An excerpt from Chapter 9

Idiocracy et al.

Attention internet men:

If any of you people reading this also see me on YouTube or Twitter (X), you probably heard me mention once or twice that I’m slowly getting around to pissing out a generic manosphere book. Mostly as practice, actually. I have some ideas for real books - a couple of fiction books actually - but I want to learn the dirty ins and outs of how to turn scribbles from my keyboard into something on people’s Kindle apps before I try my hand at a real book.

I’m something like 132 pages into this thing, and every time I go back and reread what I’ve written, I think I’m a long-winded blowhard whose writing style is terrible to parse. But this is just my practice book anyway.

So anyway, I’m currently in the first part of Chapter 9, which talks about information overload/dilution, AI, and how it’s all making us dumber instead of smarter. And I stopped after the most recent page and reread it. And actually thought the first draft was vaguely decent enough to share, so I thought I’d drop you guys a short excerpt.

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With the internet continuously available on handheld devices that live in our pockets, we have constant access to more information that any human has ever had before. And to a wider variety of viewpoints than we can possibly imagine. And it’s not just a small number of lucky, elite humans that have this. Nearly all of us do.

So clearly, one would expect humanity in 2024 to be the smartest and most informed that it has ever been.

Instead, we may be at our dumbest.

The human brain was never meant to have this much information. The brain’s job is to keep us fed, hydrated, safe from predators and the elements, and breeding. Extra information that is not usable for this purpose isn’t something our brain is designed to hungrily consume. It’s something the brain is designed to filter and avoid. Too many distractions might lead to us getting eaten by a lion, forgetting to drink enough water, or walking off a cliff.

Indeed, our brain’s job is to protect us from information, not understand it. If some idea isn’t useful to make us money and get us fed, or get a girl to like us and have sex with us, or at least help us advance socially so those two things are easier, our brain tunes that idea out, or sometimes even fights against the idea.

So when we pull out the mini-internets we carry around in our pockets twenty-four hours a day, we spend most of the enormous amount of time we stare at these devices (the average screen time for a human in 2024 is 6 hours and 40 minutes per day) moving colorful shapes around to win some meaningless objective, reading ideas we already agree with, and sometimes arguing against ideas we don’t - either directly or just inside of our heads.

When confronted with an idea we don’t agree with, or even just an idea that is new, different, and unfamiliar to us, our first instinct is not to learn, but to fight. That idea is a threat. It is not useful to get us fed or laid in any immediately-apparent way, and even if it’s not a direct threat to those goals, it may be harmful as a distraction, or because it has the potential to change things in a way we can’t predict that might make eating and breeding harder. Not that any of this actually registers in our conscious mind. We just see it on the internet and argue, or if we don’t argue directly, we at least ponder reasons inside of our minds why we are right and that idea is wrong. The goal of our brain is to filter. To enable us to dismiss that idea and regard it as stupid.

It’s almost as though when confronted with too much information, we fight as hard as we can to reduce the information. We fight to remain uninformed and dumb. Because being informed and smart, beyond a certain baseline level, is not necessary to eat or breed, and being too informed and too smart might actually make those goals harder. After all, we don’t observe harems of women lining up to eagerly have sex with the nerdiest physics student in school. Instead, that nerdy physicist-in-training overthinks everything he says to women and ends up creeping out every girl in his class. He also apparently forgets to do obvious things like prioritizing his physical appearance to maximize his chances. Maybe his brain was right and all of that extra information distracted him right out of the gene pool.

Yes, as technology progresses and the amount of information available to every single human increases exponentially, instead of becoming a smarter and more informed species, we become dumber. We seek out the safety of a corner of the virtual world where we are told only familiar and comfortable ideas, that can be reduced to manageable sound-bytes we can understand and repeat.

Human language is actually a lot simpler than it seems. We’ve trained many types of machine learning models, colloquially dubbed “artificial intelligence” or “AI” for short, to process text in a natural language then determine an output that is responsive to the text. Some models create pictures based on the text included in a prompt, while others answer questions or simulate conversation using text.

