Yesterday I talked about how we could use AI to spot relationships between different factors and limit the problem of omitting important factors and I also discussed how people's risk preferences influence the overall expected outcomes in the economy.
Combining these two points, I think we can use AI to discover some black swan events and even make their probabilities computable. One of many reasons of why black swan events exist is because they could be ignored by our human beings. When we are using AI to search for all relevant factors, it is impossible to say that there will be no likelihood of omitted variables, but the number of omitted factors is very likely to decrease. Therefore, I think using AI to spot black swan events is one effective way.
In addition, there are other ways to spot black swan events. Some black swan events are not entirely ignored by the whole population, they are observed by a minority of the population. This is partial because of the specialisation within our economy and society. When labours enter their industries for too many years, their skills, information and knowledge become isolated from the outside world. Therefore, cooperation across sectors is necessary, so labours within one particular industry can have access to information from other sectors. In the future, labours with knowledge of multiple fields are more suitable for the economy and the society.
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