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Emergence Spirals—what Yudkowsky gets wrong
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本文探讨了“涌现”这一概念在复杂系统中的应用,并对Elizier Yudkowsky关于涌现的观点进行了辩论。文章认为,涌现并非神秘的,而是可量化的。通过跨学科视角,结合系统理论、科学、历史和哲学,提出了衡量涌现的新标准,强调了涌现与熵、趋同演化、以及循环演进的关系,并以交通系统、黏菌和免疫系统为例,阐释了涌现的层级结构和螺旋式发展。文章旨在帮助读者更深入地理解复杂系统的演化过程,并提供了一种新的视角来审视世界。

🧠 **涌现并非神秘:** 文章认为,涌现并非不可理解的神秘现象,而是可以通过量化标准来衡量的。它反对将涌现简单地视为对复杂现象的模糊解释,主张关注潜在的机制。

💡 **趋同演化是关键:** 文章强调趋同演化是理解涌现的关键。例如,眼睛在不同物种中独立进化,但都具有相似的功能,这表明了在宏观层面上趋同于特定功能的重要性。这种趋同性也体现在黏菌的网络结构和交通系统的高效性上。

🔄 **涌现的循环结构:** 作者提出了涌现的循环结构,一个稳定的系统在摩擦下被扰动,然后找到新的平衡,成为新现象的基质。这个循环可以分为适应、共生和层级三种形式。免疫系统和进化都被认为是这种循环的例子,展示了复杂性层层叠加的过程。

Published on June 8, 2025 7:02 PM GMT

Before proposing the following ideas and critiquing those of Yudkowsky, I want to acknowledge that I’m no expert in this area—simply a committed and (somewhat) rigorous speculator. This is not meant as a “smack down” (of a post written 18 years ago) but rather a broadening of the discussion, offering new, more quantifiable measures of emergence for your consideration.

In his 2007 post The Futility of Emergence, Elizier Yudkowsky argues that the term ‘ emergence’ is used vaguely and misleadingly—as a mysterious explanation rather than a real one.

“… after the answer of “Why? Emergence!” is given, the phenomenon is still a mystery and possesses the same sacred impenetrability it had at the start.”

He critiques the tendency to describe complex macroscopic patterns (like consciousness or whirlpools) as if they have independent causal power, when in reality, they are just the predictable consequences of underlying mechanisms. Where large-scale patterns can be reduced to their component interactions, Yudkowsky suggests we should focus on these underlying mechanisms.

On this blog, we care about explaining complexity without resorting to mysticism—or reductionist dismissal. Curious people want to see the deeper patterns that shape real systems, so we can make sense of the world and reason more effectively. But in our series on Emergence, I’ve leaned heavily on the idea of emergent complexity to make sense of phenomena that are reducible to underlying mechanisms. I disagree with Yudkowsky that this need be misleading or vague. This post, as per usual will take a cross-disciplinary view, drawing from systems theory, science, history and philosophy. So, let’s get specific.

Not Everything is Emergent

I agree with Yudkowsky that it is possible to over-use the term, and apply it to anything that emerges from underlying mechanisms. So, it’s important to distinguish what does and doesn’t qualify as ‘ emergent’.

I’d like to make the case that emergent complexity is where…

So, when we look at an eye, we can see that it can be understood as something that fits the purpose of producing a picture of the physical world. Microscopically it is a configuration of cells, just like a big toe or a testicle, but macroscopically it is more like a camera.

On the other hand, the majority of phenomena that emerge from a system aren’t “emergent”, in that they do not add complexity, but rather decrease it, consistent with the Second law of thermodynamics. Take the traffic system for instance, this creates heat and noise, increasing entropy. Heat and noise are properties of the system, but they are not emergentproperties of the system.

Emergent systems are identified by their (apparent) inverse relationship to entropy.

Convergence

The traffic system creates noise and heat, but it also creates a level of friction and inefficiency which leads to roading measures that eventually make the roading system more efficient, this will predictably happen, because inefficiency is a constant pressure on the system to change in a particular direction.

Now, one could say these changes are the result of the collective decisions of intelligent individuals, and are therefore not genuinely emergent—that is until we see the same patterns of efficiency echo throughout nature independent of intelligence, specifically in the nutrient pathways of slime-molds.

When searching for food in a sparse environment, the slime mold Physarum polycephalum naturally forms networks of protoplasmic tubes that connect nutrient sources with astonishing efficiency. Studies reveal that the slime mold’s network design can closely resemble the layout of the Tokyo rail system.

Convergent Evolution

It is said that the eye has developed independently in more than 20 different species, this is due to the supreme benefit of vision for the survival and reproduction of a species and the transmission of those genes. But if we take Yudkowsky’s perspective—emergent phenomena are merely reducible to their component parts and are therefore not real in any meaningful sense—then aren’t we wrong to call these 20+ varieties “eyes” at all, or to call what they do “seeing”, because they are made of entirely different components.

