Ending the ‘trans’ insanity… with AI?

6 May 2024

Many people hold grave concerns about the impact that artificial intelligence (AI) is already having on virtually every facet of our lives… and even our deaths. Just to scrape the very tip of this giant iceberg:

• AI has already turned a huge chunk of the population into social media addicts, who spend giant slabs of each day endlessly scrolling though their (aptly-named) ‘feeds’.
• AI could render 300 million workers obsolete by 2030, according to the “great vampire squid wrapped around the face of humanity” itself, Goldman Sachs.*
• AI could put everyone from customer service representatives and warehouse workers to accountants and traders out of a job, producing – in the bone-chilling words of the creepy WEF muse, Yuval Noah Harari – a massive “useless class” that will pose a major management problem for the technocratic overlords.
• AI is used extensively to mark individuals – and in many cases, their entire families – for assassination, with the Israeli army currently deploying AI programs called Lavender and (grotesquely) Where’s Daddy? to target Palestinians for guided missile strikes.
• And of course, AI could, if it perceives itself to have become smarter than us, decide to exterminate the entire human species.

But, on the bright side, researchers at Stanford University have come up with a pretty cool use for AI: They developed an artificial intelligence model that proves both the gender theorists and the ‘equality neuroscientists‘ dead wrong, by accurately distinguishing male brains from female brains, based solely on scans that measure the functional organisation of said brains. Or, in plain English, they trained an AI model to pick a male brain from a female brain by looking at how each brain behaves while it’s processing information, and it was able to do with over 90 per cent accuracy.

As the authors of the new study point out, previous research on putative sex-based brain differences has focused on structure -analysing the relative size of, and connectivity between, the various regions of the brain. There are definitely structural differences between male and female brains. But do structural differences translate into functional differences – that is, do male and female brains actually think differently? The attempt to answer this question through the use of functional magnetic resonance imaging (fMRI) has been stymied by the replication crisis that plagues every scientific field – the findings of many published studies cannot be reproduced by other scientists.

The lack of replicability and generalisability of previously-published findings on functional brain connectivity patterns has led some researchers to argue that the idea “that there is such a thing as a male brain and a female brain” is bunkum, and that “human brains are comprised of mosaics of female-typical and male-typical features” rather than there being a male/female binary.

Naturally, the pronoun people have seized on this idea to argue that there are in fact 74 “gender identities” ranging from agender to omnigender, via cavusgender, esspigender and gender witched. (I’m not making this up. Check the reference. It’s on a site called MedicineNet which is part of the WebMD Network, and bills itself as “an online, healthcare media publishing company [that provides] easy-to-read, in-depth, authoritative medical information for consumers”. God help us all.)

But our trusty team of Stanford researchers came up with a way to settle the question. They created a “spatiotemporal deep neural network (stDNN) model” – essentially an AI program which can spot tiny differences in brain imaging data that even a well-trained human eye is unlikely to notice. They then showed it multiple dynamic MRI brain scans, in each case telling the AI whether it was looking at a female or a male brain. As the AI saw more and more scans, it began to notice subtle patterns of “functional brain dynamics” – the interplay among different brain regions – that allowed it to differentiate between male and female brains with greater and greater accuracy.

Finally, after its training was complete, the AI was let loose on the brain scans of around 1500 young adults (aged 20-39) from the US, UK and Germany. Its hit rate in accurately classifying the brains as belonging to either a man or a woman was greater than 90 per cent. And unlike previous models, which often mistakenly judged a brain which had been scanned multiple times, as being male on some occasions and female on others, the stDNN model was highly accurate at correctly classifying the same brain as either male or female across multiple scanning sessions, confirming “that brain features underlying sex differences are stable at the individual participant level”. (Sorry, all you cendgenders, collgenders, demigenders and genderfuzzes, but your “personal truth” is utterly divorced from reality.)

