Anarchy, Ants and Artificial Intelligence: What Emergence has to offer the Revolutionist

By: The Popular Education Commandos of the Curious George Brigade

Emergence is a not so much a theory as a principle of self-organization displayed by elemental particles, computer simulations, insect colonies, primate behaviors, child development and social/cultural movements. Over the past decade the obscure mathematics and science of emergence have started to seep out from the laboratories into the popular consciousness of folks studying everything from Hopi weavings to neurological functions: Yet, those seeking to replace the current exploitative systems with a “new world in our hearts” have mostly ignored emergence. This ignorance has limited our ability to expand and create a credible counter-culture of resistance. This introductory educational monograph suggests there is much for us to learn when it comes to promoting self-organization and that our teachers are sometimes the most unlikely mentors.

Emergence is not the new Marxism
The first thing we must understand about emergence is that it is not a theory in the traditional sense. It doesn’t seek to explain anything, but reveal how things organize themselves. It makes no judgment on this type of organization. Emergence can lead just as easy to vigilante mobs as to pirate radio stations. Emergence primarily focuses on the mathematical and physical relations of organization, divorced of morality and ethics. It is an observational model that helps us understand some things while leaving roots causes obscure. It is best for understanding extremely complex entities and tracing how simple individuals arrange themselves into sustainable complex and subtle organizations.

What is Emergence?
Emergence is the process of complex pattern formation from simpler units. This can be a dynamic process (occurring over time), such as the evolution of the human brain over thousands of successive generations; or emergence can happen over disparate size scales, such as the interactions between a macroscopic number of neurons producing a human brain capable of thought (even though the constituent neurons are not themselves conscious, nor the thoughts always that good). For a phenomenon to be termed emergent it should generally be unexpected and unpredictable from a lower level description. Usually the phenomenon does not exist at all or only in trace amounts in the very initial building block.
Now think of revolution or radical social change. At present there seems to be little agreement on how, when, where or even if such changes will occur. Emergence says that this debate is futile, time-wasting, since it is impossible to witness the emergent structure from the small isolated collectives and individuals. The traces of the revolution may be there but how they will combine and self-organize is inherently impossible to predict from our perspective. So how is it possible that a group of disparate and relatively small collectives working on simple goals (e.g. Food not Bombs providing free food) can create meaningful and radical change. Before we answer that question we need to look more deeply at what principles promote emergence.

An emergent behavior or emergent property can appear when a number of simple entities (agents) operate in an environment, forming more complex behaviors through a collective action. The property itself is often unpredictable and unprecedented, and represents a new level of the system's evolution. The complex behavior or properties are not properties of any single such entity, nor can they easily be predicted or deduced from behavior in the lower-level entities. The shape and behavior of a flock of birds or school of fish are good examples. You can not pick out the shape of a school of fish by simply studying the anatomy of the individual fish.
One reason why emergent behavior occurs is that the number of interactions between components of a system increases combinatorially with the number of components, thus potentially allowing for many new and subtle types of behavior to emerge. For example, the possible interactions between groups of molecules grows enormously with the number of molecules such that it is impossible for a computer to even count the number of arrangements for a system as small as 20 molecules.
Interactions are crucial for the health of any type of social organization and especially one of resistance. It is not simply a coincidence all rebel groups have put enormous energy in propaganda, communications and building networks in order to maximize interconnectivity. But we believe this is not enough.

