Artikel “Human-Aided Artificial Intelligence” (New Media & Society) ist jetzt Open Access erhältlich

Mein Artikel “Human-Aided Artificial Intelligence: Or, How to Run Large Computations in Human Brains? Toward a media sociology of machine learning” ist in der Zeitschrift New Media & Society 22(10), 2020, erschienen – und jetzt auch Open Access zugänglich. [PDF]

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.

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1. 

   Mühlhoff, Rainer. 2020. „Human-Aided Artificial Intelligence: Or, How to Run Large Computations in Human Brains?“ New Media & Society 22 (10): 1868–84. doi:10.1177/1461444819885334.

   Full text academia.edu bibtex

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   @article{Mü2020:NMS,
     author = {Mühlhoff, Rainer},
     title = {Human-Aided Artificial Intelligence: Or, How to Run Large
     		Computations in Human Brains?},
     subtitle = {Towards a Media Sociology of Machine Learning},
     journal = {New Media \& Society},
     year = {2020},
     volume = {22},
     number = {10},
     pages = {1868–1884},
     doi = {10.1177/1461444819885334},
     web_group = {papers},
     web_academia = {https://www.academia.edu/40263575/Human-Aided_Artificial_Intelligence_Towards_a_Media_Sociology_of_Machine_Learning._Or_How_to_Run_Large_Computations_in_Human_Brains},
     web_fulltext = {https://journals.sagepub.com/doi/full/10.1177/1461444819885334}
   }