How to Avoid Micromanagement with Swarm Intelligence (Step-By-Step Guide )

Have you ever wondered how a flock of birds interact so brilliantly? Or how ants and termites build fascinating colonies?

More importantly, have you ever wondered how your organization could mimic a flock of birds or an ant colony to create a thriving organization without having to micro-manage every little detail?

TABLE OF CONTENTS

1. What is Swarm Intelligence?
2. Why Swarm Intelligence matters to your team
How I Swarm the classroom (a case study)
3. How to use Swarm Intelligence to make your team strive (Step-by-step guide)
4. Summing it up

What is Swarm Intelligence?

First introduced by Gerardo Beni and Jing Wang in 1989, swarm intelligence is the collective behavior of decentralized, self-organized systems, for which social insects are one of the best examples.

Swarm intelligence is an attempt to design algorithms or distributed problem-solving devices intended to mimic the collective behavior of social insect colonies.¹

Essentially, swarm intelligence improves our collective behaviors (our outputs).

Derek and Laura Cabrera, systems theorists and professors at Cornell University compare this to a game of chess in Flock Not Clock,

“The game of chess has simple enough rules for a child to master, yet there are 318 billion possible ways to play the first four moves. The behaviors (or outputs) of systems – be they a flock of starlings or biodiversity writ large, chess matches or organizations – are emergent properties of simple rules at the local level. By identifying, understanding, and applying these simple rules, we can make the outputs better.”

Let’s look at an example of how these simple rules work for an ant colony:

Simple rules outlined by the Cabrera’s allow social insects (such as ants) to become a superorganism. These simple rules are as follows:²

1. Look for food. Ants randomly forage for food.
2. If you find food, shoot pheromones. A few find food and communicate by leaving a pheromone trail increasing probability of collective action on food piles.
3. Never cross a pheromone trail. Self-organizing behavior around simple rules produces collective intelligence.

How to identify simple rules that work

The Cabrera’s have defined four simple and deeply connected rules that apply in all types of organizations: Vision (V), Mission (M), Capacity (C), Learning (L).

1. Vision (V): Your desired future state or goal (what do you see?). For example, ask the following: What do you see today? What should you see tomorrow?
2. Mission (M): Repeatable actions that bring out the vision (what do you do?).
3. Capacity (C): Systems that provide readiness to execute the mission (how do we align capacity?). Here you build capacity to do the mission.
4. Learning (L): Continuous improvement of systems of capacity based on feedback from the external environment (love of learning). For example, the Cabrera’s explain that a big part of learning is making people aware of the lens through which they perceive reality.

Why Swarm Intelligence matters to your team

Dr. Louis Rosenberg (founder of Unanimous AI) informs us that we (as individuals) are smart, yet as a group we are even smarter – we are able to amplify our intelligence.

“A brain is a system of neurons so deeply interconnected that an intelligence forms. A swarm is a system of brains so deeply interconnected that a super-intelligence forms. Simply put, a swarm is a brain of brains and it can be smarter than any individual member.” – Dr. Louis Rosenberg

In Human Swarming and the future of Collective Intelligence, Rosenberg discusses the potential of human swarming. He writes,³

If we consider the leap in intelligence between an individual ant and a full ant colony working as one, can we expect the same level of amplification as we go from single individual humans to an elevated ‘hyper-mind’ that emerges from real-time human swarming?

So, can humans swarm?

Yes.

How can humans swarm?

According to Rosenberg, technology is the key. Humans can swarm only if we develop technologies that fill in missing pieces of evolution that hasn’t yet been provided.⁴

Rosenberg developed a platform allowing swarms of online users to make decisions and answer questions together by moving a graphical puck. The puck is generated by a central server and modeled as a real-world physical system.