I almost never blog twice in one day. If there is more than one story that interests me, I usually them into a single blog. However, today I have to make an exception. This from the Johns Hopkins University’s Office of Diversity and Inclusion (ODI) LGBTQ Glossary. This was all the range yesterday on Twitter. According to the glossary, you don’t have to be a woman to be a lesbian. You can be a “non-man.” You can be a non-man and have a penis (i.e., a man). This means that men can be lesbians. Gay men are still men, though. The definition seems to quite self-serving, doesn’t it? I wonder who could have written this?
The backlash was swift and fierce. Now if you visit the page you get this: “While the glossary is a resource posted on the website of the Johns Hopkins University Office of Diversity and Inclusion (ODI); the definitions were not reviewed or approved by ODI leadership and the language in question has been removed pending review.” So that’s what happened. Somebody down the line put that in there. Who did that?
Quite a few people on Twitter believe they have found the culprit: Paula Neira, Program Director of LGBTQ+ Equity and Education, Johns Hopkins Medicine Office of Diversity, Inclusion and Health Equity (and Assistant Professor of Plastic and Reconstructive Surgery). In the below tweet, Neira and Christy Blanco, who is on the faculty of the Hunt School of Nursing at Texas Tech, appear to contrive a misgendering scenario which allows Neira to clarify that he is a woman and that failure to recognize him as such reflects bigoted assumptions people (like you and me and our children) have about gender identity and how that can compromise the patient-nurse relationship. Neira wishes not only to gaslight patients whose evolved gender-detection brain module tells them that this is a man, but he wants to shame them as bigots for the results of natural history.
Let’s assume that this is the person who wrote the glossary. I think that’s a fair assumption. I believe we can also make some further assumptions. Neira is a trans identifying man (this we don’t have to assume), presumably heterosexual, but since he identifies as a woman, i.e., a subcategory of “non-man,” believes he is also a lesbian and wants to make sure that the sexuality of lesbians is not defined as exclusively female, which gives him access to their romantic circles. That gay men are not “non-women” is not a problem for Neira since he is not gay. All this taken together increases my confidence in an emerging profile. It’s a pattern recognition thing. Not infallible, of course, but rarely wrong.
Whatever makes Neira tick, there’s a lesson here: if the majority and sexual minorities who are detrimentally affected by the Orwellian transformation of language by the DEI and gender ideology crowd push back hard enough, the coalition can stop things like the erasure of lesbians (i.e., women attracted to women, with women defined as adult human females) and the redefinition of women as “non-men,” a definition that includes men (defined as adult human males). Neira didn’t pull this jargon out of his ass, after all. This is a concerted effort by the dominant institutions of our society to change the way we see and think about gender. They’re trying to reprogram us. I don’t think it’s going to work in the long run.
What these institutions haven’t realized quite yet is that the people have awakened. Not just the majority, who has been remarkably tolerant all these years (mostly because gender ideology flew under the radar obscured by acronym), but also because feminists and lesbians, who have been the most aggressively attacked by trans activists (and you can understand why, since both are founded on the fact that woman are actually-existing things), have decided they aren’t going to take it anymore and are mounting a resistance. John Hopkins was rudely awakened. A lot of institutions that operate according to the ethics of diversity and inclusion are in for a rude awakening. (Ironic, no, that the resistance is so diverse and inclusive?)
Did John Hopkins not think the Bud Light and Target controversies wouldn’t find them? Did they really believe like the progressive minions on social media the propaganda portraying the growing resistance as rightwing conservative MAGA types looking for an opportunity to roll more coal? Baristas at stores across the Starbuck US chain have been told they can’t put up Pride decorations this year, surprising given that Starbucks health insurance plans include not only “gender reassignment” surgery, but also procedures previously considered cosmetic, such as breast augmentation or reduction, facial feminization, and hair transplants. When Starbucks makes the move, it’s time to have a meeting.
Sorry for being such a science nerd (sorry not sorry), but this article in The Swaddle, an independent media company based in Mumbai, India, “How Facial Recognition AI Reinforces Discrimination Against Trans People,” is fascinating—and frankly a bit absurd the way it’s spun. The Swaddle is just one of many publications that got caught up in a mass hysteria a few years ago when research emerged showing that AI consistently “misgenders” trans people while correctly identifying the gender of “cisgendered” people. It is nonetheless an opportunity to explore further the way elites are trying to change the way the human animals perceived and thinks about gender.
