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Ontological Fallacies Linked to Energy, Information and Related Technologies

  • Nicola LabancaEmail author
Chapter
Part of the Green Energy and Technology book series (GREEN)

Abstract

People and the socio-technical systems they constitute are being literally identified with motors and information processors in the present age of complex systems. This means, among others, that (a) energy and information are seen as actual ontological entities whereon the survival and the evolution of social aggregates depend and that (b) these entities entirely frame mainstream research and policy approaches aiming to increase the sustainability of human activities. This chapter (1) discusses how and why these extremely useful conceptual entities should be considered as metaphors when applied to study societies; (2) identifies some main social dynamics causing that these metaphors are instead constantly taken literally; (3) describes the implications of this literal interpretation for the ongoing energy transition. In particular, it shows how the literal interpretation of these metaphors reinforces dependency on abstract resource units supplied by energy and information technologies as well as a continuous growth in their consumption. In addition, this chapter illustrates how the unwanted effects of this literal interpretation can be effectively escaped by researchers, policy makers and all people involved in the current energy transition by focusing on the design and implementation of policy actions where the installation of technical solutions with reduced energy input and/or emissions is made complementary or subordinated to a reorganization of the energy outputs. This chapter also shows how this can allow exploiting an otherwise neglected huge variety of context dependent policy solutions relying on people capacities and on their more active involvement in policy making.

Keywords

Practical Knowledge Mutual Reinforcement Matter Flow Conservation Principle Literal Interpretation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing Switzerland 2017

Authors and Affiliations

  1. 1.European Commission, Directorate-General Joint Research CentreUnit C.02 Energy Efficiency and RenewablesIspraItaly

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