I have also shown it can be used to model the dynamics of opinion poll statistics associated with an election or a referendum and drive a formula that gives the actual probability of a given candidate winning a future election based on today’s poll statistics and how the information will be released in the future.
In this new “information-based” approach, the behavior of a person — or group of people — over time is deduced by modeling the flow of information. So, for example, it is possible to ask what will happen to an election result (the likelihood of a percentage swing) if there is “fake news” of a given magnitude and frequency in circulation.
But perhaps most unexpected are the deep insights we can glean into the human decision-making process. We now understand, for instance, that one of the key traits of the Bayes updating is that every alternative, whether it is the right one or not, can strongly influence the way we behave.
