would be throwing the baby with the bath water IMO.
This paper is a prime example of not accounting for Simpson's paradox: "These numbers suggest that women and White applicants are proportionally more likely to get hired compared to their counterparts." No, you haven't given us the men/women breakdown by ethnicity. It may actually be that there is an over-representation of women in the white category compared to other ethnicities, and therefore the bias towards hiring females carries with it a bias towards hiring white. However it's possible that if you compare ethnicities separately between men and women you might find no racial discimination exists.
(and vice versa for ethnicity vs gender).
The fact that they don't show these breakdowns is a major weakness of this study.
Or strength. Depending on whether the desired metric is scientific correctness, or political marketability.
There's a fascinating study on orchestra auditions, where it was found that performing blind auditions (where the interviewee's identity is hidden to the interviewer) led to more equitable gender representation: https://gap.hks.harvard.edu/orchestrating-impartiality-impac...
IMHO, if the tech industry wants to live up to its narrative of meritocracy, this is one obvious improvement over existing processes. No, it won't take care of pipeline problems; no, it won't solve the "tipping point" problem (i.e. where candidates of underrepresented groups are dissuaded by a lack of pre-existing representation, making it very hard to go from zero to one, so to speak). That said, we're uniquely positioned as an industry to do this - technical interviews are similar to auditions in that they hinge on skill-based performance - so why not? It can't be any less arbitrary than asking random questions about manhole covers and light bulbs.
I'd posit that even the "show your thinking process" parts could be done in this way - e.g. via text chat, or inline comments, or maybe even using voice obfuscation and/or neutral avatars.
> performing blind auditions (where the interviewee's identity is hidden to the interviewer) led to more equitable gender representation
There has recently been quite a bit of pushback on this: https://www.nytimes.com/2020/07/16/arts/music/blind-audition...
> It can't be any less arbitrary than asking random questions about manhole covers and light bulbs.
Asking random questions about manhole covers and lightbulbs doesn't work very well! Don't take that as your comparison.
Well of course the people who want to hire by race want to get rid of blind auditions!
You may want to read https://statmodeling.stat.columbia.edu/2019/05/11/did-blind-...
“One of the more interesting findings of the study that I have not often seen reported: overall, women did worse in the blinded auditions.”
This happens all the time, the media will find one aspect of a study and blast it from on high while ignoring any parts that hurt their agenda.
A particularly infamous example of this is studies of drug use by race: https://www.icpsr.umich.edu/quicktables/quickconfig.do?34481...
You'll see news outlets claiming that black and white drug use rates are the same, but they're going off of the "Have use ever used X?" questions while completely ignoring the ones about how often they've used X, which shows a clear racial discrepancy. That's before you get into issues like the study being based on self reporting, or the vast majority of drug crimes that result in jail time being ones related to dealing and not mere use, etc.
To believe that blind applications would help increase female representation presupposes that they're being discriminated against right now, when TFA shows that women are getting preferential callbacks. That completely jives with my experience: most female candidates are highly, highly sought-after, and are quickly hired by top tech companies (leaving smaller companies looking bad in the process, despire their equal desire for female candidates).
Blind applications would probably hurt female representation. It's possible it would help minority representation.
It seems to me that if you choose something that is completely equitable in who is able to participate, then the rest of it sounds like manufacturing dissent by companies or corporations that want a "leg up" on the competition in the D&I category, which is all the rage these days in terms of marketing. Maybe there are other reasons women don't want to enter these fields, but prefer to wholly dominate others, and maybe that we should turn the conversation to this being OK. We've spent so many cycles trying to "figure this out" when there is research after research that just shows women don't prefer the "rat race" as much as men, and gravitate towards roles that focus on helping, nurturing, and community, hence why they dominate roles where those are highlighted: teachers, administrators, nurses, psychologists, etc.
There's never going to be a feeling of "service" or caring when you are writing ad-tech for a FAANG. It's just not going to happen, no matter how many D&I articles you write.
I agree.
There has been research on demographics pertaining to college majors and their career opportunities in the context of why some demographics make less money than others after graduating with a 4 year degree. One of the main factors that came up in the interviews was, like you said, the lower earning demographics wanted to have a bigger community impact, but that those jobs simply paid less money (like social workers).
I once went to a members-only hackerspace that was very open and equitable, at least in theory. To join, you had to get a recommendation from another member and support from one more. They held regular open days and were very welcoming but definitely had an established subculture that didn't include much diversity. Joining really meant being the friend of a member or possibly a friend of a friend. If you were an outsider, you'd really need to show them you were already a part of their sub-culture before they'd consider you. Openness to diversity really meant openness to conforming to an existing culture before joining.
Diversity and inclusion is an extremely hard thing to get right or even to agree on what "right" means. I don't think anybody would agree that diversity issues are fixed now and so it can't be "time to turn the conversation to this being OK". As I pointed out in my story above, lots of people can't even see that there is a present and persistent problem despite the good intentions around fixing it. That's exactly why we need to pay more attention to studies like this.
You seem keen to switch to a conversation about nature instead of having one about nurture/culture (there were a few historical arguments about race that took a similar approach). Perhaps these two are so intimately bound that it's not helpful to make observations about one in the abstract. Instead, should we not simply focus on those things we can change and try our best to ensure the inequalities of the past aren't reflected in the culture of today? It's not about some set of absolute outcomes, its about the absence of bias - an outcome I'd hope we were all on-board with.
