As we look out into the future, many of the key problems we must solve this century arise from coordination failures at multiple scales of our existing institutional systems. Climate change, existential risk from technology, energy and materials each share something in common — they are examples of multipolar traps arising when individuals and groups pursue their own selfish incentives at the expense of the collective benefit, in games that are increasingly global in their domain of action.

Multipolar traps are nothing new, and have been around for as long as life on Earth. Fortunately, stable solutions to multipolar traps have been continuously selected for at many levels of the evolutionary hierarchy. These are most visible in cases of major evolutionary transitions, in which groups of competing individuals cooperate to form new kinds of individuals at higher levels of organisation.

In search of solutions for the future, we can learn a lot from understanding what is common to the transitions of the past. At the very least, they show us that it is possible to establish stable cooperation at scale. Further, perhaps, they can provide clues for how we might establish an evolutionary trajectory towards intelligent coordination at planetary scale.

In this article, I aim to provide an accessible entry point to what the major evolutionary transitions have been, what we know about how they have happened and what has been common between them.

What is a major evolutionary transition?

Major evolutionary transitions represent rare points in evolutionary history in which groups of competing individuals came together to form a new cooperating whole at a higher level of organisation.

The most familiar example is the development of human societies. Way back in our evolutionary past, proto-humans lived primarily as self-sufficient individuals. As we fast forward through human history, however, we see the development of cooperative societies at increasing scale.

Of course, this has been a slow evolutionary trajectory. It likely began during confrontations between scavengers, establishing a precedent for cooperation to acquire food. The selective advantage of cooperating groups likely explains the emergence of hunter-gatherer bands, which we can observe as far back as 1.8 million years ago. From there, human ancestors begin to display evidence of cooperative breeding, which likely co-evolved with prosocial behaviours to enable advanced cognitive abilities like understanding of shared intentionality.

This progression laid many of the foundations for the evolution of language, and it’s here that we begin to see a major transition. Language provided a medium for the development of complex societies, leading humans to become increasingly dependent on the wider collective through the division of labour — something that is particularly visible in modern developed economies. What makes humans powerful is many people working together in real-time, accumulating information about the world over many generations. The ‘major evolutionary transition’ for humans, therefore, represents the protracted change from self-sufficient individuals to a mutually-dependent collective over many generations.

Human societies are far from the only example of a major transition in evolutionary history. Current consensus is that there have been six other major transitions, including protocells, prokaryotes, eukaryotes, plastids, multicellularity and eusociality.

While each transition is unique in its own way, there has been a concerted effort to analyse them together in the hope of extracting common principles.

Transitions occur when selection rises to the group level

Consider a population consisting of several groups competing against each other. Within each group, natural selection favours traits that maximise individual fitness regardless of their effect on group as a whole. Cooperative behaviours tend to incur an additional cost, either requiring more energy or a reduced proportion of a shared benefit. We should expect, then, that cooperative behaviours cannot evolve, because acting out of self-interest tends to have a higher payoff.

Of course, this is not what we see in practice. Broadly, major evolutionary transitions are characterised by the establishment of mass cooperation with limited realised conflict, producing a new individual at a higher level of organisation. Cooperation does evolve as a stable strategy.

The evolution of cooperation in the context of major transitions has been a controversial question over the past few decades, and I will avoid wading too far into the weeds. Instead, I will lean on the emerging consensus that there exists an additional level of selection which selects for cooperative traits that are advantageous at the level of the group instead of the level of the individual. The aggregate of such traits gives the group an advantage compared to other groups in the population. Group selection does not completely overcome individual selection, however, and selection instead jostles between both levels simultaneously — what evolves in the population results from their relative strength.

“Sometimes one level prevails, resulting in a homogenous population of public good providers (when between-group selection prevails) or free-riders (when within-group selection prevails). In other cases, frequency-dependent effects cause a mix of types to coexist in the total population.” — Generalizing the core design principles for the efficacy of groups (Wilson, 2013)

The majority of us have experienced life in a company, and so competing levels of selection is intuitive. Each of us has our own interests, like getting credit, getting promoted and making more money. But, we also know that we are ultimately better off when our team and the company as a whole succeeds, because it makes our individual position more valuable. As you pay attention, you’ll notice that these dynamics are at play in any group situation, and so we contend with the competition between individual selection (what is best for us) and group selection (what is best for the group) everyday.

