I have a small set of interview questions I prefer to choose from, in part because I've given them quite a bit of thought.
I would be sad if I had to switch questions after 20 or 30 candidates because I find it necessary to invest substantial effort in calibrating a new question. Before I ask a candidate a new question, I try use it to mock interview at least 10 people I have worked closely with. Iteration is always required to tune the difficulty and complexity of a question, so the total time invested in a question can be quite high.
One way that I keep questions well-calibrated is that I use them to mock interview other members of the interview panel. This serves at least two purposes: one is to constantly remind myself what realistic answers sound like and another is the help the rest of the panel understand the areas my question will cover.
I find that — for me — this type of mock interviewing and the subsequent retrospective cultivate empathy for candidates. I think this avoids the sort of bias you're observing.
(NB: Some of this may be specific to the kinds of questions I ask; I care less about the initial answer a candidate gives than their ability to self-assess their answer or incorporate feedback to improve their solution.)
There's also the fact that after giving the interview question for a while, you know what are the issues that candidates struggle with and can figure out how to help them.
If you're interviewing correctly, your job as an interviewer is to ensure that the candidate succeeds during the interview. For example, one question might require to check if two intervals overlap. There are multiple ways to check if they do. One can enumerate all possible ways that they can do (first interval fully contained within the second one, second interval partially overlapping with the first one, etc.) but this quickly grows into a complicated conditional. At that point, if the candidate struggles, you can mention "how would you check that two intervals don't overlap at all?" which is a much easier test that can then be inverted by the candidate.
What the interviewers should be looking for is if the candidate can think through a problem, can split it in smaller steps, can solve each step and is able to integrate each small step into a complete whole.
> I find it necessary to invest substantial effort in calibrating a new question. Before I ask a candidate a new question, I try use it to mock interview at least 10 people I have worked closely with.
You could do that some process, with the interviewee.
It would be a great way to see how collaborative they are.
i.e. you say "I've never actually worked through this problem myself, so I don't know how deep the rabbit hole is, but let's give it a crack and see what we come up with together."
Sounds a lot more like real-life to me than a manufactured question you've already worked through to the nth degree.
I don't think this would give me sufficient data to compare candidates in an unbiased way.
Without establishing objective criteria with which to evaluate candidates, it's much easier to fall back on decision making processes that are prone to unconscious bias.
A manufactured question may seem impersonal, but that's the point.
I would be sad if I had to switch questions after 20 or 30 candidates because I find it necessary to invest substantial effort in calibrating a new question. Before I ask a candidate a new question, I try use it to mock interview at least 10 people I have worked closely with. Iteration is always required to tune the difficulty and complexity of a question, so the total time invested in a question can be quite high.
One way that I keep questions well-calibrated is that I use them to mock interview other members of the interview panel. This serves at least two purposes: one is to constantly remind myself what realistic answers sound like and another is the help the rest of the panel understand the areas my question will cover.
I find that — for me — this type of mock interviewing and the subsequent retrospective cultivate empathy for candidates. I think this avoids the sort of bias you're observing.
(NB: Some of this may be specific to the kinds of questions I ask; I care less about the initial answer a candidate gives than their ability to self-assess their answer or incorporate feedback to improve their solution.)