> Openness to diversity really meant openness to conforming to an existing culture before joining.
Why is this a problem? I've been progressing most of my life, but I came to software development relatively late in life. The culture was dramatically different from that of my prior profession.
> women don't prefer the "rat race" as much as men
It's not just that. Money is like make-up for men. It's obvious why men would put more effort (on average) in acquiring it.
> Blind applications would probably hurt female representation.
Isn't this good for gender equality?
Harvard's argument is that selecting candidates based on merit means we discriminate against those who had a harder time building merit and is therefore racist/sexist.
Some people believe girls don't study CS in large numbers because programming is "a boys' job" which is a self-perpetuating cycle; and a limited period of substantial positive discrimination could turn it into a gender-neutral job that appealed to men and women equally.
Other fields, like medicine, law and chemistry have radically changed gender composition since the 1940s so it's not unprecedented for an industry to lose its gender bias.
Personally I think it's far from certain such an effort would work - or that it wouldn't.
> most female candidates are highly, highly sought-after, and are quickly hired by top tech companies
Let's say we believe that women are on average equally as capable of men, and we know there are maybe 10-20% as many women in the industry.
Are those 10-20% women roughly as good as the average man, or are they roughly as good as the top 10-20% of men? Have they had the same experience as average men, or have they fought through and survived discriminatory barriers?
Even if we suppose the answer is somewhere in-between, it wouldn't be surprising that women are highly sought-after. Because with these assumptions, the women in the industry are generally likely to be better on average.
Maybe we don't observe discrimination against women in this specific context* (post-application and pre-salary negotiation), but that doesn't mean it isn't occurring elsewhere.
*The summary data includes non-technical hires at tech companies
Your assumption relies on the women getting into the field are the best women. I don't see why that would be true. The fields with many women like law, medicine or psychology are much harder to get into than computer science or engineering so most of the best women likely ends up there.
Given that as a woman you don’t benefit from the “competency bias” and constantly has to prove yourself (which is not necessarily bad), combined with the fact that many women simply walk out of careers in computer science and physics because of sexism/harassment, you could consider that the women left are indeed more competent than the average man in the industry.
Women do benefit from likeability bias though, and likeability is certainly a factor when hiring and firing.
As for fake resume studies, the problem with those is that male and female resumes are evaluated differently. If they made a male looking resume and sent it out with a female name it will do badly. But a female looking resume with a male name will also do badly.
What does a male/female looking resume mean? (Genuinely asking. I can't imagine that a female engineering accomplishment is vs a male engineering accomplishment.)
I'm curious also, but anecdotally, women were over-represented in my engineering school's societies and probably under-represented in design competitions.
There are plenty of research done on gendered words. Like highlighting your own personal excellence or skill is more masculine etc. There are also of course that men and women tend to have different hobbies and therefore spends their free time doing different things. So one new grad might have done some leadership roles in a horse club while the other maybe did some chess competitions.
https://www.idealrole.com/blog/gender-job-ads
Does this mean if you're a woman and you highlight your own personal excellent in your resume you're statistically likely to be treated worse? Similarly if you're a man and you have a leadership role at a horse club you're statistically likely to be treated worse?
Thought experiment: These biases are mostly shared among people so you got them in yourself. Instead of thinking "What is the ideal software engineer", think "what is the ideal feminine software engineer" and "what is the ideal masculine software engineer". The picture in your head will be very different. If you are a woman you will be compared to the ideal feminine engineer while as a man you get compared to the ideal male one.
The prime example is the term "bossy", women get called this since they are expected to be much more cooperative than men. I think a very big issue right now is that we use men as a standard and say "when women use male strategies they get pushback for being too masculine", instead to gain individual success they should try to be like successful women. In an ideal society this wouldn't be the case, but as is these biases exists and so you have to work with them.
And as a personal anecdote, when I looked for jobs as a new grad when I used more cooperative and less personal excellence I didn't get any callbacks. I got lots of callbacks when I focused on personal excellence though. Its as if companies assumed I was less competent just because I talk about teamwork, because their ideal masculine software engineer wouldn't talk like that. You can see here how it works:
https://hbr.org/2018/10/how-men-get-penalized-for-straying-f...
Edit: The moral of the story is that when we tell men to be more feminine and women to be more masculine we just hurt them. Men and women aren't evaluated by the same metrics. People told me "Companies expects you to be a teamplayer, try to highlight that!", but it was clearly wrong and didn't help me at all.
That's the opposite of what happens. My own experience has been that women benefit dramatically from a "being a woman" bias that makes them much more likely to be hired - exactly what this study now quantifies - and in addition be basically unfireable even if they have severe skills or attitude problems.
The whole idea that there's a competency bias towards men is false. What's actually being observed is that women are hired even when they aren't competent, to please feminists and diversity advocates, which then by definition would make men "appear" more competent even if they were of only average competency.
Wouldn't you need to have evidence of discrimination before you start to discriminate against other groups in the name of women? Women might actually get a backlash for that and you have the classic self-fullfilling prophecy. Why not try a revolutionary approach and treat people equally, everyone to their best ability as their conscience allows?
We would need to scrap esoteric models about bias and have very simple rules that everybody understands?
Do you mean evidence or indisputable proof?
The quality of evidence needs to be very, very high to justify discrimination in my opinion.
And if people responsible for awarding research grants within tech decide not to investigate whether there is discrimination against women, or tech companies decline to give full access to their data.
