idw – Informationsdienst Wissenschaft
Nachrichten, Termine, Experten
Nachrichten, Termine, Experten
Climate change is a scientific fact and yet many people deny it. If this was different, if there was a broader social consensus, global warming could be fought more effectively. Researchers from the Leibniz Centre for Tropical Marine Research (ZMT) and Constructor University in Bremen have developed a mathematical model to simulate how people change opinions on climate issues and suggest that more ambiguity in communication may foster consensus. The results of their study have been published in the journal Royal Society Open Science.
Briefly summarised:
1. Consensus on climate issues: Researchers at ZMT and Constructor University Bremen have developed a mathematical model that shows how ambiguity in communication can help achieve consensus on climate issues.
2. Data: Survey data from the US, showing heterogeneous opinions on climate change, were used as starting point in the model. As agents in the model interact and exchange opinions, consensus, disagreement, or even polarisation may emerge.
3. Results: The model results suggest that in a society affected by some level of bias, a pro-environmental consensus can be achieved only if the communication between agents is characterised by some degree of uncertainty, that is, "ambiguity noise".
4. Conclusion: To effectively fight climate change, it is necessary to understand the role played by cognitive processes in preventing or enabling an increasingly divided and polarised society to reach a consensus on issues such as climate change.
5. Use of mathematical modelling: In addition to traditional social science approaches, mathematical modelling is an important tool for speeding up progress on understanding the role played by cognitive biases and ambiguity noise in consensus formation.
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 confirm 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 judgement.
Is it possible for a society initially characterised 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 that was recently 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 USA. This data shows the presence of six opinion groups in the USA 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 polarised, or opinions may solidify into disagreement.
The results of the model suggest that a pro-environmental consensus can be achieved only if the communication between agents is characterised by some degree of uncertainty, that is, "ambiguity noise". "Clear and unambiguous messages such as 'Nuclear power? No thanks!' tend to prevent consensus formation. A somewhat ambiguous communication that leaves room for interpretation may instead enable people to reach a consensus despite their initial differences in opinions," says Peter Steiglechner, first author of the paper and doctoral student at Constructor University.
The scientists sustain that to fight climate change, it is not enough to improve climate predictions or to disseminate the scientific facts among the public because facts do not necessarily change people’s minds. "We also need to understand the cognitive mechanisms that enable an increasingly divided and polarised society to reach a consensus on matters like climate change”, Merico points out. “The time window for acting against climate change is closing up rapidly, the sooner we can achieve a consensus on climate issues, the greater the chances for developing effective policies against the looming climate crisis. In addition to traditional social science approaches, mathematical modelling is an essential tool for speeding up progress on these problems.”
Prof. Dr. Agostino Merico | Leiter der Arbeitsgruppe Systemökologie | Leibniz-Zentrum für Marine Tropenforschung (ZMT)
E-Mail: agostino.merico@leibniz-zmt.de
Peter Steiglechner | Doktorand | Leibniz-Zentrum für Marine Tropenforschung (ZMT) und Constructor University
E-Mail: peter.steiglechner@leibniz-zmt.de
„Noise and opinion dynamics: How ambiguity promotes pro-majority consensus in the presence of confirmation bias”, by P. Steiglechner, M.A. Keijzer, P.E. Smaldino, D. Moser & A. Merico (2024) in Royal Society Open Science.
Link to the study: https://doi.org/10.1098/rsos.231071
Merkmale dieser Pressemitteilung:
Journalisten, Lehrer/Schüler, Studierende, Wirtschaftsvertreter, Wissenschaftler, jedermann
Mathematik, Meer / Klima
überregional
Forschungsergebnisse
Englisch
Sie können Suchbegriffe mit und, oder und / oder nicht verknüpfen, z. B. Philo nicht logie.
Verknüpfungen können Sie mit Klammern voneinander trennen, z. B. (Philo nicht logie) oder (Psycho und logie).
Zusammenhängende Worte werden als Wortgruppe gesucht, wenn Sie sie in Anführungsstriche setzen, z. B. „Bundesrepublik Deutschland“.
Die Erweiterte Suche können Sie auch nutzen, ohne Suchbegriffe einzugeben. Sie orientiert sich dann an den Kriterien, die Sie ausgewählt haben (z. B. nach dem Land oder dem Sachgebiet).
Haben Sie in einer Kategorie kein Kriterium ausgewählt, wird die gesamte Kategorie durchsucht (z.B. alle Sachgebiete oder alle Länder).
