Developing Design Features to Facilitate AI-Assisted User Interactions; Utilizing Actor-Network Theory (ANT) in the Analysis of the TikTok Ban Within the Privacy Landscape

Sharma, Anika, School of Engineering and Applied Science, University of Virginia
Earle, Joshua, University of Virginia
Gerling, Gregory, EN-SIE, University of Virginia

The technical project described provides an interaction design for a data analytics platform that integrates AI assistance within the data searching/ querying process; the design aims to craft a more collaborative experience with AI and help analysts achieve a goal-oriented analysis process. The key features of the design include 1) search category refinement patterns 2) customization of query input format by the user’s technical ability, and 3) context-aware prompt recommendations.
Meanwhile, the STS project utilizes actor network theory to analyze the relations of the role of privacy with the TikTok ban conflict. The different elements of interaction were organized into both human and non-human actors. In this case, the human actors would consist of the government and regulatory bodies that have their own interests and agendas regarding privacy in ensuring compliance with laws and protection of the privacy of citizens. Meanwhile, TikTok’s parent company, ByteDance serves as the central non-human actor since it has the capability to collect, process, and analyze large amounts of data. This, in turn, influences and shapes the way that privacy is observed and practiced. Some other non-human actors could also take the form of the privacy concerns and privacy regulation that form as a result of them. These actors influence government and regulatory bodies by setting the boundaries for data sharing and also influence behavior between the human actors. In terms of the network, there are many ways that the actors shape and influence each other. Analyzing this landscape by segmenting the users by scale including the individual, firm, and nation aided in building a comprehensive dynamic further compounded by the breakdown of individual actors. After all, the precedent set by this decision could change the privacy landscape on all scales for several years to come.

BS (Bachelor of Science)
Privacy, Artificial Intelligence, Mobile Applications

School of Engineering and Applied Science
Bachelor of Science in Systems Engineering
Technical Advisor: Gregory Gerling
STS Advisor: Joshua Earle
Technical Team Members: Stacy Meng, Parker Schell, Anmol Kaur, Ghislain Ventre, Rebecca Dollahite

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