Then the quality of evidence that you demand can't exist - in that case, should nothing be done about it?
Maybe it is hard to generate, but without it you have no basis to justify your discrimination. I think that people specifically denied policies that allows it by intrinsic discrimination is a very good and sensible step and should continue to be regarded as the better approach.
If you want to discriminate without sufficient evidence, I am plainly not with you on this.
It is the simplest form of power play to treat people differently because it breeds jealousy. Jealously can lead to discrimination as well. You can do that as a team leader and be sure that people are more concerned with each other than holding you accountable. This is actually a common behavior in corporate office culture which had many tech flee the premises because they had a choice.
But there is quite simple and obvious evidence of discrimination: the percentage of technical jobs which go to women.
Not accepting this as evidence and demanding that your own standards for evidence are met (without saying exactly what that would involve, so you could later reject any other evidence that is provided) before allowing any corrective action, is yet another way that this discrimination is perpetuated.
When I studied CS and electrical engineering we started with 120 students. 5 were women. 15 students made it in regular time from which 1 was a women.
You conclusion isn't obvious, on the contrary, there are contradictions. Where should the women in tech have come from?
Would you also think that nurses discriminate against men? No, you only think discrimination is an issue in spaces where men are overrepresented. That is sexism.
> allowing any corrective action
If the reasoning is already that bad, I have very little faith in this corrective action.
> Would you also think that nurses discriminate against men? No, you only think discrimination is an issue in spaces where men are overrepresented. That is sexism.
Ah yes, the hallmark of good faith discussion asking a question and answering it for them.
A rhetorical question is not a bad faith approach to discussions contrary to leveling the accusation itself. The argument is still there if you want to have a go at it.
> When I studied CS and electrical engineering we started with 120 students... 15 students made it in regular time
That sounds like a shockingly badly organised course with many barriers to success. Such barriers to success are likely to fall harder on women and minorities (who are more likely to have caring duties, less support in their social network, and will face general discrimination).
With even the facts you have given, it would be unsurprising to me that disproportionately few women bother to apply: even ridiculously fewer women start than on a typical course.
I would be embarrassed if I were an educator or organiser for that course.
> Would you also think that nurses discriminate against men?
No. Although this is not directly analogous to anything I have said, I am giving a good faith answer. I think that nursing is an underpaid profession because it is seen as women's work - just as caring work is often unpaid. I'm not aware that men face significant barriers when they choose to enter nursing.
The careers in which men are over-represented and women are under-represented tend to be highly-paid and/or prestige jobs. So, that's quite a different situation and points to societal discrimination by gender against women.
Computer Science as an industry is relevant here in that: women were initially over-represented, until it came to be seen as a prestige career and started garnering higher pay, and now they are increasingly under-represented.
I agree that it is undervalued and maybe because it is seen as a women's job, but that part is speculation. I live in a country with stronger social systems and there are countless interests that keep the pay as low as possible. You would not find a single person that says that nursing isn't important.
As I said, you if you want to have a tech job, you currently almost can choose where to work. Men and women alike, so I cannot see that many barriers.
I don't buy into the prestige argument at all, it feels far removed from reality. I didn't pick my profession because of prestige and I don't think many people do. This isn't the showbusiness. Do you know what people with strong affinity to tech were called? Nerds. The good payrate is very recent, as are the gender discussions btw.
> where candidates of underrepresented groups are dissuaded by a lack of pre-existing representation
I don't understand this persepective from candidates. The job market must be really good if they can use this as a metric for pursuing a job opportunity. I was the only person from my country when I joined my current employer. It never even crossed my mind that it could be an issue.
There was also a post on HN a few months ago that said asking minorities to attend things like recruiting fairs in order to show the diversity of the employer was unfair.
It's a chicken and egg situation for employers.
At my company, you have a leg up if you fit one of the diversity metrics and are applying for a job.
I've worked on teams where I'm the only one of my race. I've been on group projects where I'm the only one of my gender. Based on the conversations I've heard on some of the teams I've been on, I have a minority political view and culture/lifestyle as well. It's almost never a problem unless you believe or think it is a problem. There can be rare cases where you get someone who is actively trying to make it a problem, but that tends to be rare. So I don't see it as a chicken or egg issue, I see it as mindset problem.
By 'chicken and egg' I meant that employers can't really do much about minority candidates not accepting a job offer because there aren't any/enough of that candidate's gender/race already employed.
Thank you. Your experience in not suffering from discrimination clearly invalidates all of the millions of people who do. It's clearly all in their head.
It boggles my mind on people's basic inability to realize that not everyone has the same experiences in life as them. And rather than accept other peoples experiences as valid, it's always the same argument of "I haven't had to deal with this therfore they don't either."
Yes they want to be in a situation where they can just ignore it and it won't be an issue, the problem is they don't have that luxury. It's great that you do, but that doesn't change their circumstances.
I never said it doesn't exist. I'm sure there are people who are victims of discrimination. Where's your proof of the millions who do suffer from workplace discrimination in tech every year? More specifically, how do you see the chicken and egg problem posed in the parent comment not being a mindset issue?
I've actually seen women on twitter say something like "if your company doesn't already have women, we're not interested, stop your pretending to care about diversity and women's issues" or something to that effect. How will the situation ever change, then, though? Its most definitely a chicken and egg problem for employers.
We talk a big game about merit, capability, qualifications and such.
