Faulty Extrapolation

A Faulty Extrapolation is a special kind of over-generalization (dicto simpliciter) involving a prediction. It is the process of predicting a result based on insufficient or unprovable evidence. 

Faulty Extrapolations are hard to disprove because it is difficult to disprove something that hasn't yet happened and may not happen for some time. What are we going to do, pause the argument and wait until the prediction does or does not come true? What if that prediction won't come full circle for 30 years? Sort of makes an actual debate difficult, ya know?

Simple questions that could diffuse a Faulty Extrapolation are: 

1. What evidence supports that prediction? 

2. What else might/could happen instead?

The difference between a Faulty Extrapolation and a Slippery Slope Fallacy is that the Faulty Extrapolation doesn't necessarily claim that Step A will lead to step B which will lead to step C, etc. (which is what the slippery slope fallacy does). Instead, the Faulty Extrapolation simply uses insufficient evidence to come to a conclusion AND that conclusion occurs in the future, making it a prediction.

Example: 

If cases of COVID keep rising at the 2.4 rate we've been seeing, there will only be 200 people alive by March of 2024.

Couldn't a lot happen between now (May 2020) and 2024? Are we ignoring regular transmission curves? Vaccines?

BTW, I completely made up these numbers. I don't even know what a 2.4 rate is.

Sounds scary, though. 😱