Political machines: a framework for studying politics in social machines

Author:

Papakyriakopoulos Orestis

Abstract

AbstractIn the age of ubiquitous computing and artificially intelligent applications, social machines serves as a powerful framework for understanding and interpreting interactions in socio-algorithmic ecosystems. Although researchers have largely used it to analyze the interactions of individuals and algorithms, limited attempts have been made to investigate the politics in social machines. In this study, I claim that social machines are per se political machines, and introduce a five-point framework for classifying influence processes in socio-algorithmic ecosystems. By drawing from scholars from political theory, I use a notion of influence that functions as a meta-concept for connecting and comparing different conceptions of politics. In this way, I can associate multiple political aspects of social machines from a cybernetic perspective. I show that the framework efficiently categorizes dimensions of influence that shape interactions between individuals and algorithms. These categories are symbolic influence, political conduct, algorithmic influence, design, and regulatory influence. Using case studies, I describe how they interact with each other on online social networks and in algorithmic decision-making systems and illustrate how the framework is able to guide scientists in further research.

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Human-Computer Interaction,Philosophy

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

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