The Cost of Uncertainty

The Seduction of Explanation

We do not handle uncertainty well. We can survive suffering, instability, fear, even prolonged misery. What we struggle with is the absence of causality. The moment reality changes around us, the mind immediately starts searching for reasons. Why did the harvest fail? Why did the economy collapse? Why did my child become ill? Why did my marriage fail? Why did the empire fall?

At some point, the explanation itself matters less than the relief it provides.

Throughout history, we have accepted weak explanations, incomplete explanations, and completely fabricated explanations, provided they restored some sense of order to an otherwise chaotic world. Uncertainty is expensive, most of us cannot carry it for very long.

We are pattern-seeking mammals living in a probabilistic universe. Long before science existed, the ability to infer causality from incomplete information increased survival odds dramatically. A rustling sound in the bushes did not require a peer review before triggering a survival response. False positives were cheap, false negatives got eaten. The side effect is obvious: we infer causality even where none exists to better our survival.

Ancient civilizations sacrificed human beings to ensure the return of the sun. From their perspective, the evidence looked solid. The ritual was performed and the next morning, the sun returned. The alternative was too scary to think about. The conclusion was wrong, but the process itself was deeply human. Faced with uncertainty, we generated causality. We still do, only our stories became more sophisticated.

Today we approach uncertainty through two broad forms of analysis. The first builds predictive models. Given enough variables and reliable assumptions, future outcomes become forecastable. Economists model markets. Epidemiologists model disease spread. Climate scientists model long-term environmental systems. The assumption is simple: understand the system well enough, and the future becomes predictable.

The second approach works backwards by building an explanatory model. Instead of asking what will happen next, it asks what hidden structure could explain the observations already available. This is the engine behind conspiracy theories, speculative history, religious interpretation, and countless alternative frameworks. It is also how many scientific breakthroughs began. Continental drift, germ theory and meteor impacts killing the dinosaurs sounded absurd. Explanatory reconstruction is not inherently irrational. The danger appears somewhere else entirely.

Explanatory systems are seductive because they compress complexity into coherence. Erich von Däniken became famous not because he had compelling (or any) evidence for ancient astronauts, but because the theory explained so many disconnected observations elegantly. Ancient myths, impossible structures, astronomical symbolism, historical gaps. Suddenly everything fit together. The theory felt satisfying long before it became convincing.

We see the same mechanism everywhere.

The belief that vaccines cause autism survives despite overwhelming evidence against it. Not because everyone holding the belief is stupid, but because the theory performs an important psychological function. Autism appears gradually and painfully inside a family desperate for causality. Vaccination happened shortly beforehand. The timeline creates narrative gravity. If we compare the two explanations, one says autism is a highly complex neurodevelopmental condition influenced by genetics and partially understood environmental interactions. The other says something caused this. The second explanation may be wrong, but at least the suffering now has a reason.

And none of us are immune to this mechanism. At one point, I explored the possibility that Satoshi Nakamoto may have been an early artificial intelligence system. The theory explained a surprising number of anomalies elegantly. The communication patterns, the disappearance, the timing, the discipline. I had no evidence though and that was precisely what made it intellectually dangerous. I could feel my own mind rewarding the coherence long before confidence was justified. That is what explanatory systems do. They reduce uncertainty more effectively than they increase truth.

This is usually the point where analysis quietly turns into belief. A healthy explanatory model remains vulnerable to disproof. An unhealthy one becomes self-sealing. Contradictions stop weakening the theory and start feeding it, missing evidence becomes evidence of suppression, silence becomes concealment and criticism becomes proof the theory is threatening someone powerful.

The moment a theory can explain everything, it becomes strangely difficult to prove wrong. But intellectual honesty requires admitting something equally uncomfortable: institutions do this too.

History contains countless examples of events initially dismissed as paranoid fantasy that later turned out to be substantially true. Some great examples are MKUltra, Tuskegee or corporate deception around emissions testing. Governments lie, corporations hide things and institutions protect themselves. Blind trust in official explanations is no more rational than blind trust in alternative ones.

Which leaves us with a deeply uncomfortable task: learning to live with unresolved uncertainty without rushing to fill the gaps with emotionally satisfying explanations. Over time, our civilization developed intellectual tools specifically to resist this instinct.

Occam’s Razor exists because we have a tendency to keep adding invisible machinery to preserve comforting explanations. The simplest explanation is not automatically true, but every additional stacked assumption increases the odds that we are inventing structure instead of discovering it.

Bayesian reasoning forces us to accept that certainty is seldom justified. Beliefs should move gradually with evidence, not leap from possibility to conviction because a theory feels emotionally satisfying.

Hanlon’s Razor protects us from one of our oldest instincts: replacing chaos with intentional malice. Faced with incompetence or systemic complexity, conspiracy often feels emotionally easier than randomness.

Socratic skepticism may be the most uncomfortable tool of all. “I know that I know nothing” sounds simple until you actually try living that way. Remaining unresolved is psychologically very exhausting.

Science became powerful largely because it accepted incomplete causality instead of rushing toward closure. Scientific theories survive because reality repeatedly fails to destroy them, not because they feel emotionally complete.

In a world containing billions of searchable datapoints, absurd correlations become mathematically inevitable. Tyler Vigen demonstrated this beautifully on Spurious Correlations with, for example, a near-perfect correlation between Google searches for “why do I have green poop” and solar energy production in Bulgaria. The correlation is statistically real, while the causal relationship is obviously absurd. Yet part of the brain still wants to connect the dots somehow.

Vigen, T. (2024, February 13). Spurious Correlations. https://tylervigen.com/spurious-correlations

Ironically, the site recently added an AI-generated explanation section beneath many of the graphs, automatically inventing plausible causal stories for relationships that are fundamentally meaningless. It is both hilarious and deeply unsettling. Given enough data, patterns emerge. Given a sufficiently narrative-driven mind, explanations quickly follow.

Pattern recognition is automatic. Critical evaluation requires effort.

This is also why predictive theories occupy a fundamentally different category from purely explanatory systems. Astrology survives because it can continuously reinterpret reality around itself. Science tends to become uncomfortable when reality refuses to cooperate.

We should absolutely ask difficult questions. That is how progress happens. The problem starts when we become so attached to an explanation that disproving it begins to feel emotionally threatening.

Perhaps the hardest intellectual discipline is not skepticism toward others, but skepticism toward our own hunger for certainty. Most of us would rather accept a flawed explanation than endure the absence of one.

And to paraphrase the famous exchange from Men in Black:

Five hundred years ago, everybody knew the world was made of earth, water, fire, and wind.

Two hundred years ago, everybody knew it was made of indivisible atoms moving through predictable mechanical laws.

Today we know reality is held together by quantum mechanics, invisible forces, probabilities, and phenomena we barely understand.

Do you ever wonder what will hold it together tomorrow?

If this kind of structured doubt appeals to you, you might be interested in The Fifth Horseman, which brings together a range of historical and modern cases examined using the same approach. The book looks at how familiar stories often rest on surprisingly thin foundations, how neat explanations tend to unravel under closer inspection, and how the most honest conclusion is sometimes less certain than we would prefer, but more revealing than the popular version.