Abstract

During the last decade, social online networks (SON) have gained enormous relevance and they contributed to the diffusion of the Internet in broad social strata. The attraction of social online networks is rooted in “social” functions, such as personal connections and information exchange. But SON are also shaped by several “automated” functions and processes, often based on algorithmic selection.

Content and profiles on SON are subject to monitoring, scoring, recommendation, forecasting and automated transactions. The spectrum of algorithmic-selective applications on social networks encompasses personalized news feeds, trending topics, search- and autocomplete functions, computational advertising, contact recommendations, reputation scorings, identification and filtering of undesired content (e.g., pornography, spam, fake-news). Moreover, social online networks are subject to automated usage activities by chatbots, clickbots and targeted automated placement of information and advertising. Finally, SON supply data and information which serve as input for automated surveillance, recommendations, and third party decisions, e.g., in areas such as social scoring and credit scoring. 

The increasing diffusion of algorithmic selection on social online networks is accompanied by risks like violations of privacy and property rights, manipulation, bias, discrimination, growing heteronomy and a loss of individual self-determination. The project emphasizes applications and implications of the automation in social online networks. It therefore identifies the usage, benefits and the risks of algorithmic selection in SON. On this basis, the project explores the technological and organizational governance measures that are implemented by the providers of social networks to counter risks and problematic developments. Can technically induced problems be solved by technical governance measures such as governance-by-design and artificial intelligence?

Funding

The project is funded by the Vienna Anniversary Fund for the Austrian Academy of Sciences.

Staff

Florian Saurwein (CMC, Project leader)

Jaro Krieger-Lamina (ITA)

Charlotte Spencer-Smith (CMC)

Cooperation partner

Institute of Technology Assessment (ITA) of the Austrian Academy of Sciences