MundaneBlog

January 19, 2025

AI and Gender – Heteronormativity?

Filed under: AI,Gender,Technology — Tags: , — DrMundane @ 2:33 pm

I came across a newsletter by Joanna Stern, wherein she reports that Apple Intelligence often adds a “husband” when it is summarizing her wife’s messages.

When asked about this, she reports Apple responded that

  • Apple’s AI tools were built with responsible AI principles to avoid perpetuating stereotypes and systemic biases.
  • Apple’s addressing these issues through updates to its AI tools and is improving the accuracy of its models.
  • The company is encouraging people to report these issues while these AI tools are still in beta.

Now all that is well and good, but I am of the belief that owing to the nature of this “AI” and the way I expect it is implemented, as generative artificial intellegence, that it will never be able to ‘outrun’ the bias inherent in its training material. That is to say that because the “AI” must be trained on a corpus of material prior to being able to generate the summaries (in my assumption of how it works) and because that corpus does not contain context that statistically will ever reflect the marginalized, queer, etc., then the “AI” will always be unable to “react” as a human would.

I have written previously about the intersection of gender and AI, see Gender Classifier and on Facial Recognition , and to be honest this post is mostly a marker of one more datapoint to add to my argument. I make it mostly so I will be able to track back to here once needed.

If the “AI” can not be trained and guide-railed enough to figure out a contact named “Wife” is someone’s wife, then it strikes me that the potential here is… limited. And I have no interest in submitting my work to become grist for this particular mill, even if it were to increase the quality.

This being my first post in a month, I will leave it here. Thanks much,

-DrMundane

December 8, 2024

Further Signs of What’s to Come

Filed under: Gender — Tags: , , — DrMundane @ 3:51 am

I have written before that I expected the Republican agenda to be one of trans genocide if they win. 

I (am considerably enriched by some Laphroaig Quarter Cask) suddenly feel the urge to write on this once more, now that the decision has been rendered and we are in for the whole cruel agenda. 

Perhaps it is because the agenda is now stated explicitly. Perhaps the Supreme Court in United States v. Skrmetti will deliver to the states the ability to deny care and thereby commit these murders. 

But new from Punchbowl News comes this story. No less than a commissioner of the FTC (The fucking ftc!) aiming to be the chair intends to engage in fighting against gender care. I think it is clear that this anti-trans genocide agenda will extend throughout every agency in the Trump government. 

They make it clear that this agenda does not just include youths but adults as well. To quote the apparent pitch:

“Fight back against the trans agenda. Investigate the doctors, therapists, hospitals, and others who deceptively pushed gender confusion, puberty blockers, hormone replacement, and sex-change surgeries on children and adults while failing to disclose strong evidence that such interventions are not helpful and carry enormous risks.”

I would be remiss if I did not state that these are all objectionable lies. Beyond that, it must be repeated. They state in black and white that their agenda extends to adults.

P.S.

found another great article that you must read

Yours,

DrMundane

November 13, 2024

Links You Should Read – 2024-11-12

Filed under: Daily Links,Gender,Surveillance,Technology — Tags: , , , , , — DrMundane @ 12:59 am

Starting out with one from Wired, on facial recognition. Never forget that the terrain has changed for protest and online. I would certainly recommend anyone take steps to protect themselves moving forward. I am interested in the intersection of ‘dazzle makeup’, gender classification, and facial recognition in general. Genderfuck = AI protection? One can only hope.

Bonus link? The dazzle makeup one above. That machine-vision.no website seems neat, looking at how we conceptualize AI and machine vision etc. in media can tell us a lot about our worries and fears as a society. Back on course a little, dazzle makeup is one of those things I really wish were more true than it is. You can trick the AI, sure, but any human will pick out your face and track you that way. You become a person of interest real quick when you hide in that way. You need to blend, I think. Still, a person can dream.

Next up, one on pornography from techdirt. In a project 2025, Christian nationalist country, ‘pornography’ will not be limited to actual materials for sexual pleasure. It will be used as a label to restrict and remove LGBTQ+ material. It is literally the Moms for Liberty playbook, now coming to a federal government near you.

Wrapping up my links, read and subscribe to Aftermath!

November 5, 2024

“Gender Classifier” redux

Filed under: Gender,Technology — Tags: , , , , — DrMundane @ 12:49 am

As a follow up to my previous post, I also noticed while looking through the one AI companies page that they had a “gender classifier” for text too.

I had wanted to test their classifier, but was not about to upload my face or anyone else’s to some fucking AI company. But text? I can live with uploading a little of my own text (as a treat).

I started out with some fiction, something with dialog and some action interspersed. In truth it was erotica, but I skipped any descriptive action of actual intercourse. Honestly I was just interested what it would make of it. The result? “Female 70.71% confident”.

