Major evolutionary innovations arise abruptly. Novel body forms appeared suddenly, the Cambrian explosion ¹ . Seed-bearing plants spread across the earth almost instantaneously, Darwin’s abominable mystery ² . Humans spoke, made symbolic art and dominated the world.

A review ³ of Why Only Us: Language and Evolution ⁴ emphasizes the recurring controversy over evolutionary innovation:

The argument for slow evolution appeals to intuition. Such complexity cannot evolve suddenly. Evolution is an intrinsically slow process.

Against the intuitive argument for the slow evolution of language, the evidence suggests that: ³

My theme concerns the general understanding of evolutionary process. How surprising is abrupt evolutionary innovation? How do we understand what ‘abrupt’ means? To answer those questions, we must understand the nature of time in relation to generative process.

Think about cancer. A tumor evolves by accumulating changes ⁵ . The initial changes may arise before one notices any sign of tumor or disease. Eventually, the tumor acquires novel traits that give it an uncontrolled growth advantage. Overwhelming disease soon follows.

Without modern technology, one sees tumors as arising abruptly. That suddenness comes from the growth rate of tumors, shaped by the history of evolutionary innovations. Synergism between growth and innovation sets the tempo at which we perceive novelty.

Growth by itself has a natural tempo that causes things to appear suddenly. In uncontrolled growth, an initial input size is multiplied by a growth factor, producing a bigger output size. The output then becomes the input for another round of recursive growth.

A recursive doubling in size produces a series of 1, 2, 4, 8, 16, 32, …, with a size of 2 ⁿ at the nth time step. A tumor typically must have billions of cells before it is noticed. To grow from one cell to a noticeable size of 30 billion cells, a recursively growing tumor must pass through 35 doubling periods.

After just 5 more rounds of doubling growth, the tumor will be 32 times larger than the size at first detection. The time is short from being noticed to being overwhelmingly dominant.

Seemingly abrupt appearance is a property of recursive growth. Put another way, the natural timescale of growth is explosive, whereas the natural timescale of our perception seems to be relatively steady. The perception of appearance by growth tends to be abrupt.

I invoked uncontrolled growth. But where does such growth come from? What is the nature of innovation that increases growth?

We may never know the answer for language. At present, we do not know the answer for tumors, even though tumors happen all the time right under our own skin. But perhaps the puzzle of evolutionary innovation in tumors will be solved one day ⁶ .

Deeper understanding of evolutionary innovation in tumors may provide insight into what it takes, more generally, for the origin and spread of seed-bearing plants, of new body forms and of language. So I continue to discuss tumors. The abruptness of cancer is a model of evolutionary innovation.

We know that an aggressive tumor has acquired many evolutionary changes when compared to its normal ancestral tissue. Did most of those cancerous changes happen abruptly around the transition to perceptible aggressiveness? Or did many evolutionary changes accumulate slowly, over a long period, starting well before noticeable cancer?

We do not know exactly. But we can say what the likely processes are for evolutionary change in cancer, what the timescales are for those processes, and how the different processes interact. We can draft a rough solution to the puzzle of evolutionary innovation in cancer.

I step through the key evolutionary processes and their consequences for the timescale of cancer. At first, the puzzle of cancer may seem rather distant from the puzzle of language. However, consider two questions.

Is language an example of the known processes of evolutionary innovation? Or does the puzzle of language require a unique solution? We can discuss those questions in a more informed way after briefly considering cancer.

A successful tumor gains the ability to break through tissue barriers, survive in novel environments, escape detection by immunity, ignore the normal checks on growth, alter its metabolic pathways for energy production, send signals that call other tissues to remodel the tumor’s environment, and many other novel traits ⁵ .

Innovation proceeds by the layering of new changes on top of the recent changes. Each particular change creates new context, favoring a new set of changes. Three evolutionary processes of cancer likely apply to many cases of evolutionary innovation.

First, an advantageous change enhances growth. Steady growth leads to the perception of abrupt origin. However, a single change by itself does not transform normal tissue into a cancer. Evolutionary innovation requires multiple changes. The early changes accumulate imperceptibly.

Second, each change alters the context for future innovation. At some point, a single subsequent change could ignite growth. However, current evidence suggests a complex array of interacting changes that arise and spread over different timescales ⁶ . Advances in biological technology will eventually resolve the timing and the role of particular changes.

Third, as evolutionary change alters context, new pressures favor novel kinds of innovation. Sometimes, the novelty is itself a new generative mechanism that enhances the speed at which further novelty can be created. Or the novelty changes the way in which additional novelty integrates into the evolving population of cancerous cells.

The changing processes of discovery and integration in cancer likely arise in other evolutionary innovations. The following paragraphs describe a few examples for cancer. I then conclude by discussing aspects of language in relation to general properties of evolutionary innovation.