It is the fact that we recognise them on a macroscopic scale converging on a common function that it makes sense to call them “eyes”. The same is true of other convergent phenomena, like the slime mold and traffic systems.

Nature Answers Questions

This convergence is a phenomenon that is best understood from a macroscopic perspective—as an answer to the question “What is the most efficient system of pathways?” (for slime mold and traffic) or “what physical objects are in my vicinity?” (for vision). These questions can be answered by various different systems.

Design?

At this point it’s important to note that a system answering a question, or fitting a macroscopic scaffold or a specified “function” is a teleological perspective that might seem to suggest design—a top-down force determining the shape of a system. And this might be an interpretation Yudkowsky wants to avoid altogether—giving it a wide birth by denying the macroscopic view of a system. But this is unnecessary caution. We can acknowledge macroscopic systems (a top-down perspective) without denying their microscopic (bottom-up) origins. We understand that the emergent system of evolution gives an “ illusion of design” it doesn’t require the existence of a designer.

One might say that the “design” process itself is actually an emergent outcome of neural activity, analogous to evolution anyway… (so even design isn’t really design)

In the cases mentioned so far, the function of the system means that it is “ more closely aligned with a macroscopic phenomenon than with its component parts” (the slime mold is aligned with the same macroscopic structure as the traffic system, the eye is aligned with the physical environment) rather than with the complicated configuration of the cells, neurones and electrical signals that comprise the system itself.

This recognition of convergence is a confirmation of emergence.

Substrates

I’d like to make the case that a good measure of whether a system is emergent, is not whether it is irreducible (no system is provably irreducible) but that something can be described as emergent when it has completed an emergent cycle, in that it has taken a system (the substrate) and, through exposure to some friction in the system, reliably generated a new phenomenon which reaches an equilibrium that now creates a substrate or niche for something new to emerge.

To continue with the traffic and slime mold examples, once a system has reached a reliable state of efficiency, then it becomes a substrate or niche for a new emergent cycle on top. A traffic system enables systems like mass food transportation, commerce and social networks not previously possible. Take the internet, another system of transportation (for data), think of all the entirely new industries this spawned, e-commerce, web design, citizen journalism, influencers, even AI.

Similarly, the slime mold Dictyostelium discoideum has been found to have developed ‘primitive farming symbiosis’.

“Instead of consuming all bacteria in their patch, they stop feeding early and incorporate bacteria into their fruiting bodies. They then carry bacteria during spore dispersal and can seed a new food crop, which is a major advantage if edible bacteria are lacking at the new site.”—Nature

And this is not unique to slime molds, according to nature there is a…

“… striking convergent evolution between bacterial husbandry in social amoebas and fungus farming in social insects”

Again, we see convergence as a confirmation of emergence, specifically that an emergent cycle has taken place.

The Emergent Cycle

The way I see it, the emergent cycle has a specific structure that we see all around us in nature. We begin with a stable system, but stable systems exist in a world with friction, so at some point they are pathologically disturbed by some constant friction, driving the system out of balance, and it either dies or finds a new equilibrium which incorporates the disturbance, becoming the substrate for a new phenomenon.

There are a few ways we can look at how a friction is incorporated.

    Adaptation—the whole system changes, to create a novel systemSymbiosis—the original system and pathology develop harmonyHierarchy—the pathology becomes a new phenomena dependent on the original system (equilibrium).

I see emergence as the third category, not mere adaptation or symbiosis, but layers of increasing complexity, each dependent on the one below.

Immunity

A realm that develops in cycles that builds on top of one another is immunity. In The Red Queen, Matt Ridley explains that not only can our immune system develop a memory of anti-bodies against diseases we’ve faced in our lifetime, but that sexual selection allows for a genetic memory—where resistance to certain diseases can be held dormant in our genes, and rediscovered more efficiently when faced with the same threat generations later. Our genetic memory of history can help us better deal with the echoes of history. This cumulative cycle takes the form of a spiral, allowing for a new layer to be built atop the established substrate.

The Emergent Spiral

If we look at the canonical example of emergence—evolution by natural selection—we have something that can be generally adaptive rather than hierarchical, in that it creates more of the same rather than a new layer of complexity. We can see this as a feedback loop that increases capacity.

This is more an adaptive situation because one species does not become the substrate for a new phenomenon. But, often evolution yields hierarchical results—generating an emergent spiral.

Here we see an entirely different paradigm ‘language’ emerge on top of an intelligent species. Language is categorically different from the biological species it is derived from, but it is dependent on it. This is an emergent phenomenon in the strongest sense.