You don’t even need to understand what the feck a “T-distributed stochastic neighbor embedding (tSNE) plot” is to see how similar each male brain was to other male brains, how similar each female brain was to other female brains, and how distinctly different the male brains were from the female brains:

(Isn’t it cute how they used pink for females and blue for males? I’d like to think that this is them giving an academic middle finger to Stanford’s metastasising DEI bureaucracy.)

Specific networks within the brain were principally responsible for the ability of the AI to distinguish between male and female brains, namely the default mode network, the striatum, and the limbic network. Here’s where things get really interesting. I’m going to quote from the article at length, because the authors explain the functions of each of these networks, and their behavioural implications, with (for scientists anyway), great clarity:

“The DMN [default mode network] plays a critical role in integrating self-referential information processing and monitoring of the internal mental landscape (72, 73), including introspection, mind-wandering, and autobiographical memory retrieval (71, 72, 74). These cognitive processes may differ between females and males, potentially influencing self-regulation, beliefs, and social interactions. Sex-specific differences in the DMN may also influence how females and males recall past experiences, form self-concepts, or engage in perspective-taking. Our findings underscore the pivotal role of the DMN in elucidating sex differences in brain functionality and advance our understanding of how these differences influence various cognitive and social behaviors…

The striatum is important for learning cue associations, habit formation, reinforcement learning, and reward sensitivity (75)…

We also observed significant differences in the limbic network which includes, most prominently, the orbitofrontal cortex (65). The orbitofrontal cortex is involved in learning and reversal of stimulus-reinforcement associations, and correction of behavioral responses when they are no longer appropriate because previous reinforcement contingencies have changed (76). The human orbitofrontal cortex is also implicated in representing the reward value, expected reward value, and subjective pleasantness of reinforcers (77). This link to subjective pleasantness could provide a basis for investigating the limbic network’s role in sex differences in hedonic experiences.

Collectively, our findings suggest that females and males differ in how they engage dynamic functional circuits involved in both self-referential and internal mental processes, reward sensitivity, reinforcement learning, and subjective experiences of pleasure.”

Deep learning models reveal replicable, generalizable, and behaviorally relevant sex differences in human functional brain organization

Reflect for a moment how mind-bending this finding is, if indeed it proves to be replicable by other researchers, in other cohorts of participants. If everything from how we daydream, to how we remember past events in our lives, to how we motivate ourselves and experience pleasure, is rooted in sex-specific differences in the functional activity of our brains, then it is beyond ludicrous for any individual to claim that they “identify” as a member of the opposite sex. Never mind pondering what is it like to be a bat; I, as a woman, can’t even figure out what it is like to be a man!

Now, regular folk might be wondering if these findings explain the phenomenon of refrigerator blindness (which has even been written up, albeit tongue in cheek, in the medical literature), or answers the age-old questions, ‘Why won’t men ask for directions or read the damn instruction manual?’ But our Stanford researchers have their gaze fixed on far loftier targets than these prosaic matters:

“The DMN, striatum, and limbic network are also loci of dysfunction in psychiatric disorders with female or male bias in prevalence rates, including autism, attention deficit disorders, depression, addiction, schizophrenia, and Parkinson’s disease all of which have sex-specific sequelae and outcomes (78–86). Our findings may therefore offer a template for investigations of sex differences in vulnerability to individual psychiatric and neurological disorders.”

Deep learning models reveal replicable, generalizable, and behaviorally relevant sex differences in human functional brain organization

Well, that all sounds very worthy. Obviously, gaining insight into disabling conditions like schizophrenia and Parkinson’s is a good thing, since at least some of those insights will produce more effective treatments. But I do hope someone will eventually get around to addressing fridge blindness.

DEI, GFY

One thing you notice when you read a lot of scientific papers, is that researchers are generally very circumspect when stating the conclusions that can be drawn from their findings. Every statement is hedged about by qualifiers and modal verbs that caution the reader not to over-extrapolate from this one study, but diffidently suggest that it may, might, could, contribute somewhat to greater understanding of blah blah blah problem.

