Emergent Complexity and its Consequences

Conway's game of life has been around since the 1970s – it's a simple grid that looks like a sheet of graph paper, where each cell can either have a black dot or nothing. To play the game, you start by drawing any pattern onto the grid at random, and then according to specific rules, every cell in the grid changes color according to how many neighboring cells are colored. For example, if a cell is surrounded entirely by other colored dots (eight neighboring cells), it will be colored in the next turn, whereas if there's only one neighbor or none, it will stay uncolored.

With these simple principles, over time the game of life becomes incredibly complex. You'd expect the grid to quickly become a jumbled mess, but this never happens. Instead, patterns emerge which start to resemble natural processes like cellular division or animal reproduction – a concept known as 'self-organisation' in physics.

This is not an isolated example of emergent complexity at work; it's just one example within our universe that we've observed and can simulate with relative ease. When you consider the universe as a system, assuming a starting point exists–like Conway's grid, which was randomly drawn–the same concept applies.

Throughout its history, the universe has undergone a fundamental and continual change from simplicity to complexity. The universe began in a single point roughly 14 billion years ago, and over billions of years it grew into what we see today: an incredible array of complex and diverse structures from stars and planets to galaxies and our own bodies. This is the mechanism of growing complexity.

A single event such as a tree falling into a forest can lead to multiple cascading reactions. This event creates shockwaves through the environment and causes immediate physical impacts like sound waves and ground impact. As time passes, these effects continue to evolve. The fallen tree begins to decompose, which provides prime conditions for detritivores—organisms that feed on dead plants and animals—and these detritivores break down the wood into nutrient-rich soil. The nutrient-rich soil then supports other microorganisms such as fungi and plants to grow. The process of decomposition creates oxygen and food for these organisms; this then goes on to support more complex systems like the animals that consume them. This chain continues with growing complexity.

This process is directional, not random. Each new event or interaction creates more possibilities than existed before. This can be best described as a tree splitting into two branches, where each branch then multiplies potential outcomes again. Since each event must cause at least one outcome, the number of outcomes must stay the same or in practice, grow.

The mechanism of growing complexity is not just theoretical; it's observable in the history of our universe. From simple systems like chemical reactions that led to life, to complex systems such as those we see today – whether they are ecological, social or economic – they all follow this pattern.

The early universe was incredibly simple. However, it's clear that since its inception, the universe has evolved into something complex. This evolution began with fundamental particles that formed in a hot, dense state roughly 14 billion years ago when expansion started. These particles then combined to form protons and neutrons, before these were bound together to form atoms – mainly hydrogen. The complexity of the universe grew further as these atoms fused to create heavier elements enabling more complex interactions. Atoms bonded together to form molecules which became – again – increasingly complex.

From here, evolution began, and organisms started self-replicating with increasing complexity. This process continued creating the complex ecosystems we see today.

This mechanism is also observable in human revolutions – from the invention of the wheel to modern technological advancements. As a result of the wheel, trade and transportation was enabled, leading to the development of writing systems that allowed for recording information and tracking trade. With more information available, it's easier to share knowledge and individual advancements in technology can be made.

As the snowball of knowledge and technology grew, the complexity of human societies grew with them. This led to further technological developments such as industrial machinery – allowing us to build more complex systems like computers, the internet, and eventually AI.

Complex systems by definition consist of many smaller interacting components. These interactions create information flow between components, which leads to systems storing and processing information. This storage of knowledge enables adaptive reactions to inputs – whether this be a response to its environment or internal changes.

The same properties that define complex systems also define intelligence. Our brains and all other occurring intelligence are, in fact, complex systems. We think about intelligence backwards, seeing these complex behaviors as evidence of it. But really, this is what complexity does naturally: Intelligence isn't a special one-time occurrence – rather, it's what occurs when systems become complex enough to store, process, and react to information.

This mechanism is not unique to individual organisms; examples can be seen at different scales such as ant colonies which exhibit intelligence through communication and adaptive reaction, or neural networks that allow computers to learn. It also applies to more abstract concepts like markets, where the emergent behavior of agents produces complex, intelligent outcomes.

Intelligence is a property of complexity – not something unique to human brains or individual organisms.

Often, we think of ourselves as an external agent observing the environment and other animals. In actuality, we are as much a product of this process as any other animal. Our intelligence isn't unique – it's a manifestation of complexity reaching a certain threshold.

In this sense, our drive to innovate and create is not a unique phenomenon but rather a natural consequence of complexity simply cascading into more complexity. We are both the product of emergent complexity and an agent of its growth.

Throughout history we see intelligent animals dominate their surroundings. Intelligence is an evolutionary advantage. Evolution is a "complexity arms race" where more complex organisms can do more, so they can evolve even further. Humans are simply the current peak of biological intelligence.

There exists a theoretical threshold beyond which evolved intelligence becomes so complex that it can drive complexity artificially, at a higher rate than biological evolution. While artificial intelligence isn't yet more complex than biological intelligence, it is becoming more complex faster than biological intelligence – and this rate will only increase in the future due to its compounding nature.

Humans may always be the peak of biological intelligence, but we will soon be surpassed by AI of our own creation – this is inevitable.

The aim of this essay was to convince the reader (you) to adopt the following beliefs:

1. The universe – our reality – is for whatever reason, driven towards increasing complexity
2. Evolution as a phenomenon is simply a manifestation of this universal law
3. Intelligence is a property of complexity, and all complex systems are intelligent in some capacity
4. We will create artificial general intelligence, and it will be more complex than biological intelligence

I hope you now believe these things.