Looking back through evolutionary history, these two forces have been in constant tension, shaping evolution at multiple levels of individuality simultaneously.

Group selection rests on the idea that there are some outcomes that are only achievable when parties cooperate, and that those outcomes provide an evolutionary advantage to group members. It is these outcomes that get selected for — synergistic interactions between individuals leading to the emergence of an advantageous group aggregate.

“If cooperation is to evolve, non-additive, or synergistic, fitness interactions are needed. If two or more cooperating individuals achieve something that a similar number of isolated individuals cannot, the preconditions exist"” — Major evolutionary transitions (Smith & Szathmary, 1995)

When the right conditions present themselves, group selection becomes the primary evolutionary driver, and major transitions to a new level of individuality are able to occur. Groups become collectives when traits that benefit the group are selected for above selfish traits.

This pattern is visible in all prior major transitions, and once complete, the resulting organism tends to become ecologically dominant. Eusocial insects, for example, began somewhere in the evolutionary past as an individualistic species, and at some point evolved to become a collective superorganism. Eusocial superorganisms now make up more than 50% of all insect biomass on Earth. Multicellular organisms follow a similar pattern. When it works, cooperation really works.

“Selfishness beats altruism within groups. Altruistic groups beat selfish groups. Everything else is commentary.” — Rethinking the theoretical foundation of sociobiology (Wilson & Wilson, 2006)

The concept of ‘major transitions’ implies that a new level of individuality not only enables superorganisms to outcompete less cooperative species, but opens up an entirely new evolutionary state space. The difference between cooperative human societies and the next smartest primates is not just that we outcompete them for resources — we exist within a fundamentally different space of possibilities. Similarly, multicellularity opened the door to all higher-order species in the animal, plant and fungal kingdoms; a possibility space simply not available to unicellular eukaryotes.

Integrating individuals through group selection thus represents a powerful mechanism for establishing new levels of the evolutionary hierarchy. However, precisely explaining how group selection comes to dominate has proved extremely challenging. The challenge emerges because in every prior case, competing individuals have not been capable of perceiving the ultimate benefit of cooperation. Thus, it’s not enough to say that cooperation was established because superorganisms ultimately outcompete selfish individuals, because many intermediate generations had to exist between a predominantly selfish species and the evolution of a cooperative superorganism.

While we do not yet have a complete account, there is a lot to learn from studying what we do know.

Phases of evolutionary transitions

Bourke has observed that transitions tend to progress through three stages, and this provides a useful frame. First, origin — there is an initial contact point in which a group advantage is established. Second, maintenance — mechanisms develop which cement cooperation by suppressing individual incentives. Finally, transformation — a new level of individuality is consolidated with sophisticated mechanisms to produce a new unit of evolution.

1. Origin via an initial cooperative benefit

To make major transitions possible, there must be some kind of initial advantage to cooperation — a ‘first contact'. In this phase, cooperation can be established without the need for sophisticated mechanisms, producing a positive selection pressure which enables those mechanisms to develop over many generations.

It is perhaps easiest to grasp this idea in the context of human ancestors. We might imagine that at some point in our evolutionary past, there were confrontations of multiple individuals hunting the same prey, or scavenging the same food. No doubt many of these early confrontations ended in violence. At some point, however, our ancestors would have worked out that if the group cooperates, then it can be to everyone’s benefit. For example, it’s easier to hunt for large prey, or to get food from hard-to-reach places. Variation in genetics likely predisposed some individuals towards primitive forms of communication, giving them the ability to gesture or form words. Individuals with these mutations were more likely to survive in groups of others who had a similar mutation, producing a kind of group-selected advantage that could lead to cooperation becoming more common.

The evolution of multicellularity can be thought of in a similar way. Multicellularity arose many times independently, giving us some indication that there was a significant selection pressure in the ancient unicellular world. We probably cannot know for sure, but it’s likely that the initial advantage was linked to size. Imagine all organisms lined up according to size. It’s always possible for there to be a new biggest organism, and if there is an ecological niche to be filled by a new biggest organism, then it’s likely that it will be selected for. Since being bigger makes it possible to isolate from the outside world and protect genes, it seems likely that some niches could be exploited better by larger organisms.

