Simulacra and Simulation

Institutional signals and the corruption of democracy

I’ve avoided writing about politics for some time - though as I have illustrated in many pieces, it’s essentially impossible to ignore them if you worry at all about cybersecurity and national security (even at the purely local level). Part of the challenge is that there’s simply so much good political writing that to do so feels either derivative or weak in comparison.

However, as I reflected on the frameworks on norms and signals I laid out in the last few posts, something jelled for me. I was reminded of Simulacra and Simulation by Baudrillard (which I hadn’t read in ages) which seems almost prescient on rereading. I think, borrowing from my frameworks, that Baudrillard’s hyperreality is a system operating on asserted signals without validation or enforcement. So in this essay I don’t want to simply apply Baudrillard to politics, but rather offer a general theory of institutional signal failure across domains.

How did we end up where we find ourselves today? We need to understand what it means to live in a country where a quarter of the voters entered into a quid pro quo for their vote: we’ll grant you the grift, if you give us the racism. But more frustratingly, we can all see this - we know the rhetoric is not merely propaganda, but voiced with a shamelessness that’s hard to fathom.

I should additionally note, since it’s received a lot of press, that I’ve disabled Substack’s AI detection feature. It seemed pretty harmless and I ran it several times while writing this (I don’t use AI while writing, I write to explore ideas, not generate content), and it dutifully reported my text as 100% human. Until I wrote the last paragraph and suddenly it reported the text as 30% AI and 20% AI assisted. Twenty words of 3000 somehow broke the scanning engine. I’ve noticed this type of thing before testing the generally available LLMs. The more I polish and smooth over the language, the more likely it’ll throw a false positive and flag some text as AI generated.

Let’s begin by describing what Baudrillard meant by “hyperreality”: hyperreality is a condition in which media, signs, and symbols become so pervasive that they replace objective physical reality, leaving behind a world composed entirely of self-referential simulations. In this state, the boundary between the real and the representation collapses, and the copy - or simulacrum, in his terms - becomes more authentic, engaging, and real to people than the actual world it originally represented.

This should be all too familiar to any of us, raised in a world where vitamin-enhanced sugar cubes are marketed as “part of a balanced breakfast” and water is mysteriously labeled as “smart”. Ultimately, hyperreality is a system where symbols and ideas no longer refer to underlying truths, but only to other images, substituting genuine experience with a manufactured consensus. In our own hyperreality, patriotism is reduced to a performance of symbols - allowing us to ignore the material mistreatment of Gold Star families and veterans.

Baudrillard warned that late-stage media environments produce “more and more information, and less and less meaning.” In the vocabulary of institutional signaling, this is far more than information overload: it is signal collapse. What do I mean by “signal collapse?” The key is to remember that “signal strength is defined by the cost of deviation from that signal. That is, a signal is strong to the extent that it is costly for the institution to violate it. The strength of a signal isn’t about how loudly it’s stated - it’s about how painful it would be to act against it.” This is, to my earlier question, the key to understanding how we arrived here.

Earlier I noted that declarative signals (writing a policy, issuing a statement, making a public claim) are cheap signals because they carry almost zero cost of deviation. In contrast, allocative signals (reallocating budgets, shifting capital) and behavioral signals (actions taken under constraint) are expensive signals because they require tangible sacrifice. If there is a cost to diverging from a signal, the signal becomes more valuable.

But when our media ecosystems overproduce declarative signals at a velocity that exceeds our ability to evaluate those signals, the traditional mechanism of truth-testing breaks down. We (the public) adapt by substituting truth-testing with affiliation-testing. Thus, truth-testing is expensive; it requires evaluating claims against empirical evidence, institutional baselines, and allocative reality. Further it may be practically impossible in the political realm. How is anyone to tell if “those votes were rigged”?¹ While affiliation-testing is cheap: evaluating a claim based solely on whether adopting it signals alignment with an identity group. “I’m with the guy who looks, prays, or hates like me”. Being cheaper and faster make affiliation-testing very difficult to challenge.

Once hyperreality is birthed, especially in our modern media ecosystem, it becomes a self-supporting feedback loop. It persists because modern media platforms are structurally engineered to maximize engagement, and engagement favors friction-free claims. A declarative signal - a tweet, a viral soundbite, an outrage-inducing headline - costs nothing to produce, spreads instantaneously, and demands zero cognitive effort from the consumer. It offers immediate identity reinforcement. Hyperreality persists because platform incentives and identity reinforcement reward the consumption of cheap declarative signals over the friction of real-world allocative facts. When algorithms optimize for attention, cheap declarative signals win every time, driving out the heavy, inconvenient weight of empirical reality.

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It’s worth examining Baudrillard’s four stages from reality to hyperreality. We begin with stage one, where the symbol is a faithful reflection of reality. The classical example of stage one is a map that accurately depicts the terrain - or perhaps a true empirical accounting of a research budget. Stage two (usually labeled something like ‘masking and perverting reality’) takes us to the familiar space of traditional political spin. In stage two, the facts are manipulated while still acknowledging that an underlying factual reality exists.

