A “black swan” is an event of great magnitude that could never be predicted, whose probability of occurence is so small as to not even have been thought of.
These researchers are attempting to use AI to predict these very unusual events.
“The goal of this combination is to identify what might be the most useful data points when it comes to making accurate predictions of rare events. The point is to make the most of scarce data. Essentially, the quality of the data points can help make up for their lack of quantity, potentially allowing more to be done with less.”
This is bullshit of course. If you read the original work from Taleb, the point its that these events are not predictable. It dovetails with Chaos Theory in that the farther out from your actions you go, the more uncertainty there is in the prediction. A typical point is that if you want to accurately predict the position of a ball on frictionless pool table out to 50 some odd bounces, you would have to take into account the gravitational pull of an atom on the other side of the galaxy. The amount of data required to predict black swan events is like that. They are pissing in the wind…
Black Swan theory was developed by Nassim Nicholas Taleb, starting in 2001, to explain:
- The disproportionate role of high-profile, hard-to-predict, and rare events that are beyond the realm of normal expectations in history, science, finance, and technology.
- The non-computability of the probability of consequential rare events using scientific methods (owing to the very nature of small probabilities).
- The psychological biases that blind people, both individually and collectively, to uncertainty and a rare event’s massive role in historical affairs.
