Author’s Note

This piece sits within my developing Why We Do Not Live in a Simulation series. The two previous articles can be read here and here. It's an inquiry into how certain metaphors, particularly computational ones, have come to stand in for reality itself. Simulation theory, in its popular and academic forms, often feels persuasive not because it's been proven, but because it aligns so closely with how we currently understand our own tools - and how the modern mind has been groomed to think. This essay focuses on where that alignment begins to distort questions of freedom, agency, and participation, and why the ability to disengage may tell us more about reality than any amount of recursive modelling.

∼Frank Jacob

In a recent interview on DOAC, boldly entitled “The REAL Reason Scientists Know We're In A Simulation," Neil deGrasse Tyson lays out what he considers the strongest argument for why we almost certainly live in a simulation.

Not the cartoon version. Not the Matrix. The refined one.

It goes like this:

Right now, humans don’t yet know how to build a perfectly simulated world. But Tyson believes there’s no reason to think that won’t happen someday. Maybe not now. Maybe not soon. But eventually we will succeed. The Sentient World Simulation was one such attempt. But let’s bracket that for a moment.

The Sentient World Simulation

Some commentators brazenly extend the Sentient World Simulation (SWS) concept into claims of a fully realized planetary control system. For a time, I myself spoke about SWS as if it were a functioning technology. On closer inspection, that was premature. The official descriptions of SWS remain framed in aspirational language: “envisioned,” “to be,” “can be used.” The project never reached deployment in the form originally proposed. What survived was not a planetary simulation, but a modelling mindset.

That mindset quietly migrated - into economics, epidemiology, social-media analytics, behavioural cloning, and large-scale decision support. Whether or not classified continuations exist under other names is ultimately beside the point. The historical record already shows that the ambition to simulate humanity at planetary scale has already been seriously entertained by defense and research institutions.

The real danger does not lie in a hidden, fully operational master simulation. It lies in mistaking increasingly sophisticated models for reality itself.

In order for such a simulation to work properly, something fundamental would still need to be solved: how to simulate genuinely experienced free will for the characters inside it. Without that, the world couldn’t develop autonomously. There would be no true driver - no internal incentive - for the artificial environment to evolve on its own.

And once it does, something interesting follows.

The beings inside that simulation - believing themselves to be free - will invent computers of their own. And that will eventually lead to them creating simulations as well. And inside those simulations, the very same thing will happen again. Worlds within worlds. Simulations inside simulations. All the way down. At that point, Tyson says, probability does the rest of the work.

So there is one original universe, and countless simulated ones that follow. Statistically speaking, the odds are overwhelming that we are not the first. We could be somewhere in the middle. Or near the bottom. His only remaining question is this: Are we the very first universe? The one that hasn’t cracked it yet? Or are we the last? The one that hasn’t figured it out yet? Either way, he says, it’s roughly a fifty-fifty proposition. 

And that, he says, helps him sleep at night.

It’s a rhetorically elegant argument. Probably the most accessible version of simulation theory currently circulating in mainstream culture. Clean in presentation. Comfortable in tone. But that cleanliness only comes from what it leaves out. Tyson’s version avoids defining free will, avoids defining consciousness, avoids confronting physical limits, and replaces ontology with probability. It sounds reasonable because it sidesteps the very questions that would make it collapse under scrutiny. And for the average mind reading it in the mainstream consciousness, with no particular science or physics knowledge, it’s very easy to follow. After all, Tyson’s argument is delivered by a trusted cultural translator. Over time, repetition turns a way of thinking into a default position. Not through proof. Through familiarity.

A Brief Detour: Other Simulation Models (And Why They Don’t Help)

Before going further, it’s worth pausing for a moment - because Tyson’s framing is often mistaken for the simulation argument. It isn’t. But that’s only because when someone with Tyson’s public status speaks, audiences assume vetting has already happened, nuance morphs into takeaway, framing becomes conclusion.

There are in fact “cleaner" versions. Stricter ones. Less comforting ones.

The most cited is from philosopher Nick Bostrom, who doesn’t rely on intuition or bedtime metaphors. His argument is colder and more explicit. He lays out a trilemma: either civilizations go extinct before running simulations, or they choose not to run them, or simulated minds vastly outnumber biological ones. If the third is true, then statistically, we’re likely already simulated. It’s rigorous. But it also quietly assumes that consciousness is substrate-independent - that minds are portable across hardware. That assumption does all of his heavy lifting.

There are also physics-based versions. These point to discreteness in spacetime, information limits, Planck-scale resolution, or the universe behaving like it’s computationally bounded. These models at least try to be testable. But they still sneak in a machine metaphor. They interpret limits as evidence of code, rather than as features of a physical world that evolved constraints the way all living systems do.

