Implications of a machine economy

Emergence as a solution to overengineering

More is better. Our brains seem hardwired to it. Maybe it has to do with laziness, or perhaps just comfort. But we humans tend to overengineer everything, from our almost empty or often unused cars, to our ridiculously overpowered smartphones and laptops, which we use for Facebook and Candy Crush Saga. There are many examples, but the point is: a lot of our stuff is overspec’d and underutilized. A solution is emergence: simple building blocks that form a more complex whole.

From one size fits all to granularity

One of the reasons for overengineering and overcapacity is that we want one thing that tends to all our needs, all of the time. But what if we left this paradigm, and instead look at utility differently? Cars for example: you buy a car that is big/powerful enough to go on holiday with. But do you need a car like that all year round? Or the processing power of your computer: most people don’t need that most of the time. Would you be happy with a less powerful (cheaper) computer if you had access to the power and speed when you really need it?

Is there a different way to have something fitting for each unique task or goal? Could we assemble small individual parts that add up to just enough for the task at hand? Or even better, could ‘it’ assemble itself automatically, without us worrying about it? That would be the ultimate utility, from an economic perspective and from a laziness perspective. And the best thing is: the concept already exists, and has been tried and tested throughout history.

Emergence: Stupid things become smart together

Emergence is a beautiful concept where simple individuals or things work together and the result is a smart system. Simple building blocks put together can make a more complex whole. Aristotle once said: “The whole is more than the sum of its parts.” Emergence takes this even further – the whole is not just more, but it can also be different.

“At each level of complexity entirely new properties appear. Psychology is not applied biology, nor is biology applied chemistry. We can now see that the whole becomes not merely more, but very different from the sum of its parts.” 1

Anderson, “More Is Different”, 393-396

Emergence is when simple systems governed by simple rules give rise to complex phenomena on a larger scale. This video from Kurzgesagt explains emergence quite well in an entertaining way.

Emergence in nature

Some ants, honeybees, termites and other insects do not have a central master mind or manager but are very successful at gathering food, repair the nest, care for eggs and defend themselves. The individuals in the colony are not trying to solve the bigger problems. They just do their simple task. As the Kurzgesagt video explains they have divided up the tasks into smaller pieces. Ingeniously the system can also adapt to changing circumstances without steering from central headquarters. In the example the simple rule for task switching is based on interaction rate with others. It is a self-regulating ecosystem.

Emergence – basis for Artificial Neural Network

The ant colony has the same basic principle as Artificial Neural Networks. It is a network of individual, interconnected, simple units that compute simple functions on data. By using distributed parallel processing of simple units you find complex features in data. The units don’t know beforehand what they will find but together they can recognize high-level concepts in data. Just like our neurons don’t know what we are looking at, but our brain puts the different perceptions together to form an image.

Emergence in a machine ecosystem

In a machine-to-machine economy many simple machines can coöperate to give collective complexity. You can give a machine a simple task and when acting together as a group get an intelligent or complex ecosystem as a result. Fire ants for instance can link their bodies together to build rafts and stay afloat for days during floods. They can also make quite complex constructions like bridges, ladders and walls by cooperating this way.

Fire ants cluster in water | User:Junglecat on Wikipedia (CC BY-SA 3.0)
Fire ants are know to cluster together after a heavy rain, forming a larger floating construction.

Similarly, big machines do not have to be designed with one purpose in mind. It can be made by many smaller building blocks – just like Lego or Mecano. Depending on how you put the building blocks together your machine could easily change function.

Machines can be made of smaller building blocks but also managed by simple principles. Emergence has similarities to smart swarming, where a simple rule can give a complex movement or behaviour. See previous post Algorithms inspired by swarm behaviour for examples from nature or watch TEDx talk Complexity of Emergent Systems for some real life examples of emergent behaviour.

The emergency of emergence

I’m an economist with a heart for nature and biodiversity. As such I say it’s 5 past 12 to do something for ecology and the world. We are drawing way too much resources from the earth. On top of that we are not paying everyone their fair share for their contribution. This is not a sustainable situation. Right now we still have the wealth to change the system into something better, without much discomfort. Therefore I urge anyone who designs any solution to look into emergent behaviour as a solution to your specific problem. Get more utility from less. We’ve been living above our means and it is time to rebalance that.

Inspiration for Hackathon

This post is part of a series providing inspiration from nature for participants at the Blockchaingers Hackathon, specifically for the Machine Economy track. Read more about:

About the author

Hanna van Sambeek

Economist with a passion for renewable energy, looking for the next challenge. My goal in life is to leave the world behind a lot cleaner, healthier and fairer than I found it.

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Implications of a machine economy