Separate Explanation from Emotion

#strategyNo mention

The world is a hierarchy of systems. Or rather Complex Systems (e.g. a relationship, a business).

We have only limited data about the world, i.e. hints about the Causal Structure of these systems (e.g. the end of a relationship, the lifecycle of a business).

We build Explicit Models to interpret and explain these data. With these we postulate a causal structure, i.e. events and their causal connections, that is consistent with the data.

Most of the time, these models take the form of causal stories – stories that causally link observed events and/or postulate unobserved causes.

These stories are simplifying on multiple levels: They work with only a subset of the potentially available data, consider only parts of the context for explanatory purposes, and have a linear structure.

In addition, the stories, and particularly the unobserved causes they pose, are heavily influenced by contingent external factors – among them memory, habits, priming, and Ideology.

Each story traces one set of connections in the causal web, which is helpful to explore this web, but no one story, or even set of stories, can map all of them.

This means that the stories we come up with about the world are not only not true, but not even capable to give an adequate description of the world (the breakup; the business).

Thus the breakup gets assessed using a “good actor/bad actor” distinction, a mid-20th century relationship model, and a focus on how the shared assets are being split; the story about the business is “wife gets shop from well-earning husband and shuts it down when bored with it”.

None of this has any claim to truthfulness – the stories are just posits consistent with the data available to the storyteller, and as more information (about relationship dynamics; about actual decision making) becomes available, they fall apart.

The same process, though, also happens when I try to explain what happens to methe events of my own life, e.g. my breakup: I construct a simplified Causal Model of it, often in the form of a story.

Which story I come up with is determined by contingent factors (memory, habits, priming, ideology); the only hard criteria are internal coherence and consistency with the data. My stories are not only not true, but not even capable to give an adequate description of my breakup.

This means I have to avoid elevating any one story over the others; be mindful of connections between them; and, first and foremost, stay alert to the fact that not even all of them together fully describe what really happened (and/or is happening).

The stories are just my brain’s attempts to make sense of my changed life situation, my changed expectations for the future, and the feelings of loss and sadness that come with both.

The triggers for these emotions are mostly memories of past events that in some way embody the part of my life that is over. It’s easy to focus on these events and start storytelling to explain the triggered emotions, but that is susceptible to mistakes like the Availability Bias: There is no reason why the most emotionally charged memories should be of the most causally significant events – they’re just the ones available for me to think about.

It also doesn’t help deal with the underlying Emotions productively. To do that, I rather need to let them play out, feeling and inhabiting them instead of trying to explain them. And I need to look for context factors that increase or reduce my resilience for this acceptance of my emotions.

This should also help keep the process of Narrative Self-construction open: it helps avoid building a linear and rigid “story of my life” out of the causal stories I explain my emotions with, which in turn would become a fixed condition and constraint for future emotions.

In other words, it helps me accept and embrace that Life is movement through a network of encounters.

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