Networked disobedience to smart city development: The case of Hong Kong

Research output: Journal article publicationJournal articleAcademic researchpeer-review

Abstract

When urban landscapes erupt into civil unrests, smart technologies that are intended to help preserve social order may become prime sites of contention. Integrating critical data studies and research on networked social movements, this article examines the underexplored contours of networked disobedience to smart city development – that is, direct action by self-mobilised and self-organised digitally connected citizens and activists to subvert or disrupt the dominant structure of the datafied smart city – during a large-scale protest movement. The case of Hong Kong's smart lampposts is analysed to explicate a distinct technopolitical contention that emerged in the digital age, focusing on three key aspects: (1) citizens' digital curation of folk theories, which perpetuated a consensus of discontent over the installation of smart city technology, (2) the articulation of a digitised network of counter-power that provided a mediation opportunity structure for mobilisation and intervention, and (3) the crowdsourcing of disobedient practices of data activism aimed at sabotaging or evading the smart city technology. The article illustrates how seemingly ordinary issues of urban datafication can be repurposed to (re)produce political contention and the ways in which controversies over smart city development may fuel adversarial citizen–state engagement with repercussions for data-driven urban governance.

Original languageEnglish
Article numbere12095
Number of pages11
JournalIET Smart Cities
Volume7
Issue number1
DOIs
Publication statusPublished - 1 Jan 2025

Keywords

  • citizen engagement
  • digital media
  • networked dissent
  • smart cities
  • smart lampposts
  • urban technology

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Software
  • Urban Studies
  • Computer Science Applications
  • Computer Networks and Communications
  • Electrical and Electronic Engineering
  • Artificial Intelligence

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