Human-Aided Artificial Intelligence: Or, How to Run Large Computations in Human Brains? Towards a Media Sociology of Machine Learning

New Media and Society 1 (2019)
  Copy   BIBTEX


Today, artificial intelligence, 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 discrimination of users.

Author's Profile

Rainer Mühlhoff
Technische Universität Berlin


Added to PP

514 (#19,293)

6 months
58 (#28,373)

Historical graph of downloads since first upload
This graph includes both downloads from PhilArchive and clicks on external links on PhilPapers.
How can I increase my downloads?