Learning and open data in sustainability transitions: evolutionary implications of the theory of probabilistic functionalism

Abstract

The Theory of Probabilistic Functionalism, as a general theory of how organisms interact with complex environmental systems, provides a useful framework for describing essential processes of sustainability planning groups. Particularly, the mechanism of producing evolutionary stable representations of and judgment about the environment has important implications for sustainability transitions. In comparison with biological evolution, the environment changes much faster in social phenomena, and the selection dynamics working on heterogeneous groups for successful survival would be incomplete. That makes continuous learning by the members of planning groups as well as collective decision-making among them critically important. The policy of open data for assembling, distributing, and utilizing various kinds of data will facilitate vision creation, strategy development, and consensus building with stakeholders for sustainability transitions.

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Correspondence to Masaru Yarime.

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This Perspectives paper is a comment on Scholz’s “Managing complexity: from visual perception to sustainable transitions—contributions of Brunswik’s Theory of Probabilistic Functionalism”, Environ Syst Decis. https://doi.org/10.1007/s10669-017-9655-4.

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Yarime, M. Learning and open data in sustainability transitions: evolutionary implications of the theory of probabilistic functionalism. Environ Syst Decis 38, 88–91 (2018). https://doi.org/10.1007/s10669-017-9668-z

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Keywords

  • Theory of probabilistic functionalism
  • Sustainability transition
  • Evolutionary process
  • Learning
  • Open data