How Dogmatism Leaves Us Less Informed
Remember that rumor on your newsfeed about masks making a COVID infection more likely? The one you are not quite sure about. It sounded remotely reasonable—but should you share it? Or do you go and check a reliable second source first?
Such choices are ubiquitous: Do we trust an intuitive judgment or do we seek more information?
In a new paper published in PNAS, my colleagues Max Rollwage, Ray Dolan, Steve Fleming and I explored how we deal with such information-seeking decisions. We were particularly interested in how these choices differ across people who are more or less dogmatic. Dogmatic people believe that their worldview reflects an absolute truth, which often stifles debates and drives us apart.
However, it’s unclear what sort of cognitive processes drive this outlook on life. We believe that understanding how dogmatic people search for information would be a good starting point.
People who think dogmatically often appear uninterested in novel information that could change their mind. One reason for this is what’s known as motivated search. In other words, more dogmatic people might be particularly enamored with their opinions: Why hear what the other candidate has to say when my own view is better anyway?
We all share this bias and it may be inflated in more dogmatic people. However, there’s a catch: Motivated search is tied to our specific group membership or opinion. If you’re Republican, your bias is likely red; if you’re a Democrat, your bias is likely blue. This made us wonder: Is it the dogmatic individual’s specific opinions that make them seek less information? Or is their lowered search driven by something that transcends particular views?
References
Schulz, L., Rollwage, M., Dolan, R. J., & Fleming, S. M. (2020). Dogmatism manifests in lowered information search under uncertainty. Proceedings of the National Academy of Sciences, 202009641. https://doi.org/10.1073/pnas.2009641117
About the Author
Lion Schulz
Lion Schulz is a doctoral researcher at the Max Planck Institute for Biological Cybernetics. His research combines insights from behavioral economics with approaches from artificial intelligence to understand human thinking and decision making. He’s particularly interested in using a computational understanding of the mind to tackle larger societal issues like polarization or mental health. Prior to his PhD, he completed a Master’s in Cognitive Science at University College London.
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