  We present an introduction to a novel model of an individual and group
opinion dynamics, taking into account different ways in which different sources
of information are filtered due to cognitive biases. The agent based model,
using Bayesian updating of the individual belief distribution, is based on the
recent psychology work by Dan Kahan. Open nature of the model allows to study
the effects of both static and time-dependent biases and information processing
filters. In particular, the paper compares the effects of two important
psychological mechanisms: the confirmation bias and the politically motivated
reasoning. Depending on the effectiveness of the information filtering (agent
bias), the agents confronted with an objective information source may either
reach a consensus based on the truth, or remain divided despite the evidence.
In general, the model might provide an understanding into the increasingly
polarized modern societies, especially as it allows mixing of different types
of filters: psychological, social, and algorithmic.
