... We have focused our analysis predominantly on ambiguity noise because its effects on consensus formation have been the least extensively addressed in prior models of social influence. By affecting communicated messages rather than their recipients, ambiguity noise has indirect consequences for the two relevant opinion formation processes in our model: selection and adaptation to social influence. It seems intuitive to think that clarity and unbiased reasoning in public debates are key to enabling a society with initially diverse or polarized opinions to reach an agreement [28,70]. However, clear communication might be at odds with successful consensus formation, as indicated by conceptual work on ambiguity as a strategic tool [26,71]. Our results show that moderate ambiguity in expressed opinions facilitates agreement under a wide range of bias levels—a pattern that differs from those of selectivity and adaptation noise.

Figure 1. Different types of noise and how they act inside or outside the social interaction process: (i) ambiguity noise, xi_am , acts on the message from a sender, (ii) selectivity noise, xi_se , affects whether a receiver is chosen for interaction in light of the difference between message and receiver opinion and the confidence bound, (iii) adaptation noise, xi_ad , affects the receiver’s opinion after an interaction, and (iv) exogenous noise, xi_ex , perturbs an agent opinion from outside of the social interaction.
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Cognitive biases are among the most important factors that prevent people from changing their minds. Climate change deniers and climate activists often tend to accept only information that confirms their respective opinions on the matter. However, opinion dynamics are also influenced by a factor that the researchers call "ambiguity noise." Unlike biases, ambiguity noise is variable, depends on many random factors, and leads to inconsistent judgment.

Is it possible for a society initially characterized by heterogeneous views on climate change to reach a consensus despite prejudices and taking into account "noise"? A team led by Professor Agostino Merico, head of the working group Systems Ecology at ZMT, investigated this question in a study published in the journal Royal Society Open Science.

"Our model is based on realistic assumptions about how people change opinions and includes the cognitive processes affecting the dynamics of opinions in a society," says Merico. The model was fed with data from surveys conducted in the U.S.

This data shows the presence of six opinion groups in the U.S. in relation to climate change: the Alarmed, the Concerned, the Cautious, the Disengaged, the Doubtful, and the Dismissive. Using these data as initial conditions for the model, the simulations showed that as agents in the virtual society interact with each another and exchange opinions, a single shared opinion may emerge, viewpoints may become more polarized, or opinions may solidify into disagreement.

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