To investigate the effects of myside bias in group discussions, we created an agent-based model in NetLogo. This model simulates a group discussion in which the agents debate a binary issue. The debated issue has a correct/true alternative and an incorrect/false alternative. Our goal is to evaluate the impact of mybias by determining what effect it has on the ability to track the truth in discussions between agents with a myside bias compared to agents without this bias.
The model simulates a group discussions over a binary issue between myside biased agents, i.e. agents that undervalue arguments that attack their prior belief, and overvalue arguments that confirm their prior belief.
The objective of our model is to assess the extent to which the myside bias, i.e. the tendency to overvalue/undervalue arguments depending on their fit with one’s own prior belief, affect the ability of the group to find the correct answer to the binary issue under discussion.
In particular, the model is built to answer the question: does the myside bias help or hinder the ability of groups to find the correct answer to a binary issue?