July 29, 2020

Gender guessing software

A company called Genderify has what they say is “an AI-powered tool for identifying the gender of your customers”. This is an example of something that is not worth doing (asking is easy and reliable; people will be upset when you get it wrong), but also very difficult.

After seeing some examples on Twitter, I decided to try it on some senior members of the Stats department (whose gender identity I’m reasonably confident of)

“Thomas Lumley” is 63.90% likely to be male and 36.10% likely to be female, and you have to like the four digit precision. But “Dr Thomas Lumley” is 89.40% likely to be male, and “prof thomas lumley” gets up to 94.60%!

“Ilze Ziedins” is 85.20% likely to be male, which will surprise her. “Dr Ilze Ziedins” gets to 96.00%

“James Curran” is 99.60% likely to be male, adding “Dr” or “Prof” gets him up to 99.90%

“Rachel Fewster” is at 72.00% likely to be male, adding her professorial title puts that up to 95.40%

“Renate Meyer” is at 62.30%, her doctorate moves that up to 88.20%, and her promotion to professor makes it 94.00%

Note that none of these are classically gender-neutral or gender-ambiguous names: no Hadley or Hilary or Cameron.  The overall level of accuracy is pretty terrible to start with — but the response to adding qualifications is bizarre.  If that wasn’t in the basic pre-release testing, then what was?

Even better (worse):  it’s not just that adding “Dr” or “Prof” make it think you’re more likely mean a man, adding “Dame” also does.

 

Update: on Twitter, (Dr, Prof) Casey Fiesler raised the possibility that Genderify are just trolling, which I must say is looking quite plausible.

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Thomas Lumley (@tslumley) is Professor of Biostatistics at the University of Auckland. His research interests include semiparametric models, survey sampling, statistical computing, foundations of statistics, and whatever methodological problems his medical collaborators come up with. He also blogs at Biased and Inefficient See all posts by Thomas Lumley »