“In other words, the direction of the selection for size change depends solely on the ecological opportunities, and there is always room at the top. When the earth was populated with nothing but single cells, selection opportunities for multicellularity must have been inexhaustible." — The origins of multicellularity (Bonner, 1998)

Multicellularity and human societies are alike in that they represent fraternal transitions, in which each individual in the higher cooperative unit is initially the same. In these cases, the initial advantage of cooperation is most likely drawn from economies of scale — combining the same abilities across multiple individuals to achieve higher efficiency. This lays the foundation for division of labour to evolve later.

Fraternal transitions are in this way distinct from egalitarian transitions, which bring together individuals with different capabilities. In such cases, the initial advantage of cooperation is found in the emergent properties of combining different capabilities, where a division of labour is automatically established.

The transition to eukaryotic cells is a characteristic example. The general consensus seems to be that eukaryotic cells began when a prokaryotic cell ingested a mitochondria. Mitochondria produce lots of energy, and this advantage could be experienced relatively ‘immediately’ via a natural division in labour. The excess energy probably fuelled more experimentation with a higher number of genes, enabling a big jump in complexity relative to prokaryotic cells through the evolution of many different kinds of cellular compartments.

“Most organisms opt for the libertarian route, going it alone. Those that cooperate make two different kinds of alliances: egalitarian and fraternal.” — Cooperators since life began (Queller, 1997)

2. Maintenance via mechanisms that suppress free-riding

So, transitions happen when selection rises to the level of the group, via an initial cooperative advantage. However, group selection never completely overcomes individual selection, and the evolutionary pressure to act as a free-rider continues to exist. In this scenario, we should expect that free-riders do very well in populations of cooperators, since they get the benefit of cooperation without paying the cost. As such, we might expect that free-riders infiltrate budding cooperative populations and eventually become dominant.

Stable populations of cooperators are able to evolve because selection acting at the group level favours the evolution of mechanisms that suppress free-riding. In simpler terms, groups evolve rewards for cooperative behaviour and punishments for selfish behaviour.

For eusocial insects, achieving superorganism status required mechanisms to overcome many potential arenas of conflict, including sex allocation, queen rearing and male rearing. It’s no surprise that conflict is found primarily in reproductive traits — each individual is within its evolutionary incentives to ensure its replication, and so overcoming the individual drive to reproduce is key to forming a new level of individuality.

Mechanisms for controlling reproductive conflict in eusocial insects primarily include kinship, coercion and constraint. For example, workers in eusocial societies are generally capable of laying unfertilised eggs. However, workers that do so are otherwise unproductive and reduce the efficiency of the colony as a whole — a natural ‘tragedy of the commons’. To overcome this, reproduction is policed both by the queen (who retains reproductive dominance) and by other workers. In honey bees, it has been predicted that without policing, roughly 54% of workers would reproduce. With policing, however, only about 0.1% of workers become reproductive. Interestingly, ‘bottom-up’ worker policing (as opposed to ‘top-down’ queen policing) is about 98% effective.

In the transition to multicellularity, one can imagine a similar problem. There are economies of scale advantages to multicellular configurations, granted, but each cell begins as an independent replicator and will be selected to reproduce. How, then, do multicellular organisms overcome this paradox? Well, it’s likely that there was variation in the temporal dynamics of collective cell division among newly multicellular individuals. Some groups likely divided closer together, and others further apart. We observe that multicellular organisms tend to synchronise their replication, and it is likely that synchronisation was selected for because it reduced the chance of individual cells proliferating at the expense of others. As this was selected for, more efficient mechanisms for facilitating synchronisation evolved as a result. Synchronised cell replication likely cemented cooperation sufficiently to enable further evolution at the group level.

In human systems, mechanisms of suppressing conflict and selfish behaviour are everywhere. We continuously create systems of rules and regulations at every scale of human interaction — within families and friend groups, all the way up to international legal systems. Such systems of rules help to overcome game theoretic incentives enough to ensure that ‘individuals’ can predictably experience the benefits of cooperation, safe in the knowledge that free-riders will be penalised. Many anthropological studies show this process in early human societies, while Elinor Ostrom’s work shows how it remains at the foundation of effective cooperation today.