Guidelines for building an Ant Revolution
Feedback Loops
It is essential that the individuals of any emergent system have constant interaction with each other. Merely having a large number of interactions is not enough by itself to guarantee emergent behavior; many of the interactions may be negligible or irrelevant, or may cancel each other out. In some cases, a large number of interactions can in fact work against the emergence of interesting behavior, by creating a lot of "noise" to drown out any emerging "signal"; the emergent behavior may need to be temporarily isolated from other interactions before it reaches the critical mass to be self-supporting.
We all know how difficult it is to create a collective in complete isolation of a radical milieu. Our brothers & sisters in Nowhere, Kansas have long since complained and illustrated this point. We also know that having endless meetings between collectives can actually be counter-productive. The collectives spend so much time working for the coalition/federation/network that they stop doing their own important work. So how can we structure our interactions to maximize emergence?
It is not just the sheer number of connections between components which encourages emergence; it is also how these connections are organized. A hierarchical organization is one example which can sometimes generate emergent behavior (a bureaucracy may behave in a way quite different to that of the individual humans in that bureaucracy); but perhaps more interestingly, emergent behavior often arises from decentralized organizational structures, like the convergence at a mass mobilization. In most cases, the system has to reach a certain combined threshold of diversity, organization, and connectivity before emergent behavior appears.
In revolutionary Russia, anarchist thinkers like Makhno, tried to understand why the Bolsheviks out organized the anarchists despite having smaller numbers. Unfortunately many anarchist theorists have decided a stronger (read more bureaucratic) organization is the key to promote a vital resistance. While it would be folly to argue that hierarchical organizations do not sometimes promote , powerful social structures, they also unfortunately lead inevitably to less freedom and greater exploitation. Decentralized non-heirarchical structures can achieve the same level of organization (perhaps even more complex) without the negative effects of oppression and limiting liberty. This type of complexity is also confounding to the State and other forces of oppression who think in terms of pacemakers and leaders. This can be done by using the principles of emergence. To answer Makhno’s question, is not to create a party or some super-social structure but create an environment which will accelerate emergent behavior.
Systems with emergent properties or emergent structures may appear to defy entropic principles and the second law of thermodynamics, because they form and increase order despite the lack of command and central control. Simply put, they create complexity out of random chaos.This is possible because open systems can extract information and order out of the environment and meaningful interactions with each other.
In fact a hierarchy interferes with this process of data collection by forcing it to be funneled through a central committee. It seems if we are interested in promoting complexity and depth to our resistances we need to reject the implementation of a single ideology or hierarchy, not only because it is oppressive but also because it hampers our efforts to expand and diversify our resistance to Capitalism and the State. In a search for useful principles in supporting emergence we will now turn to the natural world.
Emergent structures are patterns not created by a single event or rule. There is nothing that commands the system to form a pattern, but instead the interactions of each part to its immediate surroundings causes a complex process which leads to complexity. One might conclude that emergent structures are more than the sum of their parts because the emergent order will not arise if the various parts are simply coexisting; the interaction of these parts is central.
Feedback loops are both positive and negative. Negative feedback systems are like your home’s thermostat. When a temperature is reached the furnace shuts off. Most hierarchical organizations use a negative feedback system to govern their actions and thus are primarily reactive in nature. Positive feedback is a bit more complicated can be located both in nature and in society.
Positive feedback can be illustrated with an economics example. Sony was generally credited with having the superior videotape technology with its Beta format and was first to market. However, a larger number of companies came to support the competing VHS videotape format initially developed by JVC. Although the image was not as sharp as the Sony Beta, these decks were less expensive and had a longer playing time, and over time, more and more consumers came to purchase VHS tape decks. When movie videos began to be popular, more tapes were available in the rental stores in the VHS format (because more people had VHS decks), which in turn influenced more people to purchase VHS tape decks because there was a larger movie selection. This feedback loop of more people wanting VHS tapes leading to more VHS decks being sold continued for several years, and finally Sony ceased making Beta videotape machines altogether.

