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Specification

What is Human Quotient?

Human Quotient (HQ) is a 0-10 measure of how much human effort, intention, and craft went into creating a piece of content. It is not an AI detector. It is not a quality score. It is a shared vocabulary that lets creators and audiences communicate honestly about how content was made.

The Problem

In a world where AI can generate prose, images, music, and code in seconds, "is this AI-generated?" is the wrong question. The right question is: how much human effort and intent shaped this output?

A writer who drafts a personal essay by hand and spends two weeks revising it has a different HQ than someone who prompts an AI and accepts the first output. Both are content, and either may be well-written, but they describe different production processes. But they differ in what went into making them — and that difference matters to audiences, to platforms, to publishers, and to the creators themselves.

The Contract

HQ is a contract between creator and audience. The creator declares how the work was produced and what role tools played. The audience can use that information to set its own expectations. It is not a quality judgment — it is an expectation-setting tool.

HQ 0: "This was generated. I'm sending it but I'm not owning it."
HQ 10: "I wrote this. Every word. You better read it."
The gray area (2-7): Where most content lives. How much human input shaped the output?

The Core Principle: Creation, Not Tools

HQ measures whether the act of creating content was outsourced to AI — not whether AI was used at all.

If you ask AI to do research for you, and you read that research and write the piece yourself, that does not affect your HQ. Research is not creation. Using AI for research is like going to the library.

If you ask AI to do research, and it synthesizes that research into written output without giving you the raw material — if it writes it — then that has affected the human quotient. The act of creation was outsourced.

The line: did AI participate in the act of creating the content, or did it merely assist the human who was creating it?

The Scale

Each level describes a specific relationship between human effort and AI involvement in the creation process. The score is self-declared — the writer knows their own effort. Click any level for the full description, examples, and embed badge.

The Spectrum

People use, limit, or avoid AI for different reasons, and those choices can vary from one piece of work to another.

Some work is created directly without AI. Some work incorporates AI at different points in the process. Much work falls somewhere between those descriptions. HQ records the process used for a particular work; it does not infer a preference, identity, or principle from the score.

HQ is neutral: it is neither anti-AI nor pro-AI. Pro-honesty.

What HQ Is Not

Not an AI detector. AI detectors look for statistical markers of generation. HQ looks for markers of humanity. A piece can be AI-