The same message builds trust with one audience and breaks it with another. That variation has structure.

Humor Genome is a research program that maps how audiences interpret the same message differently, and turns that variation into something you can measure and design for.


The Model

Audience-dependent meaning

Most communication models treat meaning as something a sender encodes and a receiver decodes. When a message fails, the explanation is usually noise, ambiguity, or poor targeting. But the pattern we keep seeing is different: the same message, delivered identically, produces structurally different interpretations across audiences. Not random noise. Predictable divergence.

Humor Genome starts from that observation. We treat interpretation not as a property of a message, but as a function of the relationship between a message and its audience. The same joke kills in one room and dies in another, not because one room "got it" and the other didn't, but because each room brought a different interpretive frame to the same material.

The research program maps these frames. We identify the structural features of messages that make them flexible (landing across many audiences) or brittle (only working for one). We model the audience variables that predict divergence: shared references, status dynamics, emotional priors, cultural context. And we build instruments that make these patterns visible in real time.

Comedy is the proof surface because laughter is the fastest, most measurable signal of interpretation we have. A laugh is a binary, involuntary event. Silence is equally legible. This makes live comedy the highest-bandwidth environment for studying how meaning shifts across listeners.


The Program

What we're investigating

The research program operates through a pipeline. Sponsors fund research themes here at Humor Genome. Those themes are investigated through live performances, hackathons, and experiments at Midtown Show. Systems generated by the lab ship on sound.fan, where partners take them further.

Interpretation Divergence
Why the same message builds trust with one audience and fails with another. Measuring alignment, disagreement, and the shape of audience splits.
Persona Modeling
Defining and simulating distinct audience types. What different groups pay attention to, react to, and optimize for when they interpret the same input.
How It Lands
Real-time observation of audience reactions as content unfolds. Live environments like Room Sense where interpretation is simulated, measured, and compared across audience types in the moment.
Meaning Structure
The internal architecture of an idea that determines how it can be interpreted. Mapping the structural features that make some messages flexible across audiences and others brittle.
Decision Surfaces
How interpretation affects downstream decisions. When a message triggers trust, action, hesitation, or rejection across different evaluators.


Who's Building This

Michi Yamamoto

Michi Yamamoto builds systems that make audience perception visible. His background spans comedy production, software engineering, and AI research, a combination that produced Midtown Show, Room Sense Live, and dozens of hackathon builds exploring how different audiences read the same signal. Humor Genome ties this work into a single research question: how does meaning shift across listeners, and how can we design for it?