Implications of a machine economy

Biomimicry: information and the Machine Economy

The Machine Economy track on the world’s largest blockchain Hackathon challenges you to go way beyond the current paradigm. But how do you rethink a future ecosystem? Nature could be inspiration. It’s been scrumming and iterating its ecosystems for 3.8 billion years. There’s some interesting concepts to be learned from it, through Biomimicry.


Biomimicry means learning from nature. The term comes from the Greek words bios, meaning life, and mimesis, meaning to imitate.

Biomimicry is an approach to innovation that seeks sustainable solutions to human challenges by emulating nature’s time-tested patterns and strategies.

First life occurred on earth 3.8 billions year ago. Nature has had billions of years of research, developments and failures to design the smart ecosystems we live in today. We would be foolish not to use these examples.

Importance of information in nature

Humans take a very different approach than nature to problem solving and creating things. In engineering processes (creation by humans) we use vast amounts of energy and a lot of resources (material/matter). Only when making really big things (several meters up to a kilometre in size) do we pay more attention to structure, but most of technology is done on a smaller scale.  In natural processes on the other hand information and structure are the two main inputs. Energy and materials are used very scarcely, see graph below.

Biomicry/Biomimetics graph Julien Vincent
Graph comparing resource usage in Technology vs. Biology on various scales. Based on Vincent, J.F.V.; Bogatyreva, O.A.; Bogatyrev, N.R. Biomimetics: Its practice and theory. J. R. Soc. Interface 2006, 3, 471–482.

Some examples from nature are birds, moths, termites and the reoccurring hexagon:

  • Birds have evolved to maximum bone strength and stiffness with minimum bone mass and volume. This is partially thanks to the minerals and proteins they are made of, but also finding an optimum structure. Bird bones are hollow with minimal matter in exactly the right spot. This smart utilization of matter makes them strong yet lightweight; perfect for flying.
    Bird bone
    The inside of a birdbone only has material where it has a direct function, in order to save weight. Source: Wikimedia
  • Some male moths are saving energy and material by not having a mouth. The main task they have in their short adult life is finding a partner and reproducing. There is time for eating thus having a mouth is a waste of energy and resources.
  • The Australian compass termite build mounds that are oriented optimally towards the sun to not be over heated in the day but still catch enough warming rays in the morning and evening. Furthermore, they adapt to local environmental conditions (local information) by taking long-term wind speed and shade into account.
  • Nature has found that hexagonal structures, sometimes comprised of tetrahedral elements are the most efficient for maximal strength  with minimal material. It is used for example by plants, turtles and bees.

Information today

Think about that for a moment: information & structure versus energy & material. The problems we have now with climate change, waste, air quality, water quality and much more comes from an over exploitation of energy and (natural) resources. What if we could be better by emulating nature’s thriftiness?

Current data models can be seen as both wasteful and inadequate at the same time. There is already an ocean of information out there in the form of data. But it is currently vastly underutilized, because it is not easily available. The Data Marketplace initiative from the IOTA Foundation is a great example of trying to make all the worlds data available for anyone and anything.

The goal is to enable a truly decentralized data marketplace to open up the data silos that currently keep data limited to the control of a few entities. Data is one of the most imperative ingredients in the machine economy and the connected world.


Big data or bloated data?

The big data models used today are often too big and too small at the same time. While they can have a huge amount of data that needs a data center to process, it might still have too little relevant data to make the right decisions. The decentralized Data Marketplace can become an important player in creation of and accessibility to relevant (local) data. Any sensor can be placed everywhere and data collected can be bought easily by citizens or machines.

Information in a machine economy

Are you participating in the Blockchaingers Hackathon? Especially the Machine to Machine Economy track? Or are you working on some other innovative project involving data ecosystems and algorithms? Take a different approach and learn from nature!

How would your machine use information in a machine economy? What is relevant data, or what do you think is relevant regardless of what you can find right now? Your idea might be an incentive for others to create highly localized data. Localized data could be relevant for example for drones: will you send your drone out if it rains? But just because it rains on one side of town, doesn’t mean your drone can’t fly on the other side of town.

From big data to relevant data

Relevant data is vital in a machine economy. An efficient decentralized economy cannot rely on heavy computing power and big data. The machine’s algorithms need to be as lightweight as possible to accommodate the scarce resources of IoT-devices. Can you make an algorithm that is lightweight but also strong? Inspired by bird bones that took away irrelevant bone/irrelevant information? Or by smart swarming, where the whole swarm moves as one, but each actor only responds to its closest neighbor?

I challenge you to push the boundaries on the information sharing possibilities of Distributed Ledger Technology.

Good luck!

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