Beautifying IoT: The Internet of Things as a Cultural Agenda

  • Jeffrey Bardzell
  • Shaowen BardzellEmail author
  • Szu-Yu (Cyn) Liu
Part of the Internet of Things book series (ITTCC)


As an IT research agenda, the Internet of Things is often framed according to technical and economic issues, such as protocols, standards, job-creation potential, etc. We argue that IoT also constitutes a cultural and aesthetic vision, that is, a projected image of urban- or region-scale beauty, in which lives are pursued in more meaningful and fulfilling ways than before. In HCI and related disciplines, aesthetics—when not outright dismissed as too subjective and/or confusing to engage—is commonly investigated as individual judgments about individual interfaces. This is a problem, because we know that technologies can produce ugly and unlivable environments at scale—from nuclear disaster sites to urban desolation caused in large part by the automobile. Aesthetic IoT is not a matter of making device surfaces more pretty, but of thinking deeply about the ways it will shape how we live; after all, urban desolation didn’t happen because roads weren’t painted attractively, but because roads disrupted communities and their established ways of life. This chapter demonstrates that aesthetic theory provides concepts sufficient to engage matters of IoT aesthetics in precise and pragmatic ways. It does so by analyzing a policy intended to beautify a major city in Asia alongside aesthetic interpretations of two design initiatives contemporaneous with it: an agricultural IoT project that proposes a computationally enabled new intimacy between humans and their land, and a kitchen design company that innovates not only on manufacturing materials but also on the aesthetic conventions needed for consumers to recognize those material properties as beautiful.


Aesthetic Conventions Zinc Alloy Aesthetic Experience Fruit Plate Technology Agenda 
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 Nature Switzerland AG 2019

Authors and Affiliations

  • Jeffrey Bardzell
    • 1
  • Shaowen Bardzell
    • 1
    Email author
  • Szu-Yu (Cyn) Liu
    • 1
  1. 1.School of Informatics, Computing, and EngineeringIndiana UniversityBloomingtonUSA

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