We present an argumentative agent-based model for studying the impact of “myside bias” on the argumentative dynamics in scientific communities. According to recent insights in cognitive science, scientific reasoning is influenced by `myside bias’ – a tendency to prioritize the search and generation of arguments that support one’s views rather than arguments that would undermine them and to apply more critical scrutiny to opposing than to one’s stances. Even though myside bias may pull scientists away from the truth, individually and collectively, its effects could be mitigated by specific socio-epistemic mechanisms, such as shared beliefs across the community.

Although myside bias may pull individual scientists away from the truth, its effects on communities of reasoners remain unclear since (Mercier, 2014) argue that specific socio-epistemic mechanisms may mitigate its negative impact.

The aim of our model is two-fold: first, to study the argumentative dynamics generated by myside bias, and second, to explore which mechanisms may act as a mitigating factor against the pernicious effects of the bias. Our results indicate that biased communities are epistemically less successful than non-biased ones but that two mechanisms help communities: the presence of a common filter of weak arguments, which can be interpreted as shared beliefs, and an equal distribution of agents for each view at the beginning.