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Emergence

  • Jennifer SeevinckEmail author
Chapter
  • 701 Downloads
Part of the Springer Series on Cultural Computing book series (SSCC)

Abstract

This chapter establishes a broad understanding of emergence and provides a tool for classifying it, the Taxonomy of Emergence in Interactive Art (TEIA) . This framework sits across the debated concept of emergence. It draws on the variety of understandings of emergence in the physical and life sciences through to design research communities, to reveal differences and similarities between them. The classifications fit an overarching, broad understanding of emergence as occurring when a new form or concept appears that was not directly implied by the context from which it arose; and where this emergent whole ’ is more than a simple sum of the parts . Emergence also has some core qualities and characteristics. As implied by the definition, something new is created that is a whole with parts, which exists across levels and has the potential for feedback between those levels, namely from the whole to the parts. Unpredictability , creativity and open-endedness and the subjective interpretation of emergence are other key concerns that have come out of emergence literature. A new concept that I introduce here is referencing . While new to the domain of emergence it is significant to the visual arts. It facilitates a more differentiated understanding of emergence in the context of interactive art by distinguishing those instances of emergence that are associated with something else in the world (as in figurative and representational work in the visual arts) from the more direct and material concerns of Concrete art . The various qualities of emergence and organizing TEIA discussed here go on to inform the analytical and creative activities in later chapters. A more in-depth discussion of emergence follows in Chap.  7, for the interested reader.

Keywords

Natural World Subjective Contour Physical Emergence Snow Goose Core Quality 
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.Queensland University of TechnologyBrisbaneAustralia

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