Invisible Women: default female t-shirts

Apr 11

A short missive from me this week GFPs as I finally got the black lung and this is now me:

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the absolute worst thing about it is that I finally have to stop lording it over everyone with my superior immune system 😭 god, covid sucks doesn't it? I haven't even had a terrible time of it, but it's day 7 and my brain is still mush and every. little. thing. exhausts me and I am just so fed up of being exhausted all the time. Bl**dy little f*cker of a virus! WHEN WILL THIS END

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Gender data gap of the week

Sexism: When people say ‘people’ online they may mostly be thinking about men | New Scientist — www.newscientist.com An analysis of 630 billion words published online suggests that people tend to think of men when using gender-neutral terms, a sexist bias that could be learned by AI models

No, duh, rings the echo of a legion of GFPs who remember all the research from Invisible Women that showed just this:

A 2015 study identified the top five words used to refer to people in human–computer interaction papers published in 2014 and found that they are all apparently gender neutral: user, participant, person, designer and researcher. Well done, human–computer interaction academics! But there is (of course) a catch. When study participants were instructed to think about one of these words for ten seconds and then draw an image of it, it turned out that these apparently gender-neutral words were not perceived as equally likely to be male or female. For male participants, only ‘designer’ was interpreted as male less than 80% of the time (it was still almost 70% male). A researcher was more likely to be depicted as of no gender than as a female. Women were slightly less gender-biased, but on the whole were still more likely to read gender-neutral words as male, with only ‘person’ and ‘participant’ (both read by about 80% of male participants as male) being about 50/50. (IW, p.9)

Still, more data is always welcome, and this research is an interesting example of both the benefits and the dangers of AI. Benefits, because this scale of analysis is made possible by AI (and one of the things I've been most excited by in my research for the AI episode of the podcast is the potential for us to use the statistical power of algorithms to help us CLOSE the data gap and even maybe fix some biases), but also dangers, because as lead author April Bailey points out, "the same collection of texts scoured by this research is used to train a range of AI tools that will inherit this bias, from language translation websites to conversational bots."

“It learns from us, and then we learn from it,” says Bailey. “And we’re kind of in this reciprocal loop, where we’re reflecting it back and forth. It’s concerning because it suggests that if I were to snap my fingers right now and magically get rid of everyone’s own individual cognitive bias to think of a person as a man more than a woman, we would still have this bias in our society because it’s embedded in AI tools.”

Default FEMALE of the week

YEAH THAT'S RIGHT. This week's break from standard operating procedure comes courtesy of GFP Michelle who made me laugh far too much with this picture of her packing label from Myer, which, she informs me, is a large department store in Australia.

The first two listed items, labelled as "MENS" are t-shirts and hoodies for her male partner, while the 3rd item, the generic, un-gendered "T/Shirt," is for her, and, Michelle writes, "definitely cut for the female form too."

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JUSTICE AT LAST![/caption]

Maybe I’m delirious but I found this hilarious.

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