Ultimately though, nearly all actual selection processes are are subjective or ilegible... depending on how you see these things. How an interviewer feels about you intuitively matters a lot, maybe the most. Actual tests of skill are usually intuitive as well. An interviewer tries to gauge your skills, but it's rarely designed to be an objective test of skill. If it is an objective test of skill, it's rarely the primary decision driver.
Blind auditions enforce a certain kind of objectivity. But, I think we can read into the fact that musicians "audition" while employees "interview." You perform an audition.
Blind auditions would be a radical change to hiring/selection. The big advantages/disadvantages of the approach are like those of standardised testing. They measure the easily measurable, and bury everything else.
> an objective test of skill
Other industries/careers have exactly this: a professional licensing exam. Most programmers vehemently oppose any sort of standardized testing.
I'm curious, what do you want to test? The classic "memorize how to bubblesort" interview questions which so many people complain about because they don't show anything except that someone has prepared? Isn't it better to just look over the code of applicants and check if they are aware of general structures etc?
Obviously some familiarity with algorithms etc is required and it should be checked if that's there, but with tests you can't really test if someone understands the bigger picture and did not just memorize the answer. I know more than enough people who can solve problems just fine but their code is absolutely atrocious and I'd never hire them. Interviews where one can ask them why they write code the way they do are probably far more effective.
Here's an article detailing an experiment with voice gender changers in online interviews:
https://blog.interviewing.io/we-built-voice-modulation-to-ma...
Get on with the times friend, we need to eliminate blind auditions now.They discriminate:
https://www.nytimes.com/2020/07/16/arts/music/blind-audition...
"Blind auditions are based on an appealing premise of pure meritocracy"
Damn, how did we get here?
By saying nothing years ago when "diversity" became popular and people started arguing there weren't enough women in computing. I'm as guilty as anyone, in the beginning it all seemed harmless enough. It wasn't, it was based on sexism from day one, and now we see the consequences: proven and massive bias towards women at an institutional level. And good luck trying to fix it.
California Prop 16 just attempted to overturn bans on racial/gender discrimination when hiring.
https://en.m.wikipedia.org/wiki/2020_California_Proposition_...
The people advocating for more representation almost invariably are not interested in removing discrimination on arbitrary characteristics, which is a near universally laudable objective, but rather work backwards from the demographic representation they'd like to see.
https://www.nytimes.com/2020/07/16/arts/music/blind-audition...
If you think that the diversity and equity initiatives within companies are currently working towards anything resembling a blind hiring process, I get the impression that you're not particularly up to date on the objectives of the modern left.
I wish they had broken out the other ethnicities separately in the abstract. The reasons that Black and Hispanic people might be getting fewer callbacks relative to whites are likely quite different from the reasons that Asian people might be getting fewer callbacks.
I'm making my way through the main paper but there's a lot of tables in there that would take me a lot of reading to decipher and it's really not clear which are best to use for any purpose. The tables do break out the separate ethnicities separately though (along with callback/interview/offer rates, not just callback) and it does appear that Black, Hispanic, and Asian very much do not have the same experience. In particular, the graph on page 22 seems to show that, when it comes to receiving offers, female candidates have a 29.5% advantage in receiving offers, Black 4%, -21% Asian, and -24% Hispanic. The previous column (received interview) is much worse for Asian, Black, and Hispanic applicants though; all were significantly less likely to receive interviews than whites.
Anyway, there's lots of potentially good data in here, assuming you trust their methodology, but I personally feel like I need someone who knows this stuff better to write up a longer abstract based on all this data to really explain it to me properly.
As far as I can tell, the paper doesn't seem to control for citizenship or immigration status. It seems likely that Hispanic and Asian job-seekers, especially in Silicon Valley, would be much more likely to be from overseas and therefore require a work visa.
I don't know about Hispanic per se but I definitely see that being true of Asians, and yes, it's a potential confounding factor. Would love to know if the longer paper addresses it.
At this one job, we had only two remotely viable candidates for an open position. I was on the hiring committee, as I often was in those days.
Candidate A: Had worked in the industry, had all of the qualifications, already chock-full of some interesting ideas I wanted to hear more of from the interview alone. Excited at the prospect.
Candidate B: Had never worked in the industry, had only a handful of qualifications, barely responsive. Seemed indifferent to getting the job. Additionally, not too fluent in English, to the point where it was more than a little difficult to communicate.
Candidate A was a white man, Candidate B was a recent immigrant and a woman. The immediate supervisor for the position -- a woman -- wanted Candidate A, as did most others. However, the person running the show said, out loud I might add, that our group already had "too many pale males." I would like to repeat that: too many pale males. A significant glance was then cast at me and the guy in the wheelchair on the hiring committee, both being not-particularly-dark men. Presumably by "virtue" of our disabilities we would automatically be down for the Diversity Squad.
Candidate B was hired and turned out exactly as she was in the interview: disinterested in doing the job, lacking even some bare understanding of how to accomplish many things, always trying to find ways to do her grad school homework while on the job and pushing off her duties on someone else, rather than trying to learn her tasks. Her poor English was a significant barrier. She remained a leaden weight until she went off to be someone else's problem. She wasn't a drag due to her skin color or sex, but she was hired because of those things.
My guess is that this kind of discrimination (I use that word specifically) goes on all the time in at least some segments of the industry.
I always try to give the recruiter no indication of race or gender. Frankly, if we all did that it would remove the bias.
