… And Then A Miracle Occurs

That title will make sense a bit later.

This article is about understanding and predicting the trajectory of humanity. Specifically

• To what degree can we predict the trajectory?
• How do we factor in the idea of a phase shift ?

Since computers became powerful enough (the 1970s), we have been creating models to “predict the trajectory of humanity”. The prime example is probably the World3 model, from the Club of Rome, and it’s successors and refinements. (See Wikipedia and this article for good overviews).

As is now common knowledge, the summary predictions from these models (with all caveats applied) is that, unless we make serious changes to society, we are heading towards some form of collapse. We usually simply refer to this as The Climate Crisis, but there are many more facets, which also go beyond the scope of the the World3 model.

The World3 model was based on the then emerging discipline of Systems Theory. This discipline was developed in the mid 20th century as a counter to the reductionist approach of science.

Whereas the normal scientific method breaks down systems into their individual parts and studies them in isolation, systems theory instead looks at how the parts interact with each other and with the environment. It also recognizes that systems are often dynamic and non-linear.

The usual criticisms of the World3 model (based on systems theory) are that

• It’s too simpleIt doesn’t take into account enough factors and/or does not use enough types data and/or enough detail of data.
• It’s too complexThe conclusions are obvious. We don’t need a complex model to tell us that, on a finite planet with limited resources, constant growth will hit a boundary (”limits to growth”)

But the point I want to make here is that there are deeper and more fundamental critiques - all centred around the question of whether a systems view can adequately describe or model what we are really interested in.

Here are the reasons why I think it cannot.

Systems views only take into account external factors

Integral Theory’s Quadrant model (summarised here) argues that it is essential to consider the internal dimensions alongside the external. If we only consider the external dimensions - things that can be directly measured and quantified - we only get half the picture. The internal dimensions (such as psychology and culture, whose attributes can only be measured indirectly) are equally important for a comprehensive understanding of anything.

Systems view are (usually) external-only.

Missing the inner dimension misses opportunities to see key elements to possible solutions

As a consequence of ignoring the inner dimensions, solutions such as those proposed by Inner Development Goals don’t get considered. The IDGs are a counterpart to the SDG (Sustainable Development Goals) which are themselves derived from a systems theory analysis and focus primarily on the external dimensions.

The SDG’s 2030 targets are a very long way from being realised.

Systems views are still essentially reductionist

Systems views, although “systemic”, are still limited to an understanding that’s based on a reduction into component parts. The systems view emphasises the need to understand the relationship between the parts, but it still requires a reduction into parts.

This is fine, but it excludes a way of understanding that is wholistic in essence. This idea is best described by Ian McGilchrist’s work on the left and right brain hemispheres. We need both hemispheres working together for us to function properly and effectively, but we are becoming dominated by the parts-oriented, reductionist left hemisphere, whereas McGilchrist argues that the wholistic, big-picture right hemisphere should be the master. His ideas are beautifully summarised in this information-dense video.

Systems views cannot predict phase shifts

This is, perhaps, the most important point.

A phase shift happens when a system enters a configuration whose dynamics are totally different to those of the original system.

A trivial example is the phase shift from a solid to a liquid and from a liquid to a gas. A deeper example is the phase shift from a chrysalis (containing a goo of cells) into a butterfly. A cultural example is the shift from tribe-sized hunter-gathering societies to agricultural, city-sized societies.

No model of the original system, no matter how complex and integrated and data-rich, could have predicted the transition into the new phase. (I expect some will argue against this, but that’s a longer discussion).

And this brings me to title of this article.

The phase shift is, as far as the mathematical or computer model is concerned, a miracle. It simply cannot be predicted. We may be able to look at the dynamics and conclude that a phase shift is likely (I don’t know whether such factors are included in the models: I suspect not in most cases). But I highly suspect that no model can predict the nature of the system after the phase shift.

Personally, from what I see happening (all the bad stuff combined with all the good stuff - which is usually less prominent), I suspect we are in for a phase shift. Which is a miracle, as far the models are concerned.

Which raises yet more issues, such as:

• Can we plan for the new phase?
• Can we at least try to predict its contours?
• Can we figure out what our own role might be?
• Are we able to learn to live with the inevitable high degree of uncertainty?

This topic, those issues, and more, are what we discuss in the?Humanity’s Transition - Oxford Discussions?Meetup group, which I organize. The next meeting is Oct 25th 2023

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