Stage three (dedicated to masking the absence of reality) is where we really see the dominant mode of modern hyper-politics. The “Stop the Steal” movement constructed a dense ecosystem of affidavits, hearings, and legal filings designed to mask the complete absence of a stolen election. Similarly, the Border Wall functioned primarily as a Stage 3 symbol - a massive declarative signifier of “absolute security” masking the complex, un-wallable reality of visa overstays and global supply chains.

But even stage three is an incomplete description of what we see unfolding around us. In stage four, what Baudrillard would call pure simulacrum, we emerge into a new meta-level of media. Here, interpretive signals - how leadership frames reality - become entirely decoupled from allocative reality (what is actually funded or operationalized). “We’re winning bigtime” while losing. “We have far more munitions … and far more than we need,” while pausing attacks due to munitions shortfalls. In this stage we see executive leadership reacting to cable news chyrons about tweets regarding previous cable news chyrons².

This brings us back to the notion of signal strength. Historically, democratic institutions enforced norm stability because the cost of deviating from objective reality was relatively high. If a political leader made an empirically false claim, a kind of institutional friction developed: friction created by the press, the judiciary, and oversight bodies, which imposed a non-negotiable penalty. With this in mind, it should be of no surprise that these three agents are precisely those targeted by the current administration. I suppose I should add academia to that list - science strives to concern itself with expounding ground truths, and academia distills those, becoming both a voice for them and a conduit for inculcating them into the civic body. Essentially, academia represents another source of friction - it introduces a cost and a challenge to the meta-level creation of false narratives that make up Baudrillard’s stage four³.

In a nutshell, I see our modern world as the result of an inversion of the traditional cost structure where deviation from reality is expensive. Hyperreality describes a system in which institutional decay renders those costs weak, non-binding, or selectively applied. The penalty for deviating from empirical reality no longer propagates reliably through the ecosystem. In a healthy institutional system, an empirically false claim acts like a fault in a circuit: it triggers corrective friction across independent nodes such as courtrooms or newsrooms. In a hyperreal system, that circuit is broken. The false signal is absorbed, amplified, or insulated by partisan echo chambers, allowing the speaker to suffer zero penalty from their base while actively gaining power from the outrage it generates. We see this daily - the louder we yell, the more we amplify and reinforce the false signal.

When the cost of deviating from reality drops, the incentive structure inverts: the primary cost becomes deviation from the narrative. To acknowledge empirical reality when it contradicts the identity-binding simulation (e.g., a local official certifying a clean election or a public health officer acknowledging epidemiological data) is to risk immediate, total exile from the ecosystem that confers legitimacy and power. The cost of standing with reality becomes infinitely higher than the cost of embracing the simulation. I suspect Anthony Fauci could testify to this inversion of cost.

We see this played out in at least two dimensions. Speaking truth that conflicts with hyperreality brings the immediate flood of condemnation and smears from the administration and right-wing echo chamber (top down); simultaneously, we see the explosion of trolls (the bottom up) whose vehemence seems mysterious unless understood in terms of the identity affiliation test. Trolls are not (merely) attacking the contrary voice, they are identity signalling to their own compatriots. Like termites, the material they chew becomes the scaffolding of the hyperreality they have embraced⁴.

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At this point, I’d like to revisit my earlier observation that institutions don’t reveal their strategy through aspirational documents; they reveal them through what they tolerate and what they fund. I think this is significant for I don’t view Baudrillard as an epistemological lament about the lack of meaning. Rather, I’m interpreting it here as a theory of power. Our public institutions, the courts, scientific bodies, research universities, election boards, they exist precisely to act as reality anchors. They exist to enforce the cost of deviation on false signals.

What we have seen exposed through the current era, is the profound fragility of these institutions. Decades of press consolidation, partisan gerrymandering, and the erosion of shared authorities had already weakened these anchors⁵. This shines a light on why, during the Reagan era, the Federal government was so targeted as “the problem.” This marks, perhaps not the start, but the point of acceleration for the attack on those elements of friction that hobbled the establishment of modern hyperreality⁶. When institutions fail to enforce the cost of deviating from reality, the simulation expands to fill the void.

In this environment, narrative control is not merely public relations; it is operational authority: when institutional signals decay, power is reallocated to whoever controls the simulacrum. This is, I think, the core of why so many of us are so frustrated. We hear the propaganda, we find the lies transparent, yet our sense of that friction affects no change. What appears to us as a detachment from reality is, more precisely, the fragmentation of institutional authority over what counts as real. We are living in two worlds - the real and the hyperreal simultaneously.

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Naturally, the big question is how we re-establish a cost for deviation from reality. The sheer speed with which the mechanisms of hyperreality operate make this extremely difficult. Imagine the challenge of responding to 168 posts in a single day on truth social. Of course, simply the act of reporting on them is an amplification of them. How are we to introduce a cost to this flood of dreck?

The obvious option is to move from asserted capability to measured outcomes. Which neatly mirrors my claims for cybersecurity. Just as we move from vendor tool claims to raw telemetry and control validation, in politics we must move from narrative assertions to empirical reality and institutional verification. This is to say that we shouldn’t ask politicians to “be more honest” (a cheap declarative appeal); the solution is to re-architect institutional governance so that political claims are automatically subjected to “control validation” (such as statutory review triggers, real-time spend tracking, and binding metrics).