The challenge is, I suspect they ask for race & gender is intentionally requested to add bias. I’ve worked with recruiters and part of the job is indeed targeting “under represented” groups to improve the figures.
Well, you do give them their name, that's a strong indication of race and gender for most people, isn't it?
Sure, my name is unisex though. Race might be obtained, but honestly even that is questionable
It only seems questionable because of your specific name. If your first name was Zhang or Priya, your race would also be quite obvious.
> Race might be obtained, but honestly even that is questionable
If you mean "irrevocably determined with a 100% certainty" maybe...
But you know, most people who think their name doesn't give away their race, are a certain race...
-
Funny that this is really such an uncomfortable truth for some people here... I'm a black guy with a Ghanaian name, so I laughed out loud reading the comment.
It's not like black people aren't allowed to have "euro-centric" names, but, surprise surprise, Caucasians represent a large majority of people with those names
Likewise there are names that almost no Caucasians have (like mine)
If someone is reading your resume intent on being biased, a name like "Austin Walters" is going to appear as... a white guy.
There black guys named Austin Walters but they're also not conducting a census... if someone really wants to discriminate against you based on race, your name is plenty to go on.
https://www.mynamestats.com/First-Names/A/AU/AUSTIN/chart-di...
https://www.mynamestats.com/Last-Names/W/WA/WALTERS/chart-di...
Again, they're not conducting a science study, an 80% chance is plenty for the kind of person trying to discriminate...
Likewise, someone who reads my name, which uses consonants in a way that English doesn't usually ( causing people to mispronounce my very simple last name even when reading it verbatim) will instantly assume I'm black.
It's something I accept as a person with a very black name, it tells you the main audience of HN is this is really such a revelation for some of you lol
Gender and social class, the latter of which has been shown to be a the discriminating factor in some industries in many countries.
Unfortunately, the study finds that the bias persists even past the initial stages:
> These outcome gaps do not cancel-out in the later stages, as female and White applicants are more likely to receive an interview and offer.
Though it does at least help candidates avoid bias in getting a callback:
> To further address endogeneity concerns, we perform quasi-experimental analysis involving applicants whose race and gender are ambiguous to the recruiter in the initial application review stage, but are later revealed in the phone screen stage. We find that ambiguity in applicants’ race and gender attenuates the main effects of race and gender on receiving a callback – that is, the outcome gap in callback disappears for applicants whose race and gender are ambiguous to the recruiter
Me too, I sound white too. I've noticed reactions when a Hispanic looking guy shows up.
I have 6 kids, their mother is white. I've heard stories from each of them that range from kids asking, "why is your dad brown and you're pink?" to "My parents were surprised when that brown guy showed up to pick you up."
I can confirm that at least two FAANG companies explicitly give diversity points to recruiters. That is, hiring a "diverse" candidate is worth ~1.5x as much to them as a non-diverse candidate for the same role.
They are cagey about the exact details of who is included at a given time. But I do know it varies by rule.
Honestly, I think this is a worse situation than before.
Of course it is. Using unchangeable physical characteristics is terrible and what we should eliminate it completely.
Unfortunately the political correct movement today has decided that racial discrimination is best solved with even more racial discrimination.
*by role
It would be nice if we could just hire people based on the necessary experience and regardless of how people were born or how they look; features they have no control over
Unfortunately seems like a pipe dream for the human race right now, cheers to those who try though.
Based on the research paper, it doesn't look like they're biasing towards underqualified minority candidates.
In the paper they controlled for "years of experience, average tenure, past employment at a talent competitor, education, university rank, referral status, and skills." Even with the initiatives you mention, Black (-6%), Hispanic (-9%), and Asian (-13%) applicants are less likely to be called back.
Personal experience.
Got hired into a company that did everything possible to avoid hiring straight white men.
Everything was completely dominated by not offending anyone over anything. Unless you were the aforementioned group.
Turns out there simply isn’t a lot of the right race/gender/sex. I’m sure that’ll be different as time progresses, but for now there is clearly some catching up to do.
So it was all jr developers. A couple of which truly cared about technology, and I see good things in their future.
The rest were the most arrogant sexist bigots imaginable.
Most days were filled with hatred. Full rant fest about how evil “my kind” were. But it wasn’t personal as I was clearly one of the good ones...
So yeah, n=1 personal experience. But crude that echo chamber was scary.
So what you're saying is that.. I am responsible for my happiness, and that other people are not to blame for the choices I made in regards to my behavior and life, especially straight white men?
Wow, that's a hard cookie to swallow.
(for the ones who read this far, what I wrote is sarcastic).
That's one of the reasons I left tech and went to work for an investment bank. At least here no one pretends to be in it to "make the world a better place" or whatever agenda tech companies are selling nowadays. YMMV
Ugh, that's one thing I really hate about much of tech: supposedly everyone is in it to make the world a better place, somehow, by actually making it worse through advertisement and destroying privacy and getting people addicted to social media.
It's because they only want the world to be a better place for themselves.
I’ve come to see it as people naturally tend to an US vs Them attitude.
Sports is a fairly safe outlet for this sort of thing.
Religion is a bad one to have that attitude. Holy wars, etc.
Race is dangerous, as history is full of exterminations.
The idea that "race is dangerous" is dangerous.
They're saying it's dangerous to have an Us vs Them attitude when it comes to race.
Treeman is surely a he ... and a singular person... gosh this rape of language is so ugly
I assure you we are a natural born Pine-tree.