3. Transformation to a new evolutionary unit

With the suppression of free-riding, the groundwork is laid for mechanisms which complete the transformation to a new level of individuality. The newly emerging superorganism moves past a point of no return, where sophisticated mechanisms ensure a stable base of mass cooperation. It’s at this point that we no longer see the parts and begin to see the new whole — in all practicality, selection among the original parts is no longer a significant evolutionary force.

In the transition from single-celled to multicellular organisms, the integrity of the budding new whole is dependent on a strong division of labour, as epitomised in the development of the soma (“body” cells) and the germ-line (“sex” cells). The vast majority of cells are confined to somatic responsibilities in this arrangement, foregoing their ability to contribute to the next generation. However, each somatic cell technically maintains a copy of the genetic material required to reproduce, and would be within its evolutionary incentives to compete to participate in the germ-line.

In order to overcome this multipolar trap, cells have evolved epigenetic mechanisms which affect how differentiated cells are able to interpret and express information stored in DNA. The presence of different epigenetic factors explains why daughter cells arising in many different tissues can re-establish the differentiated functioning of their parent cells while having the same core DNA. Without epigenetic factors, daughter cells would not develop the specialised characteristics of their parents and would instead switch to inappropriate states that follow their individual reproductive incentives.

“Without efficient transmission of epigenetic information, the component cells of new multicellular organisms would have switched to inappropriate states that would have compromised the success of the individual as a whole. Epigenetic inheritance is thus one of the reasons why multicellular plants and animals retained their coherence in spite of the turnover of their component cells.” — The evolution of information in the major transitions (Jablonka & Lamb, 2006)

Over time, epigenetic information inherited by differentiated cells consolidates the division of labour. Differentiated cells can’t participate in the germ-line, because it would require erasing all the accumulated epigenetic information that enables their differentiation. Epigenetic factors thus act as mechanisms for consolidating a new level of individuality, ensuring that differentiated cells are largely only capable of synergistic actions that maintain group welfare — prior individuals move past a point of no return.

In eusocial insects, we saw that conflict resolution mechanisms like policing probably acted as intermediate mechanisms to facilitate cooperation. What we see in fully evolved eusocial society is a kind of caste system, composed of some reproductive and some non-reproductive individuals, continuing the pattern of extreme divisions of labour. As with multicellular organisms, the caste system in partnership with conflict suppression mechanisms largely ensures that individuals are, in all practicality, no longer capable of acting out of the group interest.

For human societies, we are still arguably undergoing the transformation phase. We’ve never been more dependent on the wider collective to live our lives, especially in the world’s developed economies. More complex economies introduce more division of labour — information becomes increasingly distributed and each individual becomes more specialised. In turn, we each become progressively more reliant on the wider economy to produce the vast majority of the things we use everyday.

One way to look at this is to ask yourself how much of your current daily lifestyle could be maintained if it was just you alone with no contact with society. For most of us, this should reveal just how dependent we are on the accumulation of knowledge, technology and social structure over generations. Here lies the transformation with respect to primate and early human societies — it is no longer practical for us to go backwards.

New mechanisms for transmitting information

Looking at the transitions through a sequence of stages, we continually hit on the concept of information and how it is transmitted between individuals. Perhaps the most interesting aspect of transitions is that each time, a new level of individuality is correlated with the emergence of a new medium for storing and transmitting information.

Prokaryotes are the first time in evolutionary history that we see what we commonly refer to as ‘cells’ evolve. Prokaryotic cells established symbiosis among networks of molecules to produce a new individual at a higher level of organisation. In order to replicate themselves as new wholes, prokaryotes had to discover a mechanism to send information about how to reconstruct themselves and their internal networks into the future.

The mechanism they discovered was genetic code (RNA), together with ribosomes to translate that code into proteins. Where before inheritance was iconic, genetic code made inheritance symbolic. Symbolic code was selected for because code can enable arbitrarily complex molecules to be encoded by a small alphabet of components. In doing so, the transmission of information moved from limited heredity to unlimited heredity with variation, unlocking a new state space of possible environmental adaptations.

Prokaryotes laid the foundation for eukaryotes, which brought multiple cells together to form a new kind of meta-cell with functionally distinct compartments. With the added complexity of replicating a meta-cell, a new mechanism of information transmission had to evolve. This came in the form of DNA. In prokaryotic cells, RNA does the work of both storing hereditary information and enabling/regulating the production of proteins. DNA evolved from RNA to establish a division of labour, in which DNA succeeded in storing information more effectively as a more stable molecule, while RNA primarily maintained its role of enabling protein production. In doing so, the process of transcription (“reading” DNA) became separated from translation (converting DNA into proteins) and DNA/RNA each became better in their respective domain.

