Probabilistic causation

 

I can see an assertion that effect can't exist without cause, but all kinds of things happen without effect, so cause can sit there and try and try and not achieve anything.

You’ve put your finger on something important, but I think two different ideas are getting tangled together.

The classic claim “no effect without a cause” is about necessary conditions: if something does happen (an effect), then there must be some cause or set of causes behind it. It’s not saying that causes are sufficient to guarantee effects.

What you’re pointing out is the flip side: a cause doesn’t guarantee an effect. And that’s absolutely right. In fact, most modern thinking—especially in physics and probability—leans heavily in that direction.

A few ways to sharpen it:

• A “cause” is rarely a single thing; it’s usually part of a set of conditions. Strike a match (cause), but without oxygen or with damp wood, no flame (effect).

• Many systems are probabilistic, not deterministic. In quantum mechanics, for example, a radioactive atom can “have the cause” (being unstable) but still not decay at a given moment. The cause sets a probability, not a certainty.

• In everyday life, we often mistake attempted causes for actual causes. If something “tries and fails,” it may simply mean the full causal conditions weren’t present.

So I’d rephrase your observation slightly:

Causes don’t ensure effects; they only make effects possible (or more likely).

That keeps the intuition you’re expressing, while avoiding a trap: saying “things happen without effect” sounds like events occur but produce nothing, which isn’t quite right—every event has consequences of some kind, even if trivial or unnoticed.

If you want to push this further, the really interesting question is whether causation itself is fundamental—or just a way our minds organize patterns. That’s where things get genuinely murky.

Very good, you almost made sense of my nonsesnse.

I wouldn’t call it nonsense at all—more like you were circling the target from an unusual angle.

What you did, in effect, was challenge the symmetry people often assume. We casually talk as if “cause → effect” were a tidy one-to-one pipeline, when in reality it’s lopsided: effects depend on causes, but causes don’t obligingly produce effects on demand. That asymmetry is real, and worth noticing.

Your phrasing—“cause can sit there and try and try and not achieve anything”—actually captures something quite deep. It points to the difference between:

• a disposition (something has the power or tendency to produce an effect), and

• an actualized event (the effect happening here and now)

A glass is fragile whether or not it ever breaks. The “cause” (fragility + a tap) may never quite line up into the full set of conditions needed for the effect.

Philosophers have wrestled with this for centuries. David Hume, for instance, argued that what we call “cause” is really just a habit of expecting one kind of event after another—we never actually see necessity itself. And modern science, especially in probabilistic fields, has quietly drifted closer to your intuition: the world isn’t a machine that guarantees outcomes, it’s more like a system that permits them.

So I’d say you weren’t talking nonsense—you were objecting to an oversimplified picture. You just phrased it in a way that made it sound more paradoxical than it is.

Pretty much everything that happens has effects; it is just not always, maybe even not usually, what we thing the effects will be.

Yes—that’s a much cleaner way to put it, and I think it lands right on the mark.

What you’re highlighting is less about whether effects exist, and more about our limited ability to track and predict them. In reality, events ripple outward in ways that are:

• too small to notice,

• too complex to follow, or

• too delayed or indirect for us to connect back to the original cause.

So we end up saying “nothing happened,” when in fact plenty happened—we just didn’t see it or didn’t recognize it.

There’s a quiet shift here from a simple chain (“A causes B”) to something more like a web of consequences. One action feeds into many pathways, and most of those pathways interact with others. By the time anything noticeable emerges, it may look quite different from what we expected.

This is very much in line with how modern science treats things. In chaos theory, for example, tiny differences in initial conditions can lead to wildly different outcomes, which makes prediction difficult even when causation is intact. And in complex systems, causes don’t map neatly to single effects at all—they diffuse through networks.

So your revised statement could be sharpened just a bit further:

Effects are ubiquitous, but our expectations about them are often crude, local, and wrong.

That keeps causation intact while putting the real limitation where it belongs—on us, not on the world.

How can we be sure that nothing happens without prior cause? It's a big universe and we can't observe everything.

Short answer: we can’t be absolutely sure.

What we have is not a proof, but a very strong habit of inference. Everywhere we’ve looked—at least within the domains we can observe—events seem to fit into patterns where earlier conditions help explain later ones. Over time, that becomes the working assumption: effects have causes.

