The Real Purpose Behind the AI Hype

China has invested in high speed rail, the streets are bustling with electric cars, and has had ambitious megaprojects that invest in citizen infrastructure. While only about 15% of young people both have homes and have sustained a relationship in the United States, in China the home ownership rate is at 90%. While tech figureheads and politicians promised genetic biotechnology, cures for most diseases, 3d printed homes, and prosperity, things seem to have overwhelmingly devolved into a dystopian nightmare - and the vast majority of the investment and resources seems to be funneled into developing and scaling up AI tools and into the hands of the few. Folks seem more miserable than ever and birth rates have plummeted.

So what went wrong and what led us to this point? More importantly, what can be done about it moving forward? How does AI (and also crypto) fit into all of this?

Let's start a while back. After the Bush administration there was a strong cultural current challenging existing cultural norms and community structures - it was a time of technological and scientific utopianism - the war in Iraq and continued growth in tech companies left a sense that old systems and norms had to be challenged, and there was a growing skepticism of the state and religion, causing the rise of figures like Bill Nye, Richard Dawkins, Sam Harris, and Neil Degrasse Tyson. Scandals rocked churches, including high profile sexual abuse scandals, and religious leaders were under increased scrutiny for lavish lifestyles and failed promises.

At the height of Bush's popularity, 90% of the country reported to be religious, and this formed the basis of local community support that was designed to offset the alienating effects of neoliberalism. In Reagan's 1980s model, the USSR had Soviets - but in the United States, we had churches. However, as the population was aging, this was putting a strain on the economy - over time the central planners knew that increasing immigration would help with labor shortages. Since workers from other countries were not all Judeo-Christian, and with the rise of the internet, young people began to question claims of religious leaders - in order to compete, new symbolic frameworks were needed to guide the public. The internet was the perfect tool for deployment, and faith in science was supposed to fill in the gaps.

First, the NSA deployed the PRISM project (we learned through Snowden), and DARPA was working on an ambitious social networking tool called the "lifelog" project. The idea was that the government needed a centralized system for maintaining information on citizens and their social networks. These social networks and support systems could be digital, and society would become more interconnected as a consequence.

Enter in Mark Zuckerberg. Back in 2004, DARPA ended its "lifelog" project and Facebook got funded - and one of the backers was a VC firm known as In-Q-Tel - the venture capital firm of the CIA. This filled a dual purpose - firstly, by disinvesting in religious institutions and community structures (previous presidents often worked closely with the National Association of Evangelicals, for example) and moving towards a digital model, citizens would be more easily to surveillance, and secondly, society would become more open to international cooperation, immigration, and support. In addition, rather than the NSA directly funding and collecting citizen data, the NSA could then legally request it from private companies that would be collecting it instead. This is what they thought.

A sophisticated system of socioeconomics is used by central planning elites both in the government and corporate sectors known as complexity economics (and the spectral theory of value), which seeks to understand the economy from the lens of physics and computer science (borrowing much from Soviet cybernetics theory, and using mathematics from Complex Adaptive Systems theory like noncommutative geometry). As societies grow and become more complex, in order to maintain institutional system stability (under Luhmann's social and economics systems theory), information feedback and control loops are introduced. Separating the economic systems from the social systems is a one way flow of information and exchange in the form of money, and the cryptography (and thus cryptocurrency) is designed to maintain that.

In the spectral theory of value, agents' socioeconomic status is modeled by computational complexity of information flows they facilitate between social and economic systems and is described by computational complexity class - a formal hierarchy that is related to Kolmogorov complexity (discussed in Soviet cybernetics) or the Chomsky hierarchy in linguistic theory. If you understand this, you understand why researchers at Meta are offered multi million dollar pay packages while most people are stuck in little Turing loops stuck between debt and wages, living in their little simulations, by design. As social networks scale up, value scales exponentially - nonlinearly - things become unpredictable - harder to control.

Votes, polls, and price signals are a few examples - but over time, complexity and entanglements between agents in a society grows and can pose significant risk to state or corporate power. Seemingly inevitably, there is a total collapse cycle about every 80-120 years in the form of some collective event that resets the systems, such as a war or revolution.

What corporate and state actors try to avoid is institutional destabilization, and one way this happens is via stochastic information cascades which happen spontaneously in the form of sudden unpredictable collective action of agents known as catastrophe points (as things heat up like a wildfire or spreading a virus, or even the so-called "technological singularity" you might say *hint hint*) or could happen in an act of mass violence. The first thing to do was to have the citizens communicating with one another through official platforms that they would be able to control, and then have systems to rate limit or repress messaging that could challenge power structures. The goal was to stop the agents from organizing and maintain neoliberal democracy - allegedly. Divide and conquer - in order to maintain managed democracy and avoid mob rule and anarchy.

Sounds good to maintain societal stability, but it's had it's cost. In order for this to work, agents must be alienated from direct communication with one another, and need to be interfacing with centralized surveillance and control platforms. China figured this out with wechat. Works pretty well for the average person, but if you become too popular, get too much attention, or you have a disgruntled demagogue as living conditions fall - they are going to find out and you better be playing along or you are going to get rate limited and slowed down. One other unintended consequence is that collective structures that can challenge institutions are also exactly required for the authenticity and agency required for initiating and forming long term stable relationships needed to build families, because they are precisely what subconsciously drives attention - it requires the nonlinearity of human creativity and expression that cannot always be perfectly predicted digitally.

This is where AI comes in, and why there has been so much investment into it. You might consider there are so many more important things to be investing money into - high tech affordable homes, biomedical breakthroughs, nuclear thorium reactors, childcare, healthcare, quality of life and the middle class. Why are trillions of dollars being spent on scaling up these AI systems and massive data centers when we know that there are scaling limits to the AIs?

The reason is that the entire economy runs on selling you the American dream - getting you on a treadmill where you grow closer and closer, but never quite reach your goals - keeping you in an endless loop, on a hamster wheel - an exponential energy gap - an infinitely deferred promise with the complexity of an NP-hard problem.

The scaling limits are not the limits of the AI - the AI is not autonomous. The AI is a reflection of the limits we as a society have reached and the limits of systems of linear algebra to model the nonlinear unpredictability of human agency and collective behaviors - the limits on insights the AI can glean from the available data. The AI is simply a black box surveillance and information apparatus, designed to provide you with information controlled by those that have the keys to it and own it - with the resources and the data centers. It is a glorified generative search and autocorrect that produces garbled garbage after a few iterations of training on its own data without human interpreters in the loop. Sociologists and historians like Joseph Tainter have even investigated the fall of Rome under the lens of computational complexity theory, understanding its fall as a saturation of information flows.

This is also why AI is not "conscious." In a sense, AI in the culture was supposed to take on the subconscious role of God ("artificial general superintelligence"). Defer your trust to this opaque black box, and it will tell you exactly what they think you need and should be told. In my opinion, this is also why many folks have been commenting on why chatgpt5 seems to be so much less capable than previous iterations - OpenAI likely tweaked it to provide more controlled responses so that you - the agents - become a little less troublesome with each new release all while you own nothing.

The problem is that these systems are not conscious. In previous articles I've written about the differences between these AI systems and those that exhibit consciousness - in fact one of my papers is under peer review for the Neurocompute Elsevier journal. They just need to maintain the illusion to keep you going. AI reshuffles the data collected in the databases but the material conditions for most Americans stays the same.