The Privacy Bill Comes Due Before the Real Model Arrives: Field Constraints of Emotion-Guard, a Kindergarten Emotion-Recognition Demo

Author: Guangyi Zhao 1. The problem Emotion-Guard is my open-source demo of an idea that came out of real work: run emotion recognition in a kindergarten, watch for sustained negative mood, and nudge a teacher to check in on a child before distress turns into an incident — or before a stressed adult does something worse. The motivation is protective. The subjects, however, are three to six years old. They cannot consent; their parents sign for them; and the record being created is about their faces and their feelings, accumulated day after day. This article is not about making the model more accurate. There is no real model yet — the only classifier that runs in this repository is a simulator. What I did instead was audit the code line by line and run it, end to end, on synthetic data, asking a more basic question: what does this system already owe, in deployment terms, before accuracy even enters the picture? Four small things turned out to carry the weight: how often