Home    Number 1, 2022

Affectation, Articulations, Learning: Towards Technoanthropological Symmetrization of Drivers and AVs Bodies

[Affitsiruemost’, artikuliatsii, obuchenie: k tekhnoantropologicheskoi simmetrizatsii tel voditelei i bespilotnykh avtomobilei]

DOI: https://doi.org/10.31857/S0869541522010043

Type of publication: Research Article

Submitted: 11.11.2021

Accepted: 20.01.2022

About author(s)

Mariia Kiseleva | https://orcid.org/0000-0003-1894-6796 | maria.evgenevna@gmail.com | European University at St. Petersburg (6/1a Gagarinskaya Str., St. Petersburg, 191187, Russia)

Keywords

technoanthropology, science and technology studies, actor-network theory, autonomous vehicles, self-driving cars, body, Waymo

Abstract

The article discusses autonomous vehicles (AVs) and considers them in relation to the Body concept of Bruno Latour. It deals with the acquisition of the body of a driver and an autonomous vehicle. I examine the cases of sensors and testing of Waymo. Bodies learn how to be affected and to articulate propositions. Both the human driver and the AV register more and more differences, multiplying articulated propositions. I argue that Latour’s concept is capable of tracing the fluid ontology of human and technological bodies. It allows us to follow the path of symmetrical description of people and technologies, to track the dynamics of bodies and see that they are not fixed. The analysis of such bodies cannot be considered in isolation from the artificially created set-up. Latour’s concept turns out to be relevant for technical and organic bodies.

Funding Information

Российский научный фонд, https://doi.org/10.13039/501100006769 [проект № 20-78-10106]

Citation

Kiseleva, M.E. 2022. Affitsiruemost’, artikuliatsii, obuchenie: k tekhnoantropologicheskoi simmetrizatsii tel voditelei i bespilotnykh avtomobilei [Affectation, Articulations, Learning: Towards Technoanthropological Symmetrization of Drivers and AVs Bodies]. Etnograficheskoe obozrenie 1: 49–67. https://doi.org/10.31857/S0869541522010043

Full text is distributed by eLIBRARY.ru