I don’t engineer AI systems, so this is a ignorant question (purposefully—for rhetorical effect), but I wonder whether AI’s ability to detect gender identity developed at all in a way analogous to way natural history developed this ability in humans. Probably not. I’m pretty sure not. Not at all. I’m guessing that the discriminatory apparatus is learned by having the bot view thousands if not millions of images of people (maybe it doesn’t require millions but far fewer instantiations of the two genders—and there are only two—to pick up the pattern). AI’s skill at gender detections is therefore not the result of millions of years of natural history in which the instinct to discriminate between genders was worked out in the dynamic process of natural selection but rather proof that machines can learn.
That humans have an evolved capacity to discriminate between gender categories is clear in the phenomenon many parent and teacher have observed where young children will ask in a situation of ambiguity (historically rare but increasingly not) if the person they’re looking at is boy or a girl; most of the time children assume correctly and, if people aren’t trying to deceive them, this frees them to worry about other things, such as whether Suzy is still a friend after the fight they had over a doll before nap-time. Put another way, children have an innate ability to discriminate between genders. Again, this is the result of natural selection, a process that began long before humans were even a species. This would have to have been the case or humans would never would have emerged—nor would their predecessor species.
So the convergence of gender discrimination in AI and human cognitive-perceptual systems comes about through different processes with similar results; whether evolved or learned, gender discrimination is a fact in pattern recognition systems. This is not a bug. It’s a feature. And it’s necessary, a matter I will get to in a moment.
This raises what ought to be a silly question: Are children transphobic? That’s as silly as asking whether AI are transphobic. Or whether I am, for that matter. It’s a misdirection play. What we need to ask is why activists and elites are trying to train AI systems to not recognize an obvious reality, i.e., to fail to see an objective pattern in nature, while at the same time trying to negate an evolved capacity in humans to see the same pattern, which they are presently trying to do through early socialization, gaslighting, and shaming.
This raises deeper questions about why reality is so undesirable to progressives and why there is so much loathing of the discriminatory apparatuses that inhere in the human animal. Why is the act or function of discriminating between categories such a terrible thing? What’s the agenda here? The capacity to discriminate between categories of things is essential for safely and successfully navigating the world around us. Humans are expert at seeing gender. So is AI, which like humans misgender trans people people all the time, which is another way of saying that AI correctly genders individuals despite their attempt to disguise their gender. In fact, humans misgender, i.e., correctly gender, people in their minds all the time while being compelled to act in bad faith and say things they don’t believe are true (things that are in fact untrue). Progressive morality is rooted in the ability to lie about reality. Again, what’s the agenda? Why are we being compelled to lie? Why is it a virtue to lie to oneself?
There is a system that does successfully prevent observers from recognizing gender, and this is found in the way statistics are reported by officials whose agencies are captured by gender ideology. A few years ago, the UK reported a sharp rise of rape among women—not rape of women but rape by women. What was going on? We know from statistics collected for more than a century and from across the planet that those who perpetrate rape are overwhelmingly men. In the above chart, we see that, for the United States, 93 percent of perpetrators of rape are men, while 90 percent of victims of rape are women. Because the reporting of statistics can deceive the observer by changing the definition of the category of thing, what the British public didn’t know was that those reporting the data were reporting men as women. The rise in rape wasn’t because women were raping more but because rapists are overwhelmingly men and when you define some men as women it generates a false perception about reality.
Here is the British government falsely signaling danger to those most vulnerable to this type of criminal perpetration. Why are governments producing false perceptions about the reality when reporting data necessary for public policy choices and the development of situational awareness by those who consume those data? (Imagine in the United States if black perpetrators of murder and robbery were redefined as white and you can see, if you have any understanding of what the actual data, of the distortions that can be introduced into public perception.) We have to ask why elites are trying to undermine the public’s ability to receive or access knowledge necessary for their safety.
I have to beat this drum. Why are being asked to lie to ourselves about the reality of the world? Why are elites lying to us about the reality of the world? Why are our institutions protecting those who wish to deceive us, as well as some who wish to deceive themselves (not all of them do, of course, but feigning convictions helps perpetrate the lie)? This isn’t a fight over bigotry. This is a fight for reality.
freedom and reason 