What these models share is a single, unexamined move: They treat reality as something that works like the things we build. A very human projection. But one that still collapses under its own assumptions. And the reason it collapses has nothing to do with technology. It has to do with the confusion around the idea of “freedom”.

Then there’s the David Icke version: we are living inside a hologram programmed and controlled by evil actors. The object of the game is to escape.

Actually, Icke’s and Neil deGrasse Tyson’s models may appear vastly different on the surface, but structurally they are two flavours of the same pastiche. One anaesthetizes responsibility, the other dramatizes it. But both begin by convincing us that the world itself is not what it claims to be. In both cases, the world we experience is declared unreal or secondary. Ultimate authority is relocated elsewhere - whether to advanced programmers or hidden controllers. Human agency becomes conditional, limited, or provisional. And meaning is displaced from lived participation to either resignation (“it doesn’t matter anyway”) or escape (“wake up and get out”). Different aesthetics. Same architecture.

The core assumption in Tyson’s argument is subtle. It’s not that free will doesn’t exist. It’s that free will can eventually be implemented. Tyson posits that, once a system becomes complex enough, free will will simply emerge inside it. Not real freedom, perhaps. But the experience of it. And that distinction matters more than most people realize. Because a computational, artificial system can absolutely generate the feeling of freedom. It can generate choices. Branches. Uncertainty.

Even rebellion.

But feeling free and being free are not the same thing.

A chess program chooses moves. A weather model branches futures. A game character improvises within rules. But none of those things possess the capacity to recognize the authority of the system they are within. And that’s the line that keeps getting blurred. That’s the one aspect that simulation theory never quite knows what to do with. True freedom doesn’t just show up as better gameplay. It shows up as something far more inconvenient. Something most people never give much thought to: disengagement. Loss of interest. Withdrawal from the spectacle. Refusal to optimize. Seeing through the game.

And ultimately, refusal to play.

People who undergo genuine shifts in perception - those who ‘awaken’ - don’t move on to become more productive units, or better actors in the story. They often become worse ones. That’s because they stop caring about winning. It’s why monks retreat ‘to the mountains’.

They stop investing in saviors.
They stop reacting on cue.
They stop needing the narrative to resolve.

This cannot be a feature. This is a liability. Why? Well, let’s break it down. Because here’s where the refined simulation argument - or at least Tyson - tries to recover. It says: “What if the system requires people to feel freedom in order to remain stable?” 

Wouldn’t it follow that awakening itself be part of the design? Wouldn't doubt, rebellion, even metaphysical questioning all be built-in pressure valves? That would seem to be a logical move. And it seems convincing...until you ask the question about what such a system would actually be optimizing for. Because if simulations are designed to sustain themselves - be it for data, entertainment, research, or complexity - then disengaged agents pose a big problem.

They generate less data.
They respond less predictably.
They consume fewer narratives.
They resist manipulation.
They reduce throughput.

In other words, they are inefficient. And inefficient agents don’t belong in well-designed systems. This leads to an uncomfortable fork in the road. Once you spell it out, there are only three options:

Either:

• The designers of the simulation are irrational
• Or awakening is an unintended byproduct
• Or there are no designers at all

But Simulation theory never lingers on this fork. It jumps over it. And that jump appears to be doing most of the work. Because once you accept that real discernment reduces participation, the idea of a deliberately engineered awakening stops making sense. A system may tolerate rebellion. It may even benefit from it. But what it cannot afford is indifference. 

This is where the older diagnostic models turn out to be sharper than the modern ones.

In the Sethian Gnostic view, the world is not fake. What’s distorted is interpretation. Authority doesn’t actually run reality. It can only hijack meaning. The deception is not that we live in a fabricated universe. It’s that we mistake imposed narratives for reality. That distinction matters. What those ancient seers understood is that freedom can’t be simulated. But it can easily be obscured. And obscuring something is very different from generating it artificially. A mirage doesn’t mean the desert isn’t real. The popularity of simulation metaphors says more about us humans than about the universe. And their sudden ubiquity is telling.

We’ve replaced gods with engineers. Angels with coders. And fate with algorithms.

And in doing so, we’ve found yet another way to externalize responsibility. If everything is coded, then nothing is demanded of us. If the game is rigged, then agency becomes cosmetic. That may be comforting for some.

But comfort is not evidence.

So here’s the question one inevitably arrives at in the Tyson model: If reality is a simulation designed to sustain itself, why does it keep producing beings capable of stepping out of the game altogether, without offering them a new one in return? There’s no leaderboard. No replacement myth. No upgraded narrative. Just clarity. That move has no payoff.

And systems without payoff don’t survive. 

Which is why, for all its cleverness, simulation theory keeps circling the same mistake. It assumes that reality works like the machines we build. And it forgets that machines are the derivative - not the source. Freedom doesn’t need to be simulated. It only needs to be permitted. 

And that permission is far riskier than any codebase would ever allow.

Just sayin’….