16 December 2015
This article was largely inspired by Jessica Nordell’s post on Medium. And HUGE thanks to Lara Hogan for talking this through with me and giving me some really great feedback and ideas before I published it.
My co-worker Tim and I teach an interview training class at Etsy every quarter or so. Tim’s rad, and he came up with the core metaphor of our class, which he calls “mapping the potato.”
Basically the idea of the potato is this: your job as an interviewer is to try to find the candidate’s limits. In as caring and supportive a way as possible, you explore the limits of their knowledge, their skill, their empathy, their problem solving, their communication, etc. The different kinds of limits can be thought of as vectors in space. As you find limits along different vectors, you start to form a very rough idea of the “shape” of who a person is – that shape is the potato.
This is noisy and inaccurate and when I think about this potato-shape in my head it’s usually some fuzzy, shimmering blob that changes shape every time you look at it.
Another nice thing about this metaphor is that it illustrates the complexity of the problem. There are lots and lots of different places people have strengths and weaknesses, the data is noisy and “lumpy” and vague, and different areas of the potato all matter more or less when deciding whether a candidate would be a great fit for a particular role on a particular team at a particular company.
So the potato’s fun and useful, right? I dig it.
Stephen Jay Gould wrote an amazing book called The Mismeasure of Man (here’s a really good summary). In this book, Gould talks about tests, such as IQ, which try to reduce intelligence to one number. Gould demonstrates two primary problems with this: first, the kinds of questions that are asked to “determine” something like IQ and the way they are analyzed are implicitly biased; second, it’s impossible to map an abstract concept like “intelligence” onto a simple number – Gould calls this “reification”. Using Tim’s analogy, reification is saying you know everything about a particular potato when all you have is a week-old french fry.
So, there are white men in positions of power (building an engineering org, deciding who to fund) implying that hiring diverse candidates means that some “bar” has to be “lowered.” Going back to Gould’s thesis, this is alarming in a) the false implication that diverse populations somehow don’t meet b) some reified “bar” that’s a projection of a mind-bogglingly complex set of traits which can basically really only be guessed at, with varying but generally low degrees of accuracy.
Now, I know for a fact that “bars” get “lowered” for some candidates, because people have lowered the shit out of them for me many times. I’m white, I speak the nerd argot (see?), and I taught myself to code when I was 12. Because of this, every company I’ve ever interviewed at has overlooked the fact that I don’t have a college degree, my GPA both in high school and in the brief period that I was actually in college was abysmal (2.0ish, for reference), I routinely flake out on work to go hiking or bike-riding for months at a time, and – as a small degree of probing would uncover – my organizational skills are pathologically bad.
Can you imagine a female candidate, or a black candidate, with no college degree and a high school GPA of 2.0 getting an interview at Microsoft in 1994? At Google in 2005? I have a really hard time imagining that. I don’t know anyone who fits that mold, but I know plenty of white dudes with histories a lot like mine.
There were obvious biases in play that netted me interviews and jobs at those places – biases that basically let me get away with doing less work than most people, and far less work than people who aren’t playing with the settings on easy.
To bring that back to the potato metaphor: there are parts of my potato-space that are pretty much empty, but in spite of that there’s an implicit assumption that other parts of the space are “better” or more filled-in. The flip-side of that kind of unconscious bias is that in many cases, candidates who don’t fit a particular mold (in other words, candidates who aren’t white dudes) are saddled with the assumption that their strengths aren’t as good – interviewers or managers or VC-funders assume that they’re lacking strength. If they didn’t assume that, why in the world would they say that they wouldn’t “lower the bar” to hire diverse candidates? So these candidates are handicapped before they set foot into an interview, before they say a word, before their resumés are even looked at.
Hiring and interviewing are much more akin to literary criticism or philosophy than they are to math. People are complicated and opaque and what you see in people has as much to do with you as it does with them. How people perform in various situations – coding at a whiteboard, answering behavioral interview questions, being a member of a team, shipping something valuable – are at best vaguely correlated with each other. Low or noisy data situations are places where unconscious biases thrive. The best ways to fight this are to be aware of your biases, and gather more data.
If you don’t do the work to become aware of your biases, and you don’t gather more data about people you’d like to work with or fund with VC money or accept to school or etc., you are doing both them and yourself a disservice. It’s not fun work to confront your own biases, and learning more about people is hard (though not as hard as learning about yourself). Learning about others is especially hard for many of us techies who are introverted and not used to it. It is, however, your obligation, both in a strictly moral sense, and in the sense that you are obligated to your co-workers to find more great co-workers, and you are falsely limiting yourself if you can’t transcend limits that society has imagined to exist.