Abstract
Current research on autonomous vehicles tends to focus on making them safer through policies to manage innovation, and integration into existing urban and mobility systems. This article takes social, cultural and philosophical approaches instead, critically appraising how human subjectivity, and human-machine relations, are shifting and changing through the application of big data and algorithmic techniques to the automation of driving. 20th century approaches to safety engineering and automation—be it in an airplane or automobile-have sought to either erase the human because she is error-prone and inefficient; have design compensate for the limits of the human; or at least mould human into machine through an assessment of the complementary competencies of each. The ‘irony of automation’ is an observation of the tensions emerging therein; for example, that the computationally superior and efficient machine actually needs human operators to ensure that it is working effectively; and that the human is inevitably held accountable for errors, even if the machine is more efficient or accurate. With the emergence of the autonomous vehicle (AV) as simultaneously AI/ ‘robot’, and automobile, and distributed, big data infrastructural platform, these beliefs about human and machine are dissolving into what I refer to as the ironies of autonomy. For example, recent AV crashes suggest that human operators cannot intervene in the statistical operations underlying automated decision-making in machine learning, but are expected to. And that while AVs promise ‘freedom’, human time, work, and bodies are threaded into, and surveilled by, data infrastructures, and re-shaped by its information flows. The shift that occurs is that human subjectivity has socio-economic and legal implications and is not about fixed attributes of human and machine fitting into each other. Drawing on Postphenomenological concepts of embodiment and instrumentation, and excerpts from fieldwork, this article argues that the emergence of AVs in society prompts a rethinking of the multiple relationalities that constitute humanity through machines.
Highlights
Current research on autonomous vehicles tends to focus on making them safer through policies to manage innovation, and integration into existing urban and mobility systems
● In Arizona, an Uber test-driver in a Volvo semi-autonomous vehicle did not take control of the car that was in auto-pilot and hit a pedestrian wheeling her bicycle across the road; the pedestrian was not properly identified by the vehicle’s computer vision software; the driver was found to be distracted (National Transport Safety Board, 2018)
Measurement of human activity, bodies, and affect in work contexts becomes the basis for sorting, classification and analysis resulting in the production of social categories that have far reaching consequences; for example, categories such as criminality and creditworthiness are determined algorithmically based on individual data profiles and run through analytics; these control large swathes of alreadydisadvantaged communities (Amoore, 2020; Eubanks, 2018)
Summary
Current research on autonomous vehicles tends to focus on making them safer through policies to manage innovation, and integration into existing urban and mobility systems. ● In Arizona, an Uber test-driver in a Volvo semi-autonomous vehicle did not take control of the car that was in auto-pilot and hit a pedestrian wheeling her bicycle across the road; the pedestrian was not properly identified by the vehicle’s computer vision software; the driver was found to be distracted (National Transport Safety Board, 2018).
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