Jiin This project is an experimental web application that explores honesty, effort visibility, and self-representation in study culture through a machine-learning–driven interface. Built using Google’s Teachable Machine, the system allows users to train simple recognition models that register study behaviors (e.g., presence at a desk, head position) as a proxy for time spent studying.
Rather than functioning as a conventional productivity tracker, the project examines how automation and algorithmic measurement shape self-perception and accountability. By making “study time” something that is computationally inferred rather than self-declared, the design surfaces tensions between accuracy, trust, and self-reporting.
The intentionally sparse interface avoids gamification or comparative metrics, positioning the system as a critical design artifact rather than a performance tool. It invites reflection on how AI-driven monitoring can affect motivation, emotional well-being, and the social meaning of productivity—especially when effort becomes legible to machines rather than just people.
OkaytobehonestIonlystudiedthismuchhours.com Application Link