How can we wrap our minds around futures that are at once immensely complex, and riddled with uncertainty? How can we assess the likelihood of a whole range of possible outcomes? Jon Worth, Brexit blogger extraordinaire, provides one model: flowcharts augmented with probabilities.
This is just a small portion of his latest (at time of writing) map. Possible events are in boxes, and lines point to possible subsequent events. The orange boxes on the lines provide Worth’s estimate of the probability that one event follows from a prior one. The thickness of the line also conveys this information.
This seems like a marvellous way to help our feeble minds make sense of complexity and uncertainty simultaneously. I confess to not having seen probability-augmented flowcharts before (though presumably they are out there; if you know of essentially the same thing being done elsewhere, can you let me know in the comments?). I’ve seen plenty of flowcharts, and plenty of probability-linked networks (i.e. Bayes nets) but Worth’s charts are both at once. They’re not as rigorous as Bayes nets, but then Bayes nets are often intractable-in-practice for this kind of situation anyway; Worthy maps (if I can call them that) might be the “semi-formal sweet spot” between intuitive assessments and full-on Bayesian analyses.
Having seen a Worthy map, just imagine trying to estimate the likelihood of various Brexit outcomes without such a chart.