So I was struck by the confidence and forcefulness with which the authors dismissed the rival ‘mosaic’ conception of functional brain organisation, and asserted the ramifications of their conclusions:

“It is noteworthy that the use of weaker algorithms has led to the erroneous conclusion that poor classification reflects a continuum of functional brain organization in females and males (69). Our results provide the most compelling and generalizable evidence to date, refuting this continuum hypothesis and firmly demonstrating sex differences in the functional organization of the human brain…

Our study provides compelling evidence for replicable and generalizable sex differences in the functional organization of the human brain. We identified replicable and generalizable brain features within the DMN, striatum, and limbic network that differentiate between sexes. Critically, these brain features predict unique patterns of cognitive profiles in females and males, demonstrating their behavioral significance. The finding of robust functional brain features underlying sex differences has the potential to inform quantitatively precise models for investigating sex differences in psychiatric and neurological disorders.”

Deep learning models reveal replicable, generalizable, and behaviorally relevant sex differences in human functional brain organization

BAM! KAPOW! Take that, you genderfluid diversity officials! (According to Christopher Rufo’s exposé on the DEI infestation of Stanford, “The highest concentration is in Stanford’s medical school, which has at least 46 diversity officials.”)

Now, this is just one study, from just one research team, in one university. And the press release for it did slip in a weasel word disclaimer “that this work does not weigh in on whether sex-related differences arise early in life or may be driven by hormonal differences or the different societal circumstances that men and women may be more likely to encounter”, which was completely discordant with the paper itself.

But the fact that this study obtained NIH grant funding, got past peer review, and was published in a journal as prestigious as the Proceedings of the National Academy of Sciences (PNAS – yes, it’s pronounced pretty much the way you imagine it would be; can’t scientists have a giggle too?), which is the second most cited scientific journal in the world, is kind of a big deal.

When I consider this study in conjunction with other recent events including:

• The release of the explosive Cass Review, which excoriated the providers of “gender identity services” in the UK for their blithely evidence-free approach to ‘treating’ troubled children;
• The leaking of the WPATH files, which “prove that gender medicine is comprised of unregulated and pseudoscientific experiments on children, adolescents, and vulnerable adults and will go down as one of the worst medical scandals in history”; and
• The publication of papers like this one, that convincingly demonstrate that the vast majority of children and adolescents who experience some confusion about whether they’re Arthur or Martha eventually grow out of it, if they’re not mind-f*#ked by adult weirdos or predatory social media algorithms…

… I feel cautiously optimistic that the paroxysm of trans insanity that has gripped the West for the last few years may finally be nearing its postictal stage.

My personal confidence is further buoyed by the results of a study of public confidence in 45 different types of scientists, from agronomists to zoologists, which found that the least trusted (from rock-bottom up) were political scientists, economists, sociologists, food scientists and meteorologists, while the most trusted (from top down) were marine biologists, neuroscientists, zoologists, astrophysicists, and oceanographers. Awareness seems to be growing that the social sciences departments of universities are largely teaching nonsense. (And as for weather forecasting, and the Frankenfoods that come out of ‘food science’ labs, the public just ain’t buyin’ what they’re sellin’.) I’m sure our straight-talking team of Stanford neuroscience researchers would be chuffed to know how much public trust their profession enjoys!

If scientists can finally, openly state what every heterosexual couple already knows – men’s brains work differently from women’s brains – without fear of having their careers ended by the woke mob, then maybe, just maybe, we are not doomed to perpetuate the new Dark Age, after all. Now, will someone just cure that bloody fridge blindness?

Are you confused by the scientific claims and counter-claims that you encounter through popular and social media? Would you like to learn how to read scientific research, assess its biases, and understand how it fits within the body of scientific literature? My EmpowerEd membership program is custom-made for you. Activate your free 1-month trial today!

* For those who noticed that the archive.today link for this article ends with ‘soGoy’, I just wanted to make sure you know that these link extensions are auto-generated by archive.today. Sometimes a cigar is just a cigar.