1. Cultural Evolution, Disinformation, and Social Division
- Author
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Ministerio de Ciencia, Innovación y Universidades (España), Agencia Estatal de Investigación (España), Ministerio de Ciencia e Innovación (España), Vidiella, Blai [0000-0002-4819-7047], Valverde, Sergi [0000-0002-2150-9610], Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72], Bentley, R. Alexander, Horne, Benjamin D., Borycz, Joshua, Carrignon, Simon, Shteynberg, Garriy, Vidiella, Blai, Valverde, Sergi, O’Brien, Michael J., Ministerio de Ciencia, Innovación y Universidades (España), Agencia Estatal de Investigación (España), Ministerio de Ciencia e Innovación (España), Vidiella, Blai [0000-0002-4819-7047], Valverde, Sergi [0000-0002-2150-9610], Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72], Bentley, R. Alexander, Horne, Benjamin D., Borycz, Joshua, Carrignon, Simon, Shteynberg, Garriy, Vidiella, Blai, Valverde, Sergi, and O’Brien, Michael J.
- Abstract
Diversity of expertise is inherent to cultural evolution. When it is transparent, diversity of human knowledge is useful; when social conformity overcomes that transparency, “expertise” can lead to divisiveness. This is especially true today, where social media has increasingly allowed misinformation to spread by prioritizing what is recent and popular, regardless of validity or general benefit. Whereas in traditional societies there was diversity of expertise, contemporary social media facilitates homophily, which isolates true subject experts from each other and from the wider population. Diversity of knowledge thus becomes social division. Here, we discuss the potential of a cultural-evolutionary framework designed for the countless choices in contemporary media. Cultural-evolutionary theory identifies key factors that determine whether communication networks unify or fragment knowledge. Our approach highlights two parameters: transparency of information and social conformity. By identifying online spaces exhibiting aggregate patterns of high popularity bias and low transparency of information, we can help define the “safe limits” of social conformity and information overload in digital communications.
- Published
- 2024