Most startups, statistically speaking, are going to fail.
And they will fail regardless of whether they hired “the best” due to circumstances largely beyond their control. So in that context does maximizing for the best possible hires really make sense?
Given the risks, I think maybe “hire the nuttiest risk junkie adrenaline addicted has-ideas-so-crazy-they-will-never-work people you can find” might actually be more practical startup advice.
.. If your hiring attitude is that it’s better to be possibly wrong a hundred times so you can be absolutely right one time, you’re going to be primed to throw away a lot of candidates on pretty thin evidence.
.. Perhaps worst of all, if the interview process is predicated on zero doubt, total confidence … maybe this candidate doesn’t feel right because they don’t look like you, dress like you, think like you, speak like you, or come from a similar background as you? Are you accidentally maximizing for hidden bias?.. One of the best programmers I ever worked with was Susan Warren, an ex-Microsoft engineer who taught me about the People Like Us problem, way back in 2004:
I think there is a real issue around diversity in technology (and most other places in life). I tend to think of it as the PLU problem. Folk (including MVPs) tend to connect best with folks most like them (“People Like Us”). In this case, male MVPs pick other men to become MVPs. It’s just human nature.
- .. Using screens to hide the identity of auditioning musicians increased women’s probability of advancing from preliminary orchestra auditions by fifty percent.
- Denver police officers and community members were shown rapidly displayed photos of black and white men, some holding guns, some holding harmless objects like wallets, and asked to press either the “Shoot” or “Don’t Shoot” button as fast as they could for each image. Both the police and community members were three times more likely to shoot black men.
.. It’s not intentional, it’s never intentional. That’s the problem. I think our industry needs to shed this old idea that it’s OK, even encouraged to turn away technical candidates for anything less than absolute 100% confidence at every step of the interview process. Because when you do, you are accidentally optimizing for implicit bias. Even as a white guy who probably fulfills every stereotype you can think of about programmers, and who is in fact wearing an “I Rock at Basic” t-shirt while writing this very blog post*, that’s what has always bothered me about it, more than the strictness. If you care at all about diversity in programming and tech, on any level, this hiring approach is not doing anyone any favors, and hasn’t been. For years.
.. I would argue, quite strongly and at some length, that if you want better diversity in the field, perhaps a good starting point is not demanding that all your employees live within a tiny 30 mile radius of San Francisco or Palo Alto. There’s a whole wide world of Internet out there, full of amazing programmers at every level of talent and ability. Maybe broaden your horizons a little, even stretch said horizons outside the United States, if you can imagine such a thing.
.. The most significant shift we’ve made is requiring every final candidate to work with us for three to eight weeks on a contract basis. Candidates do real tasks alongside the people they would actually be working with if they had the job. They can work at night or on weekends, so they don’t have to leave their current jobs; most spend 10 to 20 hours a week working with Automattic, although that’s flexible. (Some people take a week’s vacation in order to focus on the tryout, which is another viable option.) The goal is not to have them finish a product or do a set amount of work; it’s to allow us to quickly and efficiently assess whether this would be a mutually beneficial relationship