Please use this identifier to cite or link to this item: http://dx.doi.org/10.14279/depositonce-11329
For citation please use:
Main Title: Human-aided artificial intelligence: Or, how to run large computations in human brains? Toward a media sociology of machine learning
Author(s): Mühlhoff, Rainer
Type: Article
URI: https://depositonce.tu-berlin.de/handle/11303/12510
http://dx.doi.org/10.14279/depositonce-11329
License: https://creativecommons.org/licenses/by-nc/4.0/
Abstract: Today, artificial intelligence (AI), especially machine learning, is structurally dependent on human participation. Technologies such as deep learning (DL) leverage networked media infrastructures and human-machine interaction designs to harness users to provide training and verification data. The emergence of DL is therefore based on a fundamental socio-technological transformation of the relationship between humans and machines. Rather than simulating human intelligence, DL-based AIs capture human cognitive abilities, so they are hybrid human-machine apparatuses. From a perspective of media philosophy and social-theoretical critique, I differentiate five types of “media technologies of capture” in AI apparatuses and analyze them as forms of power relations between humans and machines. Finally, I argue that the current hype about AI implies a relational and distributed understanding of (human/artificial) intelligence, which I categorize under the term “cybernetic AI.” This form of AI manifests in socio-technological apparatuses that involve new modes of subjectivation, social control, and digital labor.
Subject(s): artificial intelligence
audience labor
commercial content moderation
cybernetics
deep learning
human computation
human-computer interaction
social media
tracking
training data
user experience design
Issue Date: 6-Nov-2019
Date Available: 21-Jan-2021
Language Code: en
DDC Class: 600 Technik, Technologie
Journal Title: New Media & Society
Publisher: SAGE
Volume: 22
Issue: 10
Publisher DOI: 10.1177/1461444819885334
Page Start: 1868
Page End: 1884
EISSN: 1461-7315
ISSN: 1461-4448
Notes: Dieser Beitrag ist mit Zustimmung des Rechteinhabers aufgrund einer (DFG geförderten) Allianz- bzw. Nationallizenz frei zugänglich.
This publication is with permission of the rights owner freely accessible due to an Alliance licence and a national licence (funded by the DFG, German Research Foundation) respectively.
TU Affiliation(s): Fak. 5 Verkehrs- und Maschinensysteme » Inst. Werkzeugmaschinen und Fabrikbetrieb » FG Wissensdynamik und Nachhaltigkeit in den Technikwissenschaften
Appears in Collections:Technische Universität Berlin » Publications

Files in This Item:
10.1177_1461444819885334.pdf
Format: Adobe PDF | Size: 571.72 kB
DownloadShow Preview
Thumbnail

Item Export Bar

This item is licensed under a Creative Commons License Creative Commons