Jan 10, 2019
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Paradigms All The Way Down

Scott Alexander presents a 'Grand Unified Chart' showing how different domains of knowledge share a similar structure in interpreting the world, arguing this is due to basic brain algorithms and effective epistemology. Longer summary
Scott Alexander draws parallels between different domains of knowledge, showing how they all share a similar structure in interpreting the world. He presents a 'Grand Unified Chart' that compares Philosophy of Science, Bayesian Probability, Psychology, Discourse, Society, and Neuroscience. Each domain is broken down into three components: pre-existing ideas, discrepancies, and actual experiences. Scott argues that this structure is universal because it's built into basic brain algorithms and is the most effective way to do epistemology. He emphasizes that the interaction between facts and theories is bidirectional, and that theory change is a complex process resistant to simple contradictions. Shorter summary

Related to: Book Review: The Structure Of Scientific Revolutions

Every good conspiracy theorist needs their own Grand Unified Chart; I’m a particular fan of this one. So far, my own Grand Unified Chart looks like this:

Philosophy Of Science Paradigm Anomaly DataBayesian Probability Prior KL-divergence Evidence**Psychology** Prediction Surprisal Sense-Data**Discourse** Ideology Cognitive Dissonance Facts**Society** Frames & Narratives Exclusion Lived Experience**Neuroscience** NMDA Dopamine AMPA

All of these are examples of interpreting the world through a combination of pre-existing ideas what the world should be like (first column), plus actually experiencing the world (last column). In all of them, the world is too confusing and permits too many different interpretations to understand directly. You wouldn’t even know where to start gathering more knowledge. So you take all of your pre-existing ideas (which you’ve gotten from somewhere) and interpret everything as behaving the way your pre-existing ideas tell you they will. Then as you gradually gather discrepancies between what you expected and what you get (middle column), you gradually become more and more confused until your existing categories buckle under the strain and you generate a new and self-consistent set of pre-existing ideas to see the world through, and then the process begins again.

All of these domains share an idea that the interaction between facts and theories is bidirectional. Your facts may eventually determine what theory you have. But your theory also determines what facts you see and notice. Nor do contradictory facts immediately change a theory. The process of theory change is complicated, fiercely resisted by hard-to-describe factors, and based on some sort of idea of global tension that can’t be directly reduced to any specific contradiction.

(I linked the Discourse and Society levels of the chart to this post where I jokingly sum up the process of convincing someone as “First they ignore you, then they laugh at you, then they fight you, then they fight you half-heartedly, then they’re neutral, then they grudgingly say you might have a point even though you’re annoying, then they say on balance you’re mostly right although you ignore some of the most important facets of the issue, then you win.” My point is that ideological change – most dramatically religious conversion, but also Republicans becoming Democrats and vice versa – doesn’t look like you “debunking” one of their facts and them admitting you are right. It is less like Popperian falsification and more like a Kuhnian paradigm shift or a Yudkowskian crisis of faith.)

Why do all of these areas share this same structure? I think because it’s built into basic algorithms that the brain uses for almost everything (see the Psychology and Neuroscience links above). And that in turn is because it’s just factually the most effective way to do epistemology, a little like asking “why does so much cryptography use prime numbers”.

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