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Isn't this wrong at some level? I support the idea of promoting programs like Women In Engg., but hiring based on race/gender is so wrong. Do you lower your hiring bar to get the numbers you've aimed for? And assuming some of these employees turn out to be under-performing, how do you deal with the appraisal process?

I'm not sure if Pinterest posted this article with some other intent (like having more support programs), but in it's current state, it seems discriminatory.



This very common assumption -- which I used to hold -- has it exactly backwards. Let's assume tall people and short people are equally good at cracking eggs. Mathematically, if 90% of your egg-crackers are short, you've already hired under-performing egg-crackers. You've passed over some really good tall people in favor of the short people you hired. If you want the best egg-crackers, you need to interview a bunch of tall people.


This analysis has its own flaw. This assumes that their other opportunities are also equal. But tall people may make better apple pickers. And apple picking pays more than egg cracking. If you want 50% tall people, you are going to need to compete directly against the apple picking market as well. You need to account not just for your own selection criteria, but that of everybody else as well. (Not to say this actually explains tech demographics; it's a point about the stats in your example.)


If 90% of all egg-crackers are short, and you want to hire the best egg-crackers, it's very likely that 90% of your egg crackers are going to be short.


If 90% of all egg-crackers are short, it's likely that there's a huge problem driving tall egg-crackers out of the field.


That's a bit specious. 90% of nurses are female but there's nothing driving men out of the field.


Do you know any male nurses?

There actually are things driving men out of the field. Look at how many head nurses are male. Men in nursing is a problem as well. But this isn't NurseNews, it's HackerNews.


Let's assume tall people and short people are equally good at cracking eggs.

Umm, in the actual example we are talking about, the evidence is on the side of that assumption being false: https://news.ycombinator.com/item?id=9977751 https://jaymans.wordpress.com/jaymans-race-inheritance-and-i...


> Let's assume tall people and short people are equally good at cracking eggs. Mathematically, if 90% of your egg-crackers are short, you've already hired under-performing egg-crackers.

In fact, this depends on the underlying population sizes of tall vs. short people, so this is a faulty argument.

More germane to the situation, however, is your initial assumption, whose analogue is dubious. So much so, in fact, that it is taboo to even allude to it. cf. pg's "What you can't say".


The counter argument that I've heard most is that minorities are less likely to be hired than equally qualified members of the majority because of subconscious bias. Enforcing a quota is a sort of equalizer—formal discrimination in one direction in order to push back against informal discrimination in the other direction.

I'm not completely sold on the method, but the problem of subconscious bias in hiring is very well documented:

* Resumes with stereotypically White names receive 50% more callbacks than identical resumes with traditionally black ones. The addition of honors and special skills had a significant effect on the likelihood of White applications being called, but a statistically insignificant effect for the otherwise-identical African-American ones. http://www.nber.org/papers/w9873.pdf

* Applicants with male names are rated as more competent and offered higher starting salaries than identical applications with female names. Identical resumes with male names are called back more often than female ones. http://www.pnas.org/content/109/41/16474.full.pdf+html, http://advance.cornell.edu/documents/ImpactofGender.pdf

* Initial subconscious bias is logically justified post-hoc—in the linked experiment, the qualities deemed necessary for a position would actually be redefined by the person reviewing resumes depending on the gender of the applicants so that the male applicant's traits fit the position better. http://www.socialjudgments.com/docs/Uhlmann%20and%20Cohen%20...

There's quite a few more papers on the subject, it's easy to search for them. Depressing read all around.


If those studies are true, then the correct solution would be to:

1) ask people not include their names on their resume. Or don't use resumes at all. Create a web form application that does not require a name and only asks about the crucial skills you actually need.

2) Create a highly objective hiring process, such as this: http://sockpuppet.org/blog/2015/03/06/the-hiring-post/

I don't really buy that subconscious bias is the problem in tech. I've been part of a lot of hiring, we were actually consciously biased toward hiring women since we wanted better numbers. I had an objective interview process, always giving the same questions, and the hiring was still very disproportionately male whasian (the applicant pool was also very disproportionately male whasian, despite doing active reach out to woman-in-tech events).


1. I agree, this would be preferable and a great step for the initial screener. But that leaves the problem of the actual interview—the studies that I've seen test written resumes, because it's possible to ensure that two resumes are identical except for one variable in ways that you can't ensure that two interviews are identical. But it's highly likely that the bias would carry over to any interaction with the candidates, though I don't have any studies on hand that prove it.

2. Also agree that an objective method would be preferable, thanks for the link. Great read. IIRC, in the study I link in the third bullet point, forcing the person reviewing the resume to create a rubric before reading any of them greatly reduced the biased results. Having an objective process goes a long way. The point in the link about confident interviewers performing better in the traditional hiring process is definitely true, and also tied in a roundabout way to gender, funnily enough (women tend to be less confident than men: http://www.theatlantic.com/features/archive/2014/04/the-conf...).

It's definitely not the only problem—the pipeline is obviously skewed dramatically—but I don't see any reason why tech workers would be exempt from the biases of the general population as they've been studied. Maybe the drive to hire more women would counteract it, like in your example—that's the reasoning under which minority quotas are implemented, after all. The problem of subconscious bias is that it's not consciously recognizable by its very nature. It's just gut feeling. I know a site that uses association to try to test it for you, if you're interested: http://implicit.harvard.edu/.


It sounds like you were trying to correct for an assumed subconscious bias of "deep down, we really want to hire men." In my experience, though, decent people like you don't have that bias. What they do have is a subconscious idea that "good candidates will look like X," where X is a mental image of a male candidate. Both women and men are subject to this bias, and it's a lot harder to correct for. Simply asking the same set of questions to all candidates won't fix it, if the questions themselves have the effect of weeding out women.