But this emergent spiral doesn’t only manifest in nature, these cycles are ubiquitous across different realms. As I’ve had this in the back of my head for a while, I’ve experienced the Baader-Meinhof phenomenon on many occasions, noticing parallels to philosophy, history, science and others.

History Repeats

I think the clearest comes from Hegel (ironically, because Hegel is famously inscrutable). Hegel’s dialectic concerned how a concept (particularly one that exists in the messy real world of history) holds internal contradictions which will ultimately lead to internal conflict, and the transformation of the concept into something richer. It is commonly simplified in the form: Thesis > Antithesis > Synthesis.

Hegel’s classic model maps the evolution of political ideology and philosophical schools throughout history. It goes—simplistic ideas are vulnerable to argument (friction), and so they are forced to adapt, sometimes landing on entirely new paradigms. When a new paradigm gets ingrained and inflexible, it then falls victim to a type of Goodhart’s Law becoming vulnerable, once again, to radical new ideas.

Although Hegel’s model looks like a cycle, it is actually a spiral, as it refers to History which moves chronologically—history repeats, but if we record and remember the lessons of history, cycles need not fold back exactly on themselves.

Scientific Discovery

In the realm of science, Karl Popper has a related cycle regarding intellectual discovery, which he formulates as: P1 > TT > EE > P2.

In Popper’s intellectual autobiography Unended Quest, he holds that the accumulation of knowledge follows a similar loop to Hegel’s. You begin with a problem (P1), develop a tentative theory (TT), then eliminate the errors in that theory (EE—through the scientific method, peer review etc) creating a new equilibrium. And until we come up with a genuine theory of everything, the loose ends of that theory will inevitably lead to friction and a new problem (P2).

Unlike our cycle, Popper starts at the problem, but shift everything forward and you have the same cycle.

Popper also draws parallels between inorganic physics, biology and intellectual discovery. Popper refers to organisms as problem-solving structures. My sense is that creative processes whether by nature or design follow this pattern.

Returning to Yudkowsky

Now that we have a sense of emergent cycles—what they are and what they are not, looking in detail at Yudkowsky’s criticisms, we see that his target is not actually emergence (as I understand it at least). Yudkowsky asserts:

Gravity arises from the curvature of spacetime, according to the specific mathematical model of General Relativity.

Here, Yudkowsky lampoons the case that gravity is an emergent property of the curvature of space time, and he is right to do so, but only because of the way he has formed the argument. Gravity does not emerge from the curvature of spacetime, gravity is the curvature of spacetime. General relativity requires the existence of mass, for this model—it does not explain how mass exists. Theories of emergent gravity like the one I’ve explored, target how mass itself arises and the resulting gravitational effects, rather than how gravity can be modelled.

Yudkowsky also takes aim at intelligence:

I have lost track of how many times I have heard people say, “Intelligence is an emergent phenomenon!” as if that explained intelligence.

I would argue the description of something as emergent doesn’t explain what something is, rather it fits it to a recognisable structure that can help us understand it better. By recognising the natural selection of neurones, through the environment of stimulus, we can understand it by analogy to evolution, another emergent cycle (that intelligence itself rests upon) and it then no longer…

… possesses the same sacred impenetrability it had at the start.

Is Emergence Magic?

Yudkowsky extends this (somewhat uncharitable) reading of emergence into full straw-man when he equates emergence with magic. And I think this helps to pin-point the key concern he has when looking at the idea of emergent phenomena. I share this concern, that emergence…

… gives you a sacred mystery to worship. Emergence is popular because it is the junk food of curiosity. You can explain anything using emergence, and so people do just that; for it feels so wonderful to explain things.

As mentioned, I think this caution against attributing the properties of systems to design (or magic in this case) is unnecessary. We can understand phenomena in macroscopic terms like function, purpose, as a solution to a problem, or an answer to a question and we can recognise alignment with other macroscopic phenomena by analogy without denying the microscopic nature of causality. Emergence is a way of understanding complex systems that acknowledges that complexity arises out of particular sets of simple rules, in a way that seems wondrous… even magical, but is, by definition, not magical.

So…

I don’t doubt some people do use “emergence” as a way to curtail their own curiosity, and hand wave over more complex and nuanced (and effortful) engagement with the world around us. But, I don’t see this as the purpose of ‘emergence’ as term. I see the term as a way of aligning our understanding of something novel that we might not yet fully comprehend with other macroscopic phenomena we do comprehend. By understanding emergence as a series of cycles that emerge from friction, reach equilibrium and become a substrate for the next cycle, we can better respond or cater to the needs of that system—seeing the forest despite the trees.


Originally published at https://nonzerosum.games.

 



 



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涌现 复杂系统 趋同演化 系统理论
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