Learning by Crashing

Autonomous Cars and the Future of the Accident

in Transfers
Author:
Florian Sprenger Professor, Ruhr-Universität, Germany florian.sprenger@rub.de

Search for other papers by Florian Sprenger in
Current site
Google Scholar
PubMed
Close
Restricted access

Abstract

This text explores how the introduction of (semi)autonomous cars fundamentally transforms traffic accidents. Using examples of recent crashes, the article examines how edge cases, accidents, and machine learning are intertwined and produce “infrastructural violence.” Following the example of the suspension of Cruise in 2023, the text investigates edge cases, which may not coincide with actual collisions but necessarily raise their probability, because they enable constant optimization through machine learning. I argue that it is therefore necessary for mobility studies to go beyond existing frameworks in order to investigate the epistemology of accidents of self-driving cars and to scrutinize the transitions from human perception to big data, machine learning, and sensor-based world modeling.

Contributor Notes

Florian Sprenger is professor for virtual humanities at the Department of Media Studies at Ruhr-Universität Bochum. His research covers the transformations of digital cultures, the history of artificial environments, and the virtuality of machinic worldmaking. Email: florian.sprenger@rub.de

  • Collapse
  • Expand

Transfers

Interdisciplinary Journal of Mobility Studies

Metrics

All Time Past Year Past 30 Days
Abstract Views 499 499 430
Full Text Views 52 52 42
PDF Downloads 20 20 10