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Outside of astronomy, I don't think there's any history of reliable 80+ year scientific forecasts that predict specific changes to our world.

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There’s so much modeling that couldn’t even be done 80 years ago. Electronic computers were in their infancy, climate science was just beginning, weather satellites (hell any artificial satellite) had not yet been launched.

The inputs, the models themselves, and the main way to compute an output had mostly not been invented.

This is a fundamentally unfair comparison. If it couldn’t be computed analytically, it wasn't really possible to compute it 80 years ago. That absolutely doesn’t mean we should just ignore these predictions. Are we supposed to always wait some arbitrary time before listening to long term prediction?

We've had mathematical models of change for over two thousand years. We have reliable, precise ones for astrological changes. As far as I know, we have none related to ecology or other complex systems that have proven capable of making long-term predictions.

I never said we should ignore any prediction. My calculation is purely Bayesian: how much prior trust should you place in a model (or class of models) with no long-term track record of success?

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