Turning human-AI interactions into music to detect emotion harms

Every AI safety tool on the market detect harmful content and messages against rigid rules. But emotional harm does not show up in one message. It builds quietly over time - user-relative, relational and cumulative, thus cannot be detected by static, rule-based methods.

I replace static methods with dynamic, pattern-based methods - converting the back-and-forth human-AI interactions into sound and music, a tangible signal to be measured over time, so emotional harm can be detectable before it escalates.

Global regulations are already demanding emotional AI safety. For instance, California SB 243 banned engagement-maximising design and required third-party audits, and three other jurisdictions (EU State, EU, China) are all pushing similar rules.
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So my goal at this stage is:**

To build an engine that translates the human-AI interaction's emotional dynamics into sound and music signals, so affective harm patterns like over-attachment, manipulation or isolation become measurable and detectable.