There’s a lot of comptery stuff involved that I’m going to oversimplify, but the main idea is that if you give a computer a really big pile of text, it can learn what words mean. Not really. It’s a computer. But it can learn its own computery meanings for words well enough that it can respond to questions convincingly. The way this works is if you take this gigantic pile of text and look at which words occur next to which other words and which words are however big of a distance from various other words, you can come up with sets of numbers that let a model turn text into these things called vector embeddings. A vector is just a neat-sounding math word for sets of paired values, with the first value of the pair indicating what “dimension” is represented by that place in the vector, and the second value of the pair indicating the actual value for that dimension in whatever text was just turned into an embedding. When you turn a bunch of words into these math things, then you can figure out similar meanings of words based on the mathematical distance between two vectors. That’s how a computer knows that the word “king” is usually “male” and “Jennifer” is usually a “female” name. The vector for king is a shorter mathematical distance from the vector for male than it is from the vector for female, and so on.

That’s a lot of text to essentially say that computers have no clue what a word actually means, but that you don’t have to know what words mean to effectively mimic language. Arguably, some really dumb humans who barely know the language still manage to communicate, so why not some really smart computers?

This technology has become so advanced that I probably could have given every single thing Archwinger has ever written on the internet to a machine learning model and told it “Write a book about Archwinger’s views on the changes the internet has created in society”, and it would have spit out a better book than this one.

Some experts theorize that we are on the brink of the end of the golden age of humanity, and that instead of learning how to write or create art, future careers are going to involve learning how to train machine learning models and how to create prompts that will get the kind of art and writing we want from them. We may have hit a point where nobody will ever draw or write something new, ever again. Or at least, this may become more of a rarity.

Our culture has been predicting this dystopian event for a long time.

The 1999 film “The Matrix” is set in a dystopian world where this very thing happened, then AI started a war with humanity, took over the planet, and enslaved us for energy-production purposes using a virtual reality version of 1999 Earth. 

The 2008 Disney-Pixar film “Wall-E” is set in a dystopian world where human dimwittedness and overconsumption led to Earth being turned into a giant trash dump while all of the extremely fat, mentally challenged humans evacuated and live like zombies on an AI-piloted spaceship.

Wall-E borrowed some ideas from a far funnier 2006 science fiction comedy film called “Idiocracy”. Idiocracy was created by Mike Judge, who is probably most famous for creating the animated cartoon series “Beavis and Butt-Head”, which focused on the misadventures (and music commentary) of two absolutely moronic, perverted, disgusting, immoral teenagers with some kind of laughing disorder (that future movies about an iconic Batman villain would later use in an un-funny way).

Judge was also a co-creator of the television cartoon series “King of the Hill”, which focuses on the exploits of the Hill family, a hard-working couple and their son living in small-town-Texas, complete with an annoying mediocre wife with a high opinion of herself, a fat son who sucks at sports, and a conservative redneck-lite hardworking dad constantly trying to reconcile his ideal version of life with reality. Being Texan myself, this series was always a hoot for me growing up, because every single stereotype in the show is completely true, and then some.

Judge was also the creator of the cult-classic 1999 film “Office Space”, which told the story of “Ron Livingston”, an every-man character working in a cubicle for a generic 1990s software company, that dials up every single stereotype of mundane tech sector office life to a 20 out of 10, with hilarious results. Not to spoil too much in this 25 year old movie that you already should have seen a dozen times by now, but through a series of events, Ron suddenly finds himself aloof, uncaring, and above all of this hilariousness, and starts acting on his own wants, with weirdly effective and quite comical results.

After just my three-paragraph description of some of Mike Judge’s more noteworthy projects, you can probably tell what this man thinks about humanity and what was considered modern culture in the 1990s and early 2000s. They say art imitates life. Though honestly, if you’ve been paying attention to the rest of this book, it may be the other way around sometimes.

So anyway, Idiocracy takes place in a dystopian version of Earth, 500 years in the future. Don’t worry. I’ll tie this back in with the rest of the chapter in a second…

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