MUSE Silver

2026

Five to the Fifth

Entrant

ShanghaiTech University

Category

Student Submission - Student Experiential Design

Client's Name

Country / Region

China

Five to the Fifth is an interactive installation that examines how everyday emotions and behaviors become labeled as “conditions” within the context of social media and big data.
In recent years, terms such as claustrophobia, trypophobia, impostor syndrome, emotional numbness, or freeze response have become widely circulated online. Many of these experiences were not historically understood as illnesses, yet through repetition and categorization, they are increasingly framed as diagnosable states. On social media, posts like “Behaviors you thought were normal but are actually symptoms” invite users to recognize themselves, comment, and move on—turning diagnosis into casual content.
Five to the Fifth simulates this phenomenon through an AI-driven question-and-answer system. Participants respond to five questions using weighted physical blocks representing a scale from strongly disagree to strongly agree. These physical actions are translated into data signals, processed by the system, and rendered as a diagnostic report containing a condition label, symptoms, and suggested prescriptions.
The physical form of the installation is conceptually informed by traditional Chinese medicine, particularly its diagnostic approach based on observation, inquiry, and interpretation, as well as the practice of weighing and prescribing. Rather than seeking objective truth, both systems construct meaning through accumulated signs and judgments—whether bodily or behavioral.
The installation does not aim to determine whether participants are truly ill. Instead, it reflects how data-driven systems interpret behavior, infer emotional tendencies, and assign meaning without explicit consent. By transforming diagnosis into a tangible ritual, Five to the Fifth invites participants to reflect on how easily personal experience becomes data—and how data, in turn, becomes diagnosis in the age of algorithmic profiling.

Credits

ShanghaiTech University
Yijia Zhong
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