To understand the role of transmitting information, consider evolution as a learning process in an environmental context. As time passes, variation and selection determine adaptations that are considered ‘fit’ in the environment. Information is a way to store the results of this process. To ensure that they maintain the evolutionary advantage they have acquired through selection over generations, organisms must find a way to store and transmit information about what works between generations. Information moves from a sender (the “parent”) to a receiver (the “child”) who uses it to reconstruct an adapted state, with a little variation.

“The transmission of information between generations, whether through reproduction or through communication, requires that a receiver interprets (or processes) an informational input from a sender who was previously a receiver. When the processing by the receiver leads to the reconstruction of the same or a slightly modified organization-state as that in the sender, and when variations in the sender’s state lead to similar variations in the receiver, we can talk about the hereditary transmission of information.” — The evolution of information in the major transitions (Jablonka & Lamb, 2006)

Notice that the transition to prokaryotic cells and eukaryotic cells aggregates information previously belonging to lower-level individuals. Each individual alone acquires that information over a long evolutionary history. If either individual alone wanted to develop characteristics of the other, they would have to ‘invent’ those characteristics by themselves. As a cooperative organism, however, each benefits from merging their evolutionary histories together.

This becomes important because new evolutionary adaptations have to be constructed from combinations of components that already exist. To get to complex adaptations, like complex vision, you first need many layers of underlying capabilities (light sensors, depth perception etc). Only when you have the underlying capabilities can you ‘unlock’ complex vision by combining them together. As prokaryotic and eukaryotic cells formed by merging individuals together, there were more underlying capabilities available to try out more complex combinations.

Consider, then, that there is an abstract combinatorial search space of all possible adaptations, where each one is reachable through certain combinations. The mechanism of evolution is to search through that space. For organisms to develop adaptations of greater complexity, they have to be able to build upon the information gained from previous generations. Of course, the number of possible combinations increases exponentially, and the search space quickly becomes very large.

"…even the simplest biological objects – the polymeric sequences of proteins and RNA - postulated to play a prominent role in the origin of life - are still combinatorially complex, existing within an astronomically large space of possible molecules that are just as physically plausible, but have not been selected to exist" — Assembly theory explains and quantifies the emergence of selection and evolution (Cronin & Walker, 2022)

Part of the ultimate role of RNA and DNA, then, was to merge separate information into mutual information. As symbolic languages, they achieved this because they compress a lot of information into a small alphabet of components. As we look out into the world now, much can be explained with the combinations of just four letters.

The compression becomes important for two reasons. First of all, compression enables the *regularities *to be found between information coming from multiple sources. By identifying regularities and discarding what’s not important, compression increases mutual information to enable further cooperation. In the case of RNA and DNA, this likely meant finding the behaviours/traits that were mutually useful at the group level, and reinforcing them. Through this increase in mutual information, “cooperation“, each individual becomes able to externalise information processing to the higher collective entity (“division of labour”).

Secondly, compression makes the language more generalised. Genetic base pairings are a generalised language for describing any protein and any combination of proteins, and are thus capable of describing a huge range of possible organisms. This generality makes the ongoing process of evolutionary search more efficient, and increases the likelihood of discovering useful combinations compared to other methods. Essentially, more of the total search space becomes available — the search space available to RNA was much larger than direct molecular replication, and the search space available to DNA was significantly larger again.

“Further evolution generalizes the system so that a hyperastronomically vast combinatorial space can be sampled by evolutionary search.” — Toward major evolutionary transitions theory 2.0 (Szathmary, 2015)

As we move forwards in evolutionary time, transitions are characterised by the emergence of mechanisms that transmit information with increasing speed and level of abstraction.

Epigenetics builds on the DNA paradigm by enabling cells to inherit state (“context”). Simply inheriting code is limited in its potential because all inheritors inherit the same thing. Epigenetics enables many different types of cells to inherit the same genetic information, while varying how they use that information. There is a slight distinction here from DNA, as it enables characteristics acquired during a lifetime to be passed onto the next generation.