As the example discusses, the output from one state of the system (the number of VHS tape decks and the number of videotapes) is fed back into the system, which then leads to more VHS tape decks and more VHS video tapes, which then lead to more VHS tape decks and more videos, and so on. Positive feedback loops are an important characteristic of many complex systems, and constitute one of the interaction processes that contribute to nonlinearities and emergence in complex systems.
There is no control or command in positive feedback (unlike most negative feed back loops). The system is similar to the idea of the “tipping point” popularized about a decade ago. Anarchists can increase feedback by creating more integrated projects. As more independent media sources appear, there is more room for radical programming which begets more radical propaganda. Mutual aid can actually promote fairly complex and nuiasanced systems of economy as pointed out a 100+ years ago by Kropotkin. We need to have interrelated projects and places where feedback (both positive and negative) can be used by the individuals and small groups to coordinate their activities.
Bringing out the Dead: How Ants just do it.
A biological example of an emergent system is an ant colony. The queen does not give direct orders and does not tell the ants what to do. Instead, each ant reacts to stimuli in the form of chemical scent from larvae, other ants, intruders, food and build up of waste, and leaves behind a chemical trail, which, in turn, provides a stimulus to other ants. Here each ant is an autonomous and an unspecialized unit that reacts depending only on its local environment and the genetically encoded rules. Despite the lack of centralized decision making, ant colonies exhibit complex behavior and have the ability to solve complex geometric problems as a collective. For example, the ant colonies routinely find the maximum distance from all colony entrances to dispose of dead bodies.
Anarchists need to be more like ants, drawing information from our comrades and the environment. Together we can create (or emerge if you will) complex and ever-changing tactics to confound the authorities. The tactics and complexity of the possible of the number variables that go into any confrontation with authorities is undoubtably to complex for any individual or group to come up with. We do not need leaders, by-laws, membership dues. What we need is information and feedback.
Emergence is not limited to animals and molecules it is also seen in human societies. Emergence has been used to examine everything from cities to poker games.
Emergence in Human Culture
Emergent processes or behaviors can be seen in many places, from any multicellular biological organism to traffic patterns, city growth or organizational phenomena in computer simulations and cellular automata. The stock market is an example of emergence on a grand scale. As a whole, it precisely regulates the relative prices of companies’ stocks across the world, yet it has no leader; there is no one entity which controls the workings of the entire market. Agents, or investors, have knowledge of only a limited number of companies within their portfolio, and must follow the regulatory rules of the market. Through the interactions of individual investors the complexity of the stock market as a whole emerges.
Popular examples for emergence are Linux and other open source projects, the World Wide Web (WWW), and the various Sims games. Emergence is the major reason for the great success of Wikipedia. All of these decentralized and distributed projects are not possible without a huge number of participants and volunteers. No participant alone knows the whole structure, everyone knows and edits only a part, although all participants participate in something larger than themselves, and thus their individual contribution may be minimal the result can be enormously complex. Feedback increases motivation and unity, the bottom-up contributions increase variety and diversity. This diversity is essential to the complexity of emergent structures.
Making an emergent system more sustainable and adaptive mostly has to do with tinkering not with the base instructions of the individual group members but the feedback systems. There needs to be both positive and negative feedback in any self-organizing system that is discernable from the noise of all other interactions. Most automated systems rely on negative feedback. Negative feedback is what is used in a home’s thermostat. When the temperature reaches a certain temperature the furnace stops blowing hot air. Positive feedback is what encourages more of the same behavior. For example this is the “Tipping Point” idea which began by looking at neighborhoods in large urban centers. Morton Grodzins, who studied integrating neighborhoods in the early 1960s, discovered that most of the white families would remain in the neighborhood so long as the comparative number of black families remained very small. But, at a certain point, when "one too many" black families arrived, the remaining white families would move out en masse in a process known as white flight and thus drop the property values and more and more poorer families (mostly people of color) would move in. Most emergent systems use a combination of both positive and negative feedback loops.
Emergent structures appear at many different levels of organization. Emergent self-organization appears frequently in shanty towns where no planning or zoning entity predetermined the layout of the city. Literally hundreds of millions of experiments in self-organization are being conducted across the world in shanty towns. Some emerge to create sustainable and vibrant communities while others descend in entropy.
