Forecasters Bias
This may already be a bias, I haven’t really researched this. Excuse my ignorance. But perhaps there could be a new bias we could identify called forecasters bias.
This bias would be the phenomenon where forecasters have a tendency to place too much weight on the importance of or the effect of forecastable events versus events that are less forecastable. Thereby somewhat (or entirely) neglecting other improbable less forecastable events.
Example 1: Theres a new coronavirus variant called Omicron. It has not yet spread, but it will. We can track the spread of this virus going forward into the future. When forecasting Omicron’s effect we have a tendency to overemphasize its effect because this event is forecastable.
Another coronavirus example 2: Early in the coronavirus pandemic individuals tracked the spread of the virus, and the rate at which vaccines progressed. They predicted with a good degree of accuracy the amount of deaths. They did not predict, however, that the political whims of the populace would lead to an anti-vax movement. The less forecastable event (anti-vax sentiment) was under-predicted
Example 3: fictional market researchers notice dropping energy prices. They model this phenomenon and expect it to continue for 18 months. But in this fictional 18 months, major earthquakes destroy huge cities and the researchers systematically failed to consider the prospect of major earthquakes happening which raise energy prices.
Example 4: energy prices are rising drastically. Researchers expect this to continue for 18 months. Suddenly, commercially viable nuclear fusion becomes available and governments spread this throughout the world. Energy prices drop to “too cheap to meter”, researchers got this wrong because it was too hard to forecast the progress of nuclear fusion.
I don’t know if this idea is any good. Just a thought!
I would love to read this. What a great idea. Pursue it!!