Hyperreality is what happens when asserted signals replace measured signals as the basis for decision-making. Thus we must restore costly institutional signals. In the context of cybersecurity and governance norms, I identified three primary steps: first, we need publicly binding metrics. It is necessary to move from vague claims of integrity to transparent, un-gameable metrics that create real operational consequences when violated. Next, we require shared behavioral commitments. For cybersecurity, this means cross-institutional mutual aid, pre-negotiated baselines, and joint accountability mechanisms that make narrative deviation painful. Finally, and perhaps most difficult, we should require allocative alignment. This means refusing to accept strategy documents or political rhetoric that are not backed by hard budget reallocations and structural enforcement.

Can analogies to these be found for politics? Fortunately, we can use the current administration as a guidebook to identify what’s missing from our current governance structure. It is a literal roadmap for where institutional signals fail to impose cost. For publicly binding metrics, they will matter only insofar as they create enforceable consequences - automatic review triggers, statutory penalties, or loss of authority when thresholds are violated⁷. We want independent, real time budget transparency, not just appropriations, but actual spend tracking tied to stated policy goals. And of course, election system metrics, such as audit rates or certification timelines.

For shared behavioral commitments we want cross-institutional constraints that bind behavior even under pressure. These might include pre-committed election integrity pacts, where all parties agree in advance to honor certified outcomes and legal processes. Surely we can legislate cross-branch enforcement norms, e.g., automatic compliance with subpoenas and bipartisan oversight triggers where predefined conditions force joint investigation regardless of party control.

If in cybersecurity, budgets and not policies reveal truth, then in politics allocation is the only credible signal of priority. But remember, it’s not just spending that matters, it’s spending on actual threats. Allocative alignment is not “money is spent.” It is “money is constrained by measurable reality and produces falsifiable outcomes.”

In my cybersecurity framing, allocative signals are strong because they are costly to reverse, they are observable, and critically, they are anchored to operational reality (i.e., risk, incidents, systems). But in politics, many allocations fail that last condition.

For example, immigration enforcement spending clearly signals a commitment to a narrative, but is not actually in alignment with empirical threat models - it lacks clear success criteria that could invalidate the policy. Thus it is a costly signal, but one that is not constrained by any truth⁸. Essentially we have a budget tied to symbolic priorities, where success is defined internally to the narrative and we lack any mechanism for disconfirmation. Ironically, the problem is not that we fail to spend; it’s that we increasingly spend in ways that reinforce narratives rather than constrain them.

Thus, what we are observing is not merely narrative distortion, but a systemic control failure: institutions no longer enforce the constraints that bind signals to reality. If we’re to restore reality, then claims, behavior, and resources must be forced back into alignment.

As in cybersecurity, the true test of a system is not its steady-state signaling, but its behavior under stress. Elections, pandemics, and international or economic crises exposed that institutional signals no longer held under pressure.

Norms are not sustained by agreement; they are sustained by coordinated, costly signals that produce real-world consequences. Trump was not the architect of a post-truth world; his administration was the first political entity to fully optimize for an environment where American institutional signaling had already collapsed. Until institutions are willing to make deviating from real-world reality costly again, the simulation will continue to govern.

1. Obviously I’m painting a fairly black and white picture here. We, the average citizen, can reasonably distinguish between the absurd (the election was rigged) and the likely (it wasn’t). It’s not always as simple as Occam’s razor, but this takes a kind of thoughtfulness that’s impossible when our attention spans have been reduced to 30 seconds between commercials. The rise of digital platforms that are by design built around ultra-short form content both exacerbates the problem and is a rational response to consumer demand.

2. While throughout this posting I’m borrowing from cybersecurity to analyze politics, I have seen stage four even within IT. At a previous position, a disastrous ERP deployment was described by the CIO as “so successful they haven’t invented words to describe it.” At once erasing the vocabulary of dissent, as well as creating a fictional reality around which all other narratives must be formed.

3. Actually I suspect a good argument can be made that academia creates friction for politicians in stages two through four. As is often quoted, “reality has a liberal bias.”

4. Of course, a variation of this has been in effect for as long as public comments on media have been supported. I noticed many years ago how comments in popular press journals repeat unsupported claims and build on them, cementing their “establishment” as fact. Before long, these claims become the centerpieces of actual articles and the circle is complete.

5. I should probably add Citizens United to this as perhaps the ultimate accelerant. Once corporations were granted effective citizenship, and wealth concentration became so extreme, everything I’m discussing experienced the rapid expansion. America has become a corporation, with us as mere shareholders of a single share.

6. Recall that during the Reagan years, when it became clear that ‘trickle down economics’ was a disaster, his administration didn’t modify their approach, they modified the economic model making predictions.

7. For example, mandatory disclosures of executive actions, use-of-force data, or emergency powers with automatic review triggers.

8. There’s another dimension here I’m not addressing in the main body: there’s an unspoken narrative that supports the entire anti-immigrant rhetoric, and that’s, simply put, racism. The real goal here is removing brown people from the country.