We need to spend time developing real feedback systems between our projects and communities. We need places where self-organizing can emerge from bottom-up. The good news is there are some principles for creating effective feedback systems which are so important for promoting adaptive and vital emergent systems. These principles include: multiple interactions; maximizing feedback (positive in particular); creating systems in which the input of the individual can be minimal but correctable thus creating a complex egregate beyond the control of any individual in the group; allowing maximum diversity and promoting decentralization.
How many is Enough?
It should not come as a surprise that different types of agents have different thresholds for optimum self-organizing. Slime-mold needs millions of cells before emergence can develop and self-organize trillions of individual cells. Ant colonies, despite some variations have certain minimum and maximum thresholds for self-organizing. Only in the realm of computer simulations does the number seem to be infinitely variable.
Recently there have been some interesting studies on feedback versus noise among human groups. In a now famous study out of Canada, a group of researchers conducted an ingenious study about our ability to receive feedback from different size groups. A subject was asked to read a speech to classrooms of various sizes. The listeners were then asked to rate a number of variables including presentation; interest in the subject; and so on. The subject then was asked to guess what the average response of the listeners on the same variables. Up to class sizes of about 80, the subject was able to closely match the experiences (as reported by responses on the survey) of the listeners. When class size was increased above 80, the subject scored very poorly. It seems the amount of feedback we can receive person-to-person is limited.
Size does matter, for self organizing at least. We need to figure out for ourselves what size is the best for our projects. We have all sat in large spokes-council meetings where the facilitators seem oblivious to the mood of the audience. This may not be due to bad facilitation, the meetings may simply be too large. We need to tinker with our feedback systems to figure out what works best for promoting growth and adaptation.
Not being able to separate noise from feedback (negative or positive) can have disastrous results. In nature, the “cultures” of the Bonobo (pygmy chimp) and the Chimpanzee illustrate this. The Bononbo society is roughly egalitarian with limited aggression and great deal of nurturing behavior; while the Chimpanzee is a highly hierarchical society with alarming instances of infanticide, rape, violence and even cannibalism. One theory gaining ground among animal behaviorists is that chimpanzees, unlike Bonobos, are poorer at interpreting body language and facial signals of others. It seems the groups of chimpanzees have grown in size (no doubt due to a shrinking habitat) to the point where they receive so much noise, they misread body language which begets violent outbreaks and confusion. Bonobos who live in smaller groups and spend a great deal of time in collective work including sleeping together, have a better ability to “read the bodies” of their comrades as demonstrated by a number of recent studies. This better feedback system reduces stress and limits the outbreaks of anti-social behavior.
Anarchists can learn from the Bonobo/Chimp example. By organizing in small groups, getting to know our social environment intimately through collective work and social projects we can better interpret the feedback from the noise and adjust our behaviors more appropriately. This gives us a huge advantage over hierarchical organizations that isolate individuals and tries to limit information from the immediate surroundings so its agents can focus on commands from the center. Hierarchically formed organizations suffer from the “Kafka problem”; where noise is misperceived as feedback orientated information. The most absurd conclusions can be made, like the not uncommon problem of someone trying to prove to a bureaucrat that they are in fact not deceased despite a computer glitch that says they are. This is a clear example when the individuals in an organization can not meaningfully interpret information from their environment.
From Chaos to Community
Emergence evolved from chaos theory. It examines how complex and adaptable patterns are formed in unpredictable ways. Emergence has spread from physics and biology to nearly every academic discipline. It offers up more questions than answers and that’s what makes it so fertile and exciting as a model. This model does suggest some key principles that promote emergent systems. These principles include: initially limited numbers; decentralization; and access to direct feedback from the local environment. Emergence provides a unique approach for understanding why certain anarchist projects succeed while others degenerate into entropy. The world is constantly emerging (from shanty towns to wikipedia) and there are examples all around us to draw upon.

Further Reading
· John H. Holland, Emergence from chaos to order (1998) Oxford University Press
· Steven Johnson, Emergence (2002) Scribner
· Gregory Bateson, Steps to an Ecology of Mind (1972) Ballantine Books
· Kevin Kelly, Out of Control (1994) Perseus Books Group
· Stephen Wolfram, A New Kind of Science (2002)
· Mario Augusto Bunge, "Emergence and Convergence" (2001)
· Jochen Fromm, The emergence of complexity (2004) Kassel University Press