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fleg [soylentnews.org] writes:

interviewing.io is a platform where people can practice technical interviewing anonymously. Its described as a collaborative coding environment with voice, text chat, and a whiteboard

Over time they noticed a "disparity in interview performance on the platform between men and women."

We had amassed over a thousand interviews with enough data to do some comparisons and were surprised to discover that women really were doing worse. Specifically, men were getting advanced to the next round 1.4 times more often than women. Interviewee technical score wasn’t faring that well either — men on the platform had an average technical score of 3 out of 4, as compared to a 2.5 out of 4 for women.

They decided to run an experiment to investigate bias against women in technical interviews. They did this by making men sound like women and women sound like men and then looked at how that affected interview performance.

Result?

Contrary to what we expected, masking gender had no effect on interview performance with respect to any of the scoring criteria (would advance to next round, technical ability, problem solving ability).

So whats going on?

Women leave interviewing.io roughly 7 times as often as men after they do badly in an interview. And the numbers for two bad interviews aren’t much better.

However...

Once you factor out interview data from both men and women who quit after one or two bad interviews, the disparity goes away entirely. So while the attrition numbers aren’t great, I’m massively encouraged by the fact that at least in these findings, it’s not about systemic bias against women or women being bad at computers or whatever. Rather, it’s about women being bad at dusting themselves off after failing, which, despite everything, is probably a lot easier to fix.

The article [interviewing.io] is worth reading in full as there's a bunch of details.

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