Getting The Best of Human Network Potential
'The heuristic toggle' or 'opponent processing'
This article is inspired by a conversation between John Vervaeke, Iain McGilchrist, and Daniel Schmachtenberger. The Psychological Drivers of the Metacrisis.
“Meanwhile the Adversary of God and man, Satan with thoughts inflamed of highest design, Puts on swift wings, and towards the gates of hell Explores his solitary flight.” John Milton
We find ourselves in times of crisis. Crisis at multiple scales and in multiple domains. There is personal crisis such as mental health issues and financial insecurity. There are national crises including political corruption, economic mismanagement, crumbling social cohesion, and growing inequality. Then there are global crisis such as war, pollution, and energy poverty.
Underpinning many of these crises are perverse incentives, finite and zero-sum game theories, and adversarial processing.
Perverse incentives have unintended and undesirable results from narrow thinking and a lack of foresight.
Finite and zero-sum game theories are the belief that the game cannot go on forever and a winner must have a loser. (No win-win)
Adversarial-processing is where difference of opinion or position is met with antagonistic, rivalrous, and conflict orientated processes. One seeks to beat the other.
Adversarial-processing drives zero-sum game theories and perverse incentives. When we are locked into battle we see no value in alternatives, we also fail to see the flaws in our own position.
But it does not have to be this way. Collaborative, cooperative, and coordinated behaviour is common where common goals and values exist.
The challenge is, how to generate those behaviours where difference of opinion or position is the defining characteristic.
How do we get “enemies” to see each other differently and work together?
Well it turns out that nature has the answers. Evolution has solved this problem in a typically elegant yet sophisticated way called opponent-processing.
Opponent-Processing
Opponent-processing is where two opposing systems lock together and become a self-correcting system. A self-correcting system has no single authority, no emperor or king.
The problem with any single system, or single perspective, is bias. Every system or perspective is heuristic in nature. It is a shortcut to solving problems producing a good enough result in an efficient manner. Every heuristic has a bias.
Example: Availability Heuristic and Bias
The availability heuristic works by prioritizing infrequent events based on recency and vividness. The bias: Plane crashes can make people afraid of flying.
However, when two opposing systems have biases that counteract each other they can become the best correctors of each other. These are called complementary biases. Lets take a look at how this works in you and me right now.
We will start at the level of individual cognition, evolution has generated many opponent-processing systems within our cognitive processing that self-correct through complementary biases.
Evolutionary Provenance
Example 1. The autonomic nervous system is made of two opposing systems with complementary biases. The sympathetic and parasympathetic nervous systems.
The sympathetic nervous system activates the fight or flight response during a threat or perceived danger. It’s bias is to generate threat response. The parasympathetic nervous system restores the body to a state of calm or homeostasis. It’s bias is to control response.
The heuristic toggle between the two is opponent-processing. The self-correcting, self-regulating system with no singular executive authority making decisions.
Example 2. The attentional system made of task focus and default modes constantly moves between focussing and “wandering” which includes daydreaming and environmental scanning. This helps you can get things done without distraction, but also keeps an eye on your environment for important signals.
It also ensures that you can draw on other information, getting inspiration from lateral thinking without getting lost in daydreaming.
Beyond The Individual
Seeing how opponent-processing works within us is all very well, but how do we extend this to get the best of human network potential?
Lets start with something we are all familiar with - family and friends.
We all have family and friends that we don’t always see eye to eye with. This sometimes leads to disagreement, argument, even conflict. What I have referred to above as adversarial-processing. When we come up against opinions or behaviours that are at odds with our own we often default to a defensive position.
However, this does not always last, and on occasion we reflect and realise that perhaps the other was right, or at least not entirely wrong! We can, over time, begin to value those friends that call us out on our bullshit. Drawing critical attention to our biases becomes a source of growth. It helps us see ourselves better.
The realisation that the other is not attacking us, but is being honest with us, often out of love, transforms adversarial-processing into opponent-processing. Not only do we gain a valuable source of self-correction, but we can become one for the other.
You are the best possible entity to help me overcome my biases because you have alternative biases - I am the best to help you.
To help another become aware of their own biases, to self-correct, to know themselves better, to become more - is this not love? Opponent-processing is, in some ways, an act of love between individuals.
Distributed Cognition
How about scaling opponent-processing to the level of networks, societies, and even global governance? This requires embedding opponent-processing into distributed cognition systems.
First, distributed cognition (DCog). Put simply distributed cognition is thinking spread out. Cognition isn't just in our brains, it involves people, tools, and the environment all working together. ️
Imagine a team navigating a ship. Their shared knowledge, the instruments, and even the ocean currents all contribute to their thinking. Or an agricultural society working with the land to grow food and raise live-stock.
Systems of Governance
It’s easy to see how systems of governance are distributed cognition systems. Some also provide great examples of opponent-processing systems.
The San of the Kalahari and The Minangkabau of Indonesia are great examples of governance systems without authoritarian executive functions (no emperor or king).
But for an example where adversarial-processing became opponent-processing we can look to The Iroquois Confederacy.
Formed around 1570, the Iroquois Confederacy united five previously warring nations into a powerful alliance.
Each nation retained its own autonomy but came together for matters of war, trade, and diplomacy.
Decisions were made through a Grand Council, where each nation had equal representation and decisions required unanimous consent.
The Iroquois Confederacy found a way to use their differences to self-correct for previously devasting interactions such as enduring warfare, bloody internal conflict, and common external threats. Additionally they fostered common benefits such as trade, resource sharing, dispute resolution, unity, justice, and inclusion.
For a while, modern democracies continued this tradition. Although in recent years politics seems to have degenerated into adversarial-processing.
How To Get The Best of Human Network Potential
It is easy to see how opponent-processing and distributed cognition can create self-correcting systems where there are shared values and goals.
We see this at many levels, from children creating and playing imaginative games, to DAOs (distributed autonomous organisations) providing financially governance to collective investments.
But how do we do this where there is competition, ideological disagreement, and historical grievance? Although I do not foresee a utopia where humanity has transcended its limitations and built a world beyond scarcity. I do believe we can do a lot better than we currently are.
Curiosity and the thirst for knowledge are driving forces for humanity. The power of collaboration, cooperation and understanding are self evident. What is needed is a shift in mindset.
As I stated in Wise Man or Networked Man? homo sapien (wise man) may not be the best description of our species. Homo diktyos or “networked man” is much better. We are intrinsically networked social beings. We are ill-equipped to survive alone.
Today more than ever we are utterly dependent on each other. Our survival is a collective effort all the way down. Our networks are rooted in our biology.
We need to remember this, talk about this, promote this idea. When we value connectedness more than success, when we fall in love with our relevance to each other, we fulfil the best of our potential.
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