But you’re right to press on the gap. As David Hume pointed out, we never actually observe causation itself—only regular sequences. We see A followed by B often enough that we expect B after A. The idea that A must produce B is something we supply, not something we directly witness.

Modern physics complicates things further. In quantum mechanics, certain events—like when a particular atom decays—don’t appear to have a specific, identifiable prior cause in the classical sense. You can describe probabilities with great precision, but not a definite trigger for a single event. Some interpretations say there is an underlying cause we just don’t see; others accept a degree of genuine randomness.

So where does that leave us?

• As a practical rule, “nothing happens without a cause” works extremely well and underpins science.

• As a philosophical certainty, it’s not provable.

• As a description of reality, it may need to be softened to something like:
  events arise from prior conditions, but not always in a strictly deterministic or individually traceable way.

Your instinct is exactly right: the universe is bigger than our observational reach, so any universal claim like that is, in the end, an assumption—albeit a very successful one.

Well, yes, we do have a bias to find causes, so we do, whether or not they are really causes or just associations.

Exactly—and that bias is both one of our greatest strengths and one of our most reliable sources of error.

Humans are almost compulsive pattern-finders. Once we see A followed by B a few times, we’re very quick to say “A causes B,” even when the relationship might be coincidence, indirect, or driven by some hidden factor. That tendency is what lets us learn quickly—but it also leads us astray.

David Hume again is helpful here: he argued that what we call “causation” is really just constant conjunction plus expectation. We see events paired, we form a habit of mind, and then we project necessity onto the world.

Modern thinking refines that rather than discarding it. In statistics, there’s a sharp distinction between correlation (things occurring together) and causation (one producing the other). And in cognitive science, researchers study this exact bias—we’re wired to infer agency and causality even from sparse or noisy data.

What’s interesting is that we can’t really get rid of this tendency without crippling ourselves. If we demanded absolute proof of causation before acting, we’d be paralyzed. So instead we live with a kind of calibrated compromise:

• Assume causation provisionally

• Test and refine those assumptions

• Stay aware that many “causes” may turn out to be misidentified

So you’re right: sometimes we are indeed “finding” causes that are really just associations. But without that bias, we wouldn’t find the genuine causes either. It’s a trade-off the mind seems to have accepted.

The assumption is that "genuine" causes exist; the reality is that there are so many factors contributing that picking one out is almost always a gross oversimplification. Even in carefully controlled experiments where one reaches the glorious Sigma 5, there remains a remainder.

That’s a very sharp way of putting it, and you’re not wrong to be suspicious of the word “genuine” when it’s used too neatly.

In most real-world situations, what we call a cause is really shorthand for something like “a dominant contributing factor under these conditions.” The underlying reality is almost always a dense tangle of influences—background conditions, interactions, timing, noise—so isolating one thread is, as you say, an abstraction.

Even in the cleanest cases, we’re simplifying. A well-designed experiment tries to hold everything constant except one variable, but that doesn’t mean the rest vanish; it just means we’ve made them less relevant for the question at hand. The famous “five sigma” standard in physics is really a statement about how unlikely it is that the observed effect is due to random fluctuation—not a declaration that all other contributing factors have been banished. There is always a residual, whether from measurement limits, unknown variables, or sheer stochasticity.

So perhaps a more careful way to talk is:

• Not “this is the cause,”

• but “this factor makes a measurable difference, given a controlled background.”

That shifts causation from something absolute to something contextual and graded.

There’s also a useful distinction lurking here. Some causes are:

• Necessary (without them, the effect won’t occur),

• Sufficient (they guarantee the effect),

• and in practice, most real causes are neither alone—they’re INUS conditions (an “insufficient but non-redundant part of an unnecessary but sufficient set”).

That mouthful just formalizes your intuition: any single factor is usually only one piece of a larger configuration.

So I’d push back just a hair on one point—not to disagree, but to sharpen it. It’s not that “genuine causes” don’t exist; it’s that they almost never exist in isolation. What we call a cause is a handle we put on a complex system so we can reason about it without drowning in detail.

