As we gather partial information, we become less uncertain — for example, by reading customer reviews, we become more certain about which product to buy. This mental updating is expressed in a mathematical formula worked out by the 18th-century English scholar Thomas Bayes. It essentially captures how a rational mind makes decisions by assessing various uncertain alternatives.
When combining this concept with the mathematics of information (specifically signal processing), dating back to the 1940s, it can help us understand the behavior of people, or society, guided by how information is processed over time. It is only recently that my colleagues and I realized how useful this approach could be.
So far, we have successfully applied it to model the behavior of financial markets (market participants respond to new information, which leads to changes in stock prices) and the behavior of green plants (a flower processes information about the location of the sun and turns its head towards it).