Suppose that an innovative trait would be favored, but it arises only one time per million cellular divisions. A tissue typically has far more than one million cells. So the trait arises many times in one round of cell division. But only a few rare cells have the novel trait.

The novel trait creates a context that would favor an additional innovation. Because only a few cells have the novel trait, it may take a very long time before the second innovation follows. However, if the initial trait spreads, then many cells would have the trait. The time before the second innovation would then be very short, because of the large size of the target population.

Rapid spread of the first trait may happen because it has a growth advantage and reproductively outcompetes other cells. Or the trait may spread if it produces a signal that transforms other cells to express the same trait. Much of cellular behavior arises by intercellular signalling. Transformation by novel signalling is a key aspect of evolutionary innovation in cancer progression ⁵ .

The discovery of a new trait is often discussed in terms of genetic mutation. Mutation couples two aspects in one stroke: the creation of novelty and the transmission of that novelty to future generations. However, one may have to wait a very long time for mutation to create a particular innovation.

Alternatively, the novel trait may first appear by cellular adjustment to a novel environment ⁷ . Initially, only a few cells may adjust to express the newly favored trait. Those cells gain an advantage, possibly transmitting to their descendants the tendency to adjust in the appropriate way. That process can favor rapid evolution of a novel trait that first appears by adjustment, or by learning, rather than by mutation ⁸ .

An environmental challenge may require two novel traits to arise simultaneously. For example, a novel cellular signal may require other cells to express a novel ability to respond to the signal. How do jointly synergistic traits evolve, if neither trait alone provides value ^{9, 10} ?

If some cells and their descendants remain spatially associated over time, then the group evolves almost like a single unit. The origin of the signal, initially by chance, strongly favors the recipient response. Signal and response may arise by one mutation then another. However, it may be a long time before two rare mutations arise.

Alternatively, different cells with the same genetics inevitably have a certain amount of randomness in the traits that they express. A population of cells that, by chance, expresses the right combination of novel signal and response traits will gain a growth advantage.

Any genetic tendency to express the right trait combination will increase. Over time, the beneficial combination evolves to be expressed more frequently ¹¹ . The process assimilates an initial tendency for random expression of traits into an increased genetic tendency to express the traits. Synergistic trait combinations can evolve relatively rapidly by this process when compared to the slow pace of origin by sequential mutations.

These ideas about innovation follow from classical evolutionary theory. We do not yet know exactly which aspects apply to particular cancers. However, technological advances will soon provide additional insight.

My discussion of evolutionary innovation and timescale for cancer applies broadly to any evolutionary system. Recursion unifies the conceptual frame.

First, natural selection recursively drives the spread of innovations. Given an input population, selection enhances the frequency of beneficial traits, producing a new output population. The output then becomes the input for another round of selection. An innovation with constant benefit increases by recursive multiplication, transforming constancy of benefit into explosive increase.

Second, an innovation can act by enhancing the rate at which additional new innovations are discovered. A discovery mechanism increases by selection when it associates with the beneficial innovations that it creates ¹² . Discovery applies recursively to each new generation.

Third, the trait of an individual may itself be a recursive system. Our bodies develop from the single-cell union of egg and sperm into approximately 30 trillion cells. Genetics does not specify the exact form of the adult. Instead, evolutionary history has built a developmental language applied recursively to the birth cell ¹³ .

New evolutionary innovations arise by modification of the recursive developmental language. The encoding of traits in a recursive developmental language accelerates the discovery of innovations.

In addition to the development of body form, other traits are also encoded by rules applied recursively. For example, our immune system combines recursive mechanisms to discover innovations and recursive mechanisms to select and enhance beneficial innovations ¹⁴ . These recursive processes allow rapid discovery and expansion of novel defenses against infection.

This hierarchy of recursive processes provides the framework for understanding evolutionary innovation. The origin of human language falls naturally within this general evolutionary framework. However, the consequences of human language add a new process of innovation.

Before language, all evolutionary change had to follow a trajectory through the lineage of genes, a sufficiently stable molecular encoding of information to carry forward innovations.

Human language created a parallel system to encode and transmit information. That parallel system follows the same general principles of recursion and innovation. However, the distinction between encoding by language or by molecules influences the recursive hierarchy and the consequences for innovation. The parallel systems of language and molecules interact, although the degree of coupling is controversial.

Language, as an innovation to the process of innovation, expands the recursive hierarchy and accelerates further innovation ^{15, 16} . Evolutionary history has always been an evolving recursive hierarchy ¹⁴ . When an evolutionary innovation alters the recursive hierarchy in a way that accelerates further innovation, then abrupt change often follows.

Cancer, development and language differ. But they share the ways in which interacting recursive processes alter the timescale of innovation.