Ok, what if I swing the other direction, nonfiction? An excerpt of a blog post from this site or two. Say my last post (linked above). “Male 60.22% confident”. Trying another post I get “Male 67.71% confident”.

The straight ahead, non fiction, or opinion type of work seems to get the male classification. An artifact, I assume, of the gender normative source material and of the patriarchy in publishing, or of the biases of the humans classifying the dataset.

Trying one last example, this time an excerpt from my private writings (my diary/commonplace book takes the form of notes in the apple notes app a lot of times). It certainly leans more on my feelings and such, and not on straight ahead opinion and references. Results for one entry? “Female 66.21% confident”

Now I must admit the whole experiment here gave me some ill feelings, to say the least. Being classified did not sit right with me at all. It feels as though your self is being crushed back into one label or the other and that you have been reduced. But one more thought grabbed my interest.

What would it classify this writing as?

It is like gazing into a mirror, no, as if you can gaze through the eyes of another. How does anyone really take my work? What voice do they hear? I know, in my heart of hearts, that I should not care about such things. Even if I do, the AI will not be the eyes of another human. It is a statistical daydream.

And besides I wrote the word patriarchy (now twice), so I imagine that should add 20% Female points right there.

Nevertheless, I put everything from this sentence to the top into the classifier.

Results: “Female 52.23% confident”.

So a toss up. But I had to know, what if I replaced patriarchy with, say, normativity? Does it make a difference?

I literally clapped my hands and laughed. “Male 50.42% confident”. So it adds exactly 2.65% “female-ness” to say patriarchy twice. lol.

fuck these people and their products. never let them take root and give them no quarter, no serious consideration.

P.S.

I thought suddenly, “what’s 100% confident look like? What could one write to make it sure?”.

How about “I am a woman/I am a man”? Very high confidence there.

Results: “I am a man” : “Male 55.23% confident”.

”I am a woman”: “Female 82.15% confident”.

I had a couple of other thoughts:

“I am a nonbinary”: (I kept the grammar similar in the interests of fairness) “Female 83.79% confident”

“I am a trans man”: “Male 54.96% confident”

“I am a trans woman”: “Female 84.79% confident”

Of course it isn’t designed to interpret anyone actually stating their gender, but still. I hope it shows the hollow nature of the technology. How absolutely unfit for purpose it is. Let alone how its purpose is needless et cetera I’m looping here.

And I just had fun fucking around with it. Costs them money too, I imagine, to run the queries.

November 4, 2024

Gender Normativity and Facial Recognition

Filed under: Gender,Uncategorized — Tags: , , — DrMundane @ 11:48 am

Reading the always wonderful “Pivot to AI” by Amy Castor and David Gerard, and they link to a great 2019 piece by Os Keyes, “The Body Instrumental” which was new to me and enjoyable. Well, enjoyable in that particular way that any sufficiently prescient and worrying thing can be enjoyable. I have been thinking briefly as of late on heteronormativity, so both articles were a great coincidence.

I can’t restate any point not already sufficiently covered by the two articles above, but it really does strike me that any such “gender determining” (perhaps really “sex determining” in the end is their goal, reflecting the binary and exclusive nature of sex and gender for them, not that either is so binary as they think) AI will be inescapably heteronormative (perhaps “gender normative”, as I am speaking mostly in the gender, expression, and such things realm, not in the relational sense, although I take the term to apply to both. I can not claim to be an experienced scholar of gender, so forgive me if my terminology is incorrect. I was just reading Sex in Public, so, like, 1998?. Still very much a relevant work in my mind, but my cognition is biased towards that which I can remember in the moment).

The training data is classified first by humans, who will have to fit each photo into a binary category, man or woman. Most of the data will likely be of people who “pass” or perform gender in the correct way, simply owing to the dominance of such images in the training data. Movies, photos, public domain images, et cetera. Simply by volume alone the normative wins out, and therefore any such AI will be biased in its favor. It will be biased to fit people into these categories.

Turning to prognostication, who will be allowed to opt out? To gate access to a room or facility behind such an AI means that the non-normative, the queer, will be penalized. Even if one is notionally allowed to opt out, the process of doing so may very well lead to further stigmatization simply by virtue of being the different one.

As Keyes states: “We should focus on delegitimizing the technology altogether, ensuring it never gets integrated into society, and that facial recognition as a whole (with its many, many inherent problems) goes the same way.”

I could not have said it better or any earlier. You simply must read the whole article, as the portion on how the AI will reshape gender in its image is brilliant and gets to the very heart of not just the AI problem, but of problems of gender in society more broadly.

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