That your post is on the top shows the "white male" bias in hackernews audience. People are up-voting your personal anecdote and your "I am a white male victim" post more than the discussions about the actual results on the original article.
The post reveals the hackernews bias against discrimination in all forms, regardless of whether it is targeted at minorities or white males. Meritocracy baby!
All hatred needs to stops.
I totally agree. But shouldn't we trust the data more than one person's anecdote? The original article clearly did not find any discrimination against white male. Rather than discussing that result, we are here commenting about one person's anecdote.
>The original article clearly did not find any discrimination against white male.
How do you interpret women getting 10% more callbacks if not as discrimination against males?
The demographic working in CS nearly reflects demographics that study CS or other relevant degrees. Ever asked yourself if it may be your bias that is the root of the accusations for discrimination? Because with the evidence available you can make that case.
> Got hired into a company that did everything possible to avoid hiring straight white men.
Same here. Like you mentioned, anecdotes are not data.
But likewise - I was pressured to specifically hire a female / non-white developer for my team.
Personal experience.
Worked in a group that did everything possible to avoid hiring, acknowledging, and rewarding women's contributions.
Everything was completely dominated by one-upmanship and crude jokes. Unless you were in the in-group, you were screwed.
I don't doubt your annecdote. I guess all I can say is, welcome to the club? Being part of the "out group" in a toxic workplace sucks. I've had men come up to me and say, "Wow now I get it." Because in their entire lives they had only worked on male dominated teams, and working on a toxic non hetero non male dominated team made them really uncomfortable, they were fine working on toxic hetero male dominated teams. All the norms had changed and they didn't know what to do. But until they experienced it themselves didn't get "what the big deal" is.
I stay in tech because I don't want to be forced to take a lower salary because of cultural attitudes that women being around "ruins the atmosphere". But yes if I had a pile of FU money, I would bail in a second, not because I'm busy taking care of children or whatever excuse, but because people are insecure, emotionally immature and create a great deal of toxicity.
Had a brief stint in a place like that. Bunch of good ole boys club. Yes all young white males
Got out of their as fast as possible. It’s disguising to see how they treated woman. I’m trying to raise my daughters to never put up with that.
Thank you.
And once again a race study that doesn't list Native Americans at all. It would be nice if they remembered 2% of the US population, since certain policies ("Actual Name") have discriminated against Native Americans because of the ignorance of silicon valley firms. AIHEC and American Indian College Fund (collegefund.org) could really use the help to get placements for students.
They don't care about you because you're not a politically influential demographic. Notice how the demographic that dominates this debate is the second most privileged and influential demographic in the country: white women; yet they are portrayed as being some powerless minority.
It's always powerful demographics fighting each other. Nobody cares about the actual minorities that have no representation. That is almost tautological.
If it makes you feel better, you're not alone - middle eastern is never broken out either. In fact - we're grouped with white people. Some of us are white passing - some of us are very much not. Fun article about it... https://www.latimes.com/projects/la-me-census-middle-east-no...
I can tell ya - after 9/11 - being middle eastern sure didn't feel like being white!
Personal anecdote:
I knew someone who worked as a recruiter at Boeing a few years ago, and she told me the pressure from higher ups to give preferential treatment to female applicants was crazy. She said they couldn't explicitly discriminate, but would use things like "Women in Tech" events to try to increase their female applicant pool.
Surprising study results regarding women being more likely to receive a callback than men. From personal experience and the teams I've been on, women have always been in the minority, along the lines of 8-10 men for every two women. However, I am not in Silicon Valley.
We need more studies in this area. I'd also like to see studies that include other possible sources of discrimination (gender identity, age) that are known to exist in some areas. Without those other sources included in the data it's possible those sources could be skewing the data.
One scenario might be that most of the women were young (20s-early 30s), while many of the men were older (late 30s to early 50s). Just one possible scenario, I'm not saying that was the case. But in that scenario the bias could be against older candidates rather than for female ones.
There's a contradiction in your second sentence, I'm not sure what your meaning is.
>women have always been in the majority, along the lines of 8-10 men for every two women.
From context I think they meant that "men have always been in the majority".
Yes, thanks - it was meant to be minority. I've fixed in the original post.
There are less women in the tech industry, so it is very possible for them to be more likely to get a callback and still be underrepresented.
The graph on page 13 was interesting. The gender distribution of applicants stays about the same, but the gender distribution for hires has dropped for men and risen for women. So were the women previously dropping out of the workforce? Do we now have men dropping out of the workforce? Or are they simply being reshuffled among the various companies within the industry? I ask this because there are other studies that say the industry in the US is facing a shortage of tech workers, so it seems unlikely to be that a significant number of people would be dropping out, or that this study accurately represents the industry as a whole.
>From personal experience and the teams I've been on, women have always been in the [minority], along the lines of 8-10 men for every two women.
That's because fewer women overall are applying for such jobs relative to men. Those that are applying are more likely to be hired.
That could be. I have seen women managers in charge of hiring who had a more balanced team. However, my anecdotal experiences are nowhere near enough of a sample to draw real conclusions from.
If there are fewer women going into tech, that also may represent a problem. Here I have more personal experience, as my daughter is interested in digital graphic design and programming. She has faced criticism for this choice from peers, and from teachers, and online. Several people commented that the tech world is too hard for women. Perhaps fewer women are going into tech because they are being discouraged at a young age, if this pattern of discouragement turns out to be widespread.
