We live in a world built on software, but what if the natural world itself runs on software-like principles? That’s the idea at the heart of "Software in the Natural World: A Computational Approach to Hierarchical Emergence". The authors argue that many systems in nature - your brain, ecosystems, even particle dynamics - can be thought of as running their own “software,” complete with abstractions and layers, just like the operating systems on your devices.

This isn’t just a metaphor. It’s a powerful way to understand how complex systems work and why they break down.

What Does It Mean to Call Nature “Software”?

Think about software for a second. You can run the same app on different hardware - your phone, your laptop, a server in the cloud - because software doesn’t care about the specifics of the machine. What matters is the program.

The authors argue that in many natural systems, higher-level processes are similarly independent of the lower-level “hardware.” Take your brain, for example. Thoughts aren’t determined by the exact quantum states of atoms in your neurons. They’re an emergent property of the neural network as a whole, independent of the microscopic details.

This independence is what the authors call causal closure. A system is causally closed when everything that matters to it happens at its own level. Your thoughts influence your decisions without needing to involve the subatomic particles in your brain.

Why Layers Matter

This idea of causal closure gives us a way to break down the overwhelming complexity of the world. Instead of getting lost in the chaos of microscopic interactions, we can focus on the layers where the action really happens.

For example:

Macroeconomics doesn’t care about individual transactions; it looks at aggregate behaviors like inflation or unemployment.
Weather forecasting doesn’t simulate every air molecule; it models high-level patterns like pressure systems and jet streams.

The magic happens in the middle. Layers emerge, each with their own rules, and those rules are surprisingly self-contained. It’s like peeling back the layers of an onion: each layer is its own little world, complete with its own logic and dynamics.

How to Spot the Layers

The paper provides a method for identifying these layers, using three kinds of “closure”:

Informational Closure: Can the system predict itself without needing information from lower layers?
Causal Closure: Does everything that matters to the system happen within its own layer?
Computational Closure: Can we describe the system as a kind of abstract machine, with inputs and outputs at its own level?

When a system satisfies all three, it’s like discovering that nature has written a piece of software to run that layer.

Why This Changes Everything

This way of thinking about the world has huge implications:

Simplification: If we know which layers are causally closed, we can simulate them without worrying about the details below. For example, weather models can focus on pressure systems without worrying about individual air molecules.
Control: Knowing the “software layer” of a system tells us where to intervene. Want to change a person’s behavior? Focus on their thoughts, not the atomic structure of their brain.
Discovery: This approach helps us find new emergent layers, revealing hidden patterns in complex systems.

What’s Next?

The idea that nature is “running software” isn’t just a poetic metaphor; it’s a practical framework. It can help scientists, engineers, and thinkers across disciplines understand and manipulate complex systems.

We already know software runs the modern world. This paper suggests it might run the natural world too. The more we understand it, the better equipped we are to work with - and not against - the hidden layers of complexity all around us.

For more details, you can read the original paper here: Software in the Natural World: A Computational Approach to Hierarchical Emergence.