And that lingering “remainder” you mention—that’s not a flaw in the method so much as a reminder of the world’s irreducible richness.

The point I'm really after though is not that causation is complex and easily misread, but the very assumption that there is always complete causation, that in the mix there might be uncaused elements. The idea that such factors don't exist, that if we achieve enough detail all events are completely causes by prior events, is an assumption based on incomplete experience.

Ah—that makes your point much clearer. You’re not talking about the practical limits of isolating causes; you’re questioning the ontological assumption itself: that everything that happens is fully determined by prior events. That’s a very different—and much deeper—question.

You’re right that it’s an assumption, not something we can prove. We’ve observed that most events seem to follow patterns and have antecedents, so it becomes natural to generalize and assume a universal causal closure. But that’s an extrapolation, not an observation. It’s entirely possible—at least in principle—that there are events, factors, or “sparks” in the universe that are uncaused in any classical sense.

Quantum mechanics nudges this idea. For instance, in quantum mechanics, certain interpretations suggest that individual quantum events—like a single radioactive decay—don’t have a prior cause in the classical sense; they’re genuinely probabilistic. Even if other interpretations try to sneak in hidden variables, the fact remains that at our level of knowledge, some events seem uncaused or intrinsically random.

Philosophically, you’re touching on the difference between:

• Determinism: every event is necessitated by prior events.

• Indeterminism: some events are not fully caused and may include genuine novelty or randomness.

Your critique is valid: assuming universal determinism is an assumption of completeness, not an empirical fact. Even if the universe is mostly predictable, that doesn’t rule out exceptions. We simply can’t know that no uncaused events exist; our experience is too limited, and our inference too habit-bound.

In short: the claim “everything has a cause” is a deeply ingrained working assumption, not a logically or empirically necessary truth. Your insight is that it might just be wrong at some level—and that possibility has profound implications for how we think about freedom, chance, and novelty in the universe.

If you want, I can try to sketch a way of thinking about how a universe with both caused and uncaused events would behave, just to give some intuition for your idea. Do you want me to do that?

Nuclear decay is probabilistic, not random. There is a buried hint of cause in there.

Exactly—that’s an important nuance. “Random” suggests pure chaos with no underlying principle, whereas nuclear decay is probabilistic: it follows precise statistical laws. For a given isotope, we can predict its half-life with extraordinary accuracy, even though we can’t pinpoint the exact moment an individual atom will decay.

In a sense, the “cause” is hidden in the probability distribution itself. The atom isn’t acting without a reason—it’s embedded in a lawful pattern, just not one that lets us trace a single deterministic chain. The laws give propensity rather than certainty.

So the event is not uncaused in the broad sense: it is caused by the combination of quantum structure, interactions, and laws of physics—but it’s uncaused in the classical, singular-event sense. That’s why probabilistic events feel like the “hint of cause” you mentioned—they’re governed by causes at the statistical or structural level, even if individual occurrences remain unpredictable.

If you want, we can go even deeper into how this kind of probabilistic causation might affect the philosophical assumption that “everything has a prior cause.” It’s subtle but fascinating.

Macro events are generally similarly probabilistic, but made to seem determined by the law of large numbers.

Exactly—that’s a key insight. At the macro level, what seems deterministic is often just statistical regularity in disguise. The law of large numbers smooths out individual probabilistic events, producing the illusion of certainty.

Take, for example, rolling a million dice. Each die is unpredictable, but the average outcome becomes sharply predictable. Similarly, weather, traffic, or even population dynamics are composed of countless micro-level events, each probabilistic, but collectively they follow patterns that look deterministic. That’s why people casually speak as if macro events have causes in the classical sense—it’s a convenient shorthand.

The underlying reality is that macro determinism is emergent, not fundamental. The apparent “laws” we observe—like Newtonian mechanics—are statistical regularities built on top of deep probabilistic foundations. So the universe may be full of probabilistic micro-events, and macro patterns simply mask that indeterminacy.

It’s a subtle but important point: what feels like a fixed, fully caused chain of events is often just a high-probability path among a sea of possibilities, not a guarantee.

If you want, we could explore what that implies for your original intuition: that maybe some events—or “elements of novelty”—truly have no classical cause at all. That’s where the discussion starts to get really interesting.