Simply asking the same set of questions to all candidates won't fix it, if the questions themselves have the effect of weeding out women.

The questions I asked were representative of things we actually had to do on the job, for instance: "write code to spider a web site." Does that unfairly weed out woman?


Assuming a different race/gender is under the bar or will under-perform seems discriminatory.


I never said that they will. I'm just wondering how are they gonna do things differently to meet those numbers. I'm sure their current hiring process isn't biased towards a particular race/gender. To make it more balanced, are they planning to have a different hiring bar?


If it is similar to the Rooney Rule, no. The bar is the same, just required to consider a minority candidate.

I personally find tangible monetary value in employees with diverse backgrounds but I don't lower my bar. I just slightly discount sameness and slightly appreciate difference.

https://en.wikipedia.org/wiki/Rooney_Rule


@infosample, you are right. You cannot assume minorities and women will under-perform or are under the bar. The issue of people just don't give it enough thought when hiring. At the same time, you should not hire someone solely based on their gender or race. But if there are 2 candidates with very similar skill sets and meet the standards you are looking for, hire the one who will bring you more diverse background.


Consider the one who had to come farther to get to the same point, and what that implies about how they will go in the future.


This is why the discussion can't even happen, and why companies and universities still enforce percentages for underprivileged groups even though it is obvious discrimination (but it's "good" discrimination! Give me a break).

Person 1 says that enforcing a 50 people of type A and 50 people of type B when the number of qualified candidates is 20 and 80 will result in either hiring significantly fewer people in general, or hiring under qualified people of type A. People of type B are being passed over because of their race/gender/ethnicity. This is discrimination.

Person 2 says that implying that anyone of type A could be under qualified is itself discrimination, and this possibility should not be addressed or considered. Nothing can change because the issue cannot be discussed.


It helps to have a discussion when affirmative action and the Rooney Rule aren't conflated.

We have a tendency to assume type A is qualified and type B isn't. That is a natural bias based on evidence. We must actively subdue our biases if we want to overcome them, sometimes with rules.

I think we sometimes forget that the goal isn't to get a qualified employee but a successful employee. Qualifications generally leads to success but not always, so we should constantly question our qualification criteria.

White males have benefited from discrimination for a long time. White males have been discriminated against sometimes.

This article isn't about discrimination or affirmative action. It's about setting a goal to be more diverse, not by lowering the bar, or forced hiring, but through awareness, inclusion, and an opportunity to interview.

BTW, everyone's been given a chance they didn't deserve.


If you have 9 men who apply and 1 woman and they're all of equal skill, chances are a man will get it purely on probability.


Where I work, if we had 9 men and 1 woman of equal skill applying for a job the woman would get it hands down. I find most good sized companies would rather have that kind of diversity even when it's not official policy. Our team has a few women but still well less than 50%.


And it would be discriminatory to give the job to the women purely based on her gonads in such a scenario. Benevolent sexism is still sexism, but it seems people only care about it when it comes to holding doors rather than holding jobs.


For a site whose chief technical accomplishment is to allow women to pin and share cutesy images, I'm not sure having top talent really matters that much.


Congratulations on illustrating the problem of sexism in tech so well.

Your interest in the content they host has zero relevance to the technical challenges they face as a platform and heavily trafficked website.


I would hardly consider a troll post from an account less than half an hour old to be representative of the technology industry.


There are plenty of folks in our industry moonlighting as trolls, and plenty not outright trolling who still hold these sorts of attitudes.


And yet their post is still getting voted into oblivion, even when nobody knows who votes for what.


Yes, obvious trolling by a Nazi username gets downvoted. Yay us!

Unfortunately, biases are rarely so blatant. Many are even non-malicious and entirely unconscious, like how people tend to guess older ages for black youth than white youth. http://www.apa.org/news/press/releases/2014/03/black-boys-ol...


Yes, obvious trolling by a Nazi username gets downvoted. Yay us.

I still say they don't represent the technical community. And it's blatantly obvious they don't represent the HN community, given the downvotes.

I'm not saying there aren't biases, sexism, ageism, or racism in tech, but I'd appreciate it if you didn't point at the obvious troll and say "this right here is the face of tech".


I'd rather see more top women doctors, scientists, lawyers, civi, biomedical and chemical engineers. Not sure what having more women sit in front of a computer screen writing CRUD apps all day does for equality.


I'm really having a hard time imagining you're concerned about equality given the username.


Really? Pinterest is ranked #16 by Alexa in the US for internet traffic[1]. Do you really think running such a site with that much traffic doesn't require top talent?

[1] http://www.alexa.com/topsites/countries/US


Come on. This is not like Cancer research. Its a solved problem.


It's a solved problem in the sense that the 5% of work that yields 95% of benefits have already been done. But because of the massive user base small improvements at great cost can be worthwhile.


I hope that you're just a troll and not serious. Pinterest is one of the most visited sites in the world. It requires huge technical talent to handle that much traffic and data. WTF is wrong with you?


The fact that you immediately equated "diversity" to "lowering your hiring bar" and "under-performing" is as ignorant as it is insulting.

Women and brown people are not lower quality humans, and it has been shown over and over and over that companies who hire for diversity perform better.

http://lmgtfy.com/?q=do+diverse+companies+perform+better


I think ignorance is taking things out of context unnecessarily. I am assuming Pinterest already has an unbiased hiring bar. Yet, due to sheer probability, the number of other races get hired much more. Considering the number of applicants remain the same, how do you balance the race/gender without being biased to one race/cast?




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