Noise, Fake News, and Tenacious Bayesians - Brody, Dorje C. (Frontiers in Psychology, 2022)
A modelling framework, based on the theory of signal processing, for characterising the dynamics of systems driven by the unravelling of information is outlined, and is applied to describe the process of decision makings. The model input of this approach is the specification of the flow of information. This enables the representation of (i) reliable information, (ii) noise, and (iii) disinformation, in a unified framework. Because the approach is designed to characterise the dynamics of the system under study, it is possible to quantify the impact of information control, including those resulting from the dissemination of disinformation. It is shown that if a decision maker assigns an exceptionally high weight on one of the alternative realities, then under the Bayesian logic their perception hardly changes in time even if evidences presented indicate that this alternative corresponds to a false reality. By observing the role played by noise in other areas of natural sciences, a new approach to tackle the dark forces of fake news is proposed.