Counter-Mapping the Spaces of Autonomous Driving (Englisch)

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In this article I provide an account of key tensions shaping the development of autonomous driving technologies, and explore how such tensions can open up avenues for counter-mapping the data spaces produced through these navigation technologies. The design and massive commercialization of autonomous vehicles implies the production of new models of space, generated through the integration of data collected through technologies such as lidar scanning, machine learning, and artificial intelligence. This production of space is bounded within the confines of the technological black boxes of the vehicles themselves, as well as the corporate black boxes of the companies that design and deploy them. However, there are key sources of tension surrounding the creation of these black boxes: those between market competitors; between the state and the private sector; and between civil society, the private sector, and the state. In this article I explore these tensions by focusing on the potential for counter-mapping as a means of critique, transparency, and political action across three separate aspects of the autonomous driving space-making process: (1) legislation, by examining the emergence of Right to Repair laws across the United States, beginning with the Automotive Right to Repair Law passed in Massachusetts in 2012; (2) design, through open source projects for building self-driving cars, exemplified by Udacity, a pioneer in this area; and (3) hacking, specifically interventions designed to open, critique, or disrupt autonomous driving technologies. These examinations are embedded in a political economic account that interrogates the ownership and control over the spaces produced through autonomous driving, as well as the economic value associated with such production of space.

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  • Titel:
    Counter-Mapping the Spaces of Autonomous Driving
  • Autor / Urheber:
  • Verlag:
    North American Cartographic Information Society
  • Erscheinungsjahr:
  • Anmerkungen:
    Cartographic Perspectives; No 92 (2019); 10–23 ; 1048-9053
  • Medientyp:
    Aufsatz (Zeitschrift)
  • Format:
    Elektronische Ressource
  • Sprache:
  • Klassifikation:
    DDC:    629

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