Covid To Climate Change: Bayesian Updating

Climate Change Bayesian Update
  1. Q1+Q2 is the majority: Doesn’t matter what changed, as long as believers are now the majority, we can be optimistic about climate change.
  2. Q2 is large: Doesn’t matter if believers outnumber the rest, what’s important is that people rationally change their mind when given compelling information. If Q2 is large, it means we have an engaged, informed, and thinking public that ensures society is learning from its mistakes and being better because of it.
  3. Ratio of Q2/(Q2+Q3) is large: Doesn’t matter if Q2 is large, as long as the % of non-believers who are converted because of Covid is large. Status-quo bias is very strong, like surface tension or a phalax, penetrating that first layer is the difficult part, needing a shock-event like Covid. After that mask is taken off, climate change acceptance will steadily grow.
  4. Q4 is very small: Doesn’t matter what goes on in Q1–2–3, as long as Q4 is kept small. Science is fighting an uphill battle against politics and religion. Conversion was hard-fought but well worth the trouble because converts are high-value customers. They’re worth more to us than new converts who were anyway less inclined towards science otherwise the would’ve converted already. Remission is a dangerous period, and the comfort of religion and petty politics is a tempting mistress. Minimizing Q4 is the top priority. If this has been small despite the many highly publicized attempts to malign science during Covid, then that is also an indication of an engaged, informed, thinking public.

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A novel insightful exercise to determine the pragmatic difference in intellectual payoff between a novel insight and an obvious fact mistaken for novel insight.

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