I’d be interested to know how people think long-range forecasting is likely to differ from short-range forecasting, and to what degree we can apply findings from short-range forecasting to long-range forecasting. Could it be possible to, for example, ask forecasters to forecast at a variety of short-range timescales, fit a curve to their accuracy as a function of time (or otherwise try to mathematically model the “half-life” of the knowledge powering the forecast—I don’t know what methodologies could be useful here, maybe survival analysis?) and extrapolate this model to long-range timescales?
I’m also curious why there isn’t more interest in presenting people with historical scenarios and asking them to forecast what will happen next in the historical scenario. Obviously if they already know about that period of history this won’t work, but that seems possible to overcome.
Does anyone know of examples in the academic literature of “retrodictions” being used to assess forecasting accuracy?
John Maxwell makes a couple of good points in a comment about the linked post on the EA Forum:
Does anyone know of examples in the academic literature of “retrodictions” being used to assess forecasting accuracy?