Dalia Mukhtar-Landgren
Associate Professor | Senior Lecturer
From senses to sensors : autonomous cars and probing what machine learning does to mobilities studies
Author
Summary, in English
Cars are nowadays being programmed to learn how to drive themselves. While autonomous cars are often portrayed as the next step in the auto-motive industry, they have already begun roaming the streets in some US cities. Building on a growing body of critical scholarship on the development of autonomous cars, we explore what machine learning is in open environments like cities by juxtaposing this to the field of mobilities studies. We do so by revisiting core concepts in mobilities studies: movement, representation and embodied experience. Our analysis of machine learning is centred around the transition from human senses to sensors mounted on cars, and what this implies in terms of autonomy. While much of the discussions related to this transition are already foregrounded in mobilities studies, due to this field's emphasis on complexities and the understanding of automobility as a socio-technological system, questions about autonomy still emerge in a slightly new light with the advent of machine learning. We conclude by suggesting that in mobilities studies, autonomy has always been seen as intertwined with technology, yet we argue that machine learning unfolds autonomy as intrinsic to technology, as the space between the car, the driver and the context is collapsing with autonomous cars.
Department/s
- Department of Political Science
- Lund University
- Centre for Innovation, Research and Competence in the Learning Economy
- Organizational Studies
Publishing year
2023-03-12
Language
English
Pages
301-314
Publication/Series
Distinktion
Volume
24
Issue
2
Document type
Journal article
Publisher
Taylor & Francis
Topic
- Human Aspects of ICT
Keywords
- automobility
- autonomous vehicles
- machine learning
- Mobilities
- seamlessness
- senses
- sensors
Status
Published
ISBN/ISSN/Other
- ISSN: 1600-910X