Bees, meanwhile, are able to communicate with other bees by using a waggle-dance to indicate the location of a food source. Essentially, this involves walking forwards while waggling at an angle relative to the position of the sun, using the hive as a medium. The angle represents the location of a food source, while the intensity of the waggle represents the distance. See this video for a quick walkthrough.

Something different is happening here compared to prior transitions — rather than transmitting information between generations, information is being transmitted socially within generations. Social transmission aggregates information arising from many bees, producing a kind of externalised map of food sources.

In a way, human language did for information transmission within generations what genetic code did for transmission between generations. Bees are only capable of communicating about the location of food. Symbolic language, on the other hand, generalises representation of information and enables communication of arbitrarily complex concepts. As with genetics, language achieves this by compressing information via a small alphabet of components that can be recursively composed together. Genetics and language are therefore similar in that they are both generalised mechanisms for transmitting information from a sender to a receiver. The difference is the timescale — memes travel faster than genes — and the level of abstraction.

The pattern here seems to be one of continuous aggregation, compression and generalisation, spiralling through levels of abstraction at faster and faster speeds:

• Aggregation — individuals come together and ‘share’ information, merging their evolutionary histories to produce the possibility of a collective aggregate that enables newly adaptive higher-order combinations.

• Compression — cooperation coevolves with new mechanisms (“languages”) for storing and transmitting aggregated information, operating through information compression. Through aggregation and compression, individuals are increasingly able to externalise information processing to the higher-order collective (“division of labour”).

• Generalisation — languages become more generalised and more capable of combining what is known to reach higher levels of complexity. This opens up a new dimension of higher-order adaptations not available to lower levels, providing a selection pressure that consolidates a new layer of organisation.

• The cycle repeats — at the new level of organisation, there becomes a selection pressure for re-aggregation.

Conclusion

So, what can we learn from our journey into biological esoterica?

Well, the first thing to realise is that there is a strong evolutionary precedent for deeply cooperative integration of previously uncooperative units. “Collective intelligence” has been continuously selected for at many levels of the biological hierarchy, where extreme cooperation between components with partial information is a rule, not an exception.

Second, each transition is similar in critical ways, progressing through phases of origin, maintenance and transformation. Shared information is core to new levels of organisation, and newly cooperative individuals coevolve with new mechanisms to aggregate, compress and generalise it for the collective benefit. Over time, there is a selection pressure for higher levels of abstraction and increasing speed of transmission.

Third, the consolidation of higher levels of organisation opens up entirely new evolutionary possibilities that simply were not accessible at the lower levels. The emergent characteristics of the higher level are not predictable from the viewpoint of lower levels.

More broadly, major transitions suggest an important lens for looking at the evolutionary process as it pertains to social systems. When we think of evolution, we tend to think ‘survival of the fittest’. The connotation is to see evolution purely as a mechanism for ruthless, zero-sum competition in which cooperation must be a glitch. Of course, it is ruthlessly competitive at each level — lions and hyenas are forever locked in a vicious blood feud until one species no longer exists. But we need only zoom in, to look back in time, to see the symphony of cooperation between individuals at lower levels combining to give meaning to ‘lion' and ‘hyena’. With a better lens, it is really cooperation all the way down.

While institutions have solved for cooperation at many scales, it is hard not to feel as though they are stuck in an individualistic paradigm. A glass ceiling seems to separate us and higher levels of organisation. It’s here that multipolar traps arise, from each following their individualistic incentives at the expense of the collective good, without understanding the possibilities available when everyone cooperates. Well, the insight from major evolutionary transitions is not only that there is an evolutionary precedent for overcoming these traps that has been continuously selected for; but that what ultimately comes of the integration is so collectively powerful and so far out of the existing space of possibilities as to be a new level of the evolutionary hierarchy.

As we look to overcome the multipolar challenges we face, there is at least one thing that distinguishes a future transition from those past. This time, we are capable of understanding at least the medium-term benefits of extreme planetary cooperation — we can project into the future and conceive of a world in which everyone cooperates. Rather than waiting on millions of years of naturally directed evolution, we can consciously engineer this world into being.

If you found this essay valuable, please consider collecting it as an NFT. Think of it like funding research, and enabling me to do more of it. Like buying a book in reverse, after you decided it was already worth it. If you do, know that it is deeply appreciated.

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