There are some efforts to fix this that have been getting more attention, including Girls Who Code [https://girlswhocode.org].
Also, thanks for the s/majority/minority catch. I've edited the original post to fix.
In my anecdotal experience the split happens pretty early, in early high school at the latest. All the people who were interested in computers in my grade 9 class were male.
"We need more studies in this area. I'd also like to see studies that include other possible sources of discrimination"
I'd love to see this based on culture and personality too.
I've been on teams that seem to look down on you if you live within your means and thus aren't able to fully participate in discussing the latest gadgets, like people's new Tesla's and BMWs when you drive a no-frills work truck that doesn't even have blue tooth. I actually had a manager tell me I need to discuss gadgets and sports more with my coworkers. Even if I like gadgets, I like the lower cost and hands on stuff like setting up a Zoneminder server rather than installing a Ring.
I'm also a quiet person who tries to focus on work when at work. I speak up when I have ideas or can help out. Yet I'm constantly being told to speak up and form stronger relationships with my team. I feel we have a good working relationship. Why can't I value them as a coworker and have them value me based on our work interaction?
You mentioned personality, which would be an awesome study to see.
I knew a manager once who insisted every person who joined his large project take a Myers-Briggs Type Indicator (MBTI) personality profile test [https://www.myersbriggs.org/my-mbti-personality-type/mbti-ba...] and give him the results. No idea if that's allowed, but as far as I know nobody refused. He was government, I'm hesitant to try it as a contractor team lead. I also don't have a big enough team where I need to do that, and prefer to let folks self-organize organically. My job is to remove friction, not add it.
He then used that information to organize his teams with the goal of improving collaboration and team performance, and it seemed to work well.
Okay, honest question coming from ignorance. In computing at least, there's a well known diversity disparity going back to STEM graduation rates.
It seems financial is a similar boat: Wells Fargo recently claimed a “limited talent pool" but got criticized by AOC for lacking "talent to recruit Black workers".
Obviously society, including industry, could do more to get kids into school. But right now, in the resume pile, what should employers be doing, and why is "not enough X talent" not a good defense?
https://www.washingtonpost.com/business/2020/09/23/wells-far...
The pipelines have problems for sure but this study was about whether or not a focus on diversity in hiring was effective.
I think the important bit is here:
> Our results in light of these considerations suggest that the push for diversity without any effort towards inclusion is unlikely to be sustainable in the long term.
There's a lot of implicit assumptions around this stuff that actually matter a lot, and the demographics of the actual candidate pool [0] as opposed to the general population is a huge one. I would venture that most people pushing diversity agenda want representation to match the general population, but that may not be supported the candidate pool.
As you point out, it's well studied that women don't graduate with STEM degrees at a rate that matches the general population. That means that for every company that matches general population for women in STEM fields, there's other companies that literally cannot unless they hire unqualified women from outside the candidate pool.
[0] I'm defining this as the group of all possible people who are qualified to be hired into a role.
I'm reminded of a quip I came across in the conversation around the George Floyd killing - "Being a black man in America is like being a man only more so".
I guess in the case of SV hiring outcomes, this is literally true!
So according to this, high-potential women are receiving a pay premium. But I thought the BLS listed tech jobs as one of the few industries that does have an actual wage gap favoring men?
Searched the article for "visa" and "migrant" found no results, surely that hugely skews the data with respect to Asians?
I fully imagine there is bias towards Asians within SV but it'd be heavily weighted towards recent arrivals who either have uncertain visa status or aren't yet at native speaking English proficiency surely? Whereas you'd have to imagine the vast majority of black applicants meet both of those requirements with ease.
It's the same with truly blind dating, isn't it? If you deprive yourself from the knowledge of the gender of your candidate for partner, you'd become a truly inclusive pansexual astral being in the dating scene.
> Using matched sample analyses and controlling for a rich set of job and applicant attributes found in applicants’ resumes and LinkedIn profiles, we find that women are 9-10% more likely to receive a callback compared to men, whereas Black, Hispanic, and Asian applicants are 8-13% less likely to receive a callback compared to White applicants. These outcome gaps do not cancel-out in the later stages, as female and White applicants are more likely to receive an interview and offer
How accurate this is, however, depends a lot on how well controlling for applicant attributes worked.
> An obvious set of confounders is the applicant’s objective qualifications such as years of experience, educational attainment, and field of study, all of which affect the outcome of an application. It is widely known that many of these attributes differ across demographic groups – for example, women are less likely to major in STEM subjects, Asian Americans are more likely to have graduate degrees (Camilie Ryan and Kurt Buaman 2015). To account for these confounds, we control for total years of experience, average tenure, educational attainment (associate or less, bachelors, masters, and doctorate), field of study, and rank of the university attended (Top 10, 21-50, 51-10, ). For experience controls, we use the total number of years of experience at the time of application parsed from resume text. For average tenure, we divide the total years of experience by the number of jobs held. For university rank, we parse the Education section of the applicant’s LinkedIn profile and join this against the U.S News Global University Rankings list. If an applicant attended multiple universities, we take the lowest rank. For the field of study, we parse the Education section of the applicant’s LinkedIn profile and bucket them into one of the following categories: Technical – mathematics, computer science, engineering, economics, etc. Business – business administration, finance, accounting, marketing, etc. Law – law and legal studies. Science – natural sciences such as biology, chemistry, etc. Other – all other majors.
> An applicant’s professional and social network is another important signal that employers use to screen applicants (Fernandez and Weinberg 1997; Sterling 2014). Since one’s network tends to be demographically homogeneous, the effect of gender and race could be confounded by these affiliations. We control for this in two ways. First, we use a Referral indicator from the ATS, which indicates whether an applicant has a referral from an existing employee of the firm. Second, we identify whether an applicant has worked at the company’s talent competitor. We identify a company’s talent competitors by taking the top 10 companies from which its current employee pool comes from based on all of LinkedIn data. For example, to identify Company A’s talent competitors, we first search for all the employees of Company A using all of LinkedIn data. Once these employees are identified, we look at the previous company these employees worked at before joining Company A. We then aggregate these previous companies by count, and take the top 10 companies from which Company A’s current employee pool comes from.
> Finally, an applicant’s skills, previous job responsibilities, and fit for the job to which they applied are perhaps the most important factors in determining the success of an application. We operationalize this using a text-analytics method called Word2Vec to measure the similarity between skills and competencies listed in the applicant’s resume and the job description (Mikolov et al. 2013). To do so, we first train a Word2vec model on a corpus of resumes. Using this model, we transform each document (i.e resumes and job descriptions) into a vector representation based on skills listed in each document, and measure the cosine similarity between the resume vector vR and job description vector vJ . The higher the cosine similarity between the job description and resume vector, the better the fit. This type of approach is often used in automatic application screening tools
I'm skeptical that this actually captures what hiring managers or recruiters care about when looking at resumes, which means I'm not sure I trust the callback numbers. Submitting identical resumes with different demographic characteristics seems like a much more appropriate experimental approach here?
As for whether candidates receive an offer, they don't have anything here where they have actually evaluated the candidates' skills. I've given over 200 technical interviews, and resumes are just not that good a predictor of technical competence. It really doesn't seem to me like they have good enough controls to run this as a correlational experiment.
> I'm skeptical that this actually captures what hiring managers or recruiters care about when looking at resumes,
You're in the tech industry and you honestly are skeptical that recruiters and hiring managers at most companies aren't extremely eager, to say the very least, to hire female candidates?
But regardless of whether the outcome fits your priors or not, you may wish to know whether the study has decent evidence, or is just noise.
And GP has a good point. The authors have some automated scheme for grading how well-qualified people are. The recruiters also have some such scheme. If these two schemes differ, and the distributions aren't identical between the groups being compared, then you will detect group differences like what they see. To label these differences bias in the recruiter's process, you must be confident that you have less bias in your process. The details of this correction are going to be crucial.
Yes, it's a good point. I made a snap response, and was wrong to do so. I just get tired of the ideological nonsense I see so often propogated by a certain group in the tech industry.
Yes, but the list of criteria they use for controls is pretty reasonable and more importantly, unbiased by woke ideology. We all know many firms have a very strong bias towards women that grades them as more well qualified (desirable to hire), so we'd expect a re-run using purely objective metrics to detect that. The outcome of this study isn't a surprise, the only surprise is that the bias is "only" 10%.
That the bottom line results be plausible is not enough. It matters whether the study is a good source of evidence for its claims. Otherwise none of us have any reason to update our views in response, and the study has no value as information.
Are we still going to call it Silicon Valley when everyone is remote?
Key point of the abstract:
Anyway, kudos (I guess?) to the researchers for choosing the absolutely most fashionable subject they could possibly study in this day and age.
Would be interesting to separate Asian applicants into their own group.
They do in their model. Being Asian carries with it the worst relative odds of being hired, though it is not responsible for the overall negative non-white male coefficient (Black and Hispanic applicants also have negative coefficients in the logit)
Seems to make sense relative to each other. D&I initiatives often times target Black and Hispanic candidates, but not Asian since they are not underrepresented.
And also separating out Indian, Chinese, and Other Asian. The majority of many tech workforces are broadly Asian, along with over half of the global population. It doesn't make sense to lump them all in together. It may be acceptable in other industries in the US where Asian representation is in line with the US standard of ~6%, but certainly not in tech. If a single bucket accounts for more than half of your entire sample, and that bucket can trivially be broken down further into sub-buckets, then you should absolutely do so.
This is something that tech in particular just keeps getting wrong over and over. E.g. look at the 2019 Google diversity report [1] -- on page 52 it shows that 55.5% of new tech hires in the most recent year were Asian, vs 0.7% for the smallest category (Native American). Break out that 55.5%, please!
[1] https://kstatic.googleusercontent.com/files/25badfc6b6d1b33f...
"Fashionable"? Being so dismissive of the push for racial equality is deeply arrogant and small minded.
If the medicine has more side effects than the indication, it might be time for an honest review.
In my experience there is little discrimination in tech. I am located in Europe and maybe other factors apply. But here you could be a raccoon and if you have an affinity for tech, you can almost get the job you like.
edit: On the contrary, I think these talk about discrimination drives people away, but I hold back my criticism because I think people mean well.
Yes, fashionable in that suggesting we live in a deeply unequal society(not true) shows that you're one of the "good guys". Its just a social signal and at this point people have been hearing/saying it for so long that most probably believe people should be judged by the color of their skin, rather than your personality.
What made you think I am dismissive of "the push for racial equality"?
That's surprising - every software team I've worked on for the past 20 years at least has been predominantly Asian.
These callback rates are relative to the number of applicants, so if the pool of applicants is predominantly Asian, the hires could still be predominately Asian, just slightly less so.