There are no surprising facts, only models that are surprised by facts
Bayesian design
novel
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Descriptive
Prescriptive
Discussion (what it means or how it might be applied)
An architecture is, in some form, a model of the system that exists or will one day exist in real life. As stated by George Box (and many others): All models are wrong, some are useful.
In Bayesian probability, prior probabilities are used to
This means
Accounting for surprise means building architectures that integrate the prior probabilities into their model
Kaizen, architecture must either be flexible, or broad enough to account for adjustments in prior probabilities.
Historical reference (philosophy, etc)
Source
Surprise
Thinking about # unable to be surprised ?
Think of an architecture as something that can be asked a question.
When you ask it what happens in the real world, will the things it expected to happen happen at the frequencies it expected to have happen?
In other words, will it be surprised?
more on # unable to be surprised ?
System Architecture as a model of future reality
Shannon Entropy, the amount of “surprise” inherent to a set of outcomes
When the architecture meets reality, what will the surprise be? Minimize that surprise.
In other words, make it an architecture that accurately reflects your probabilities of the world.
Similarly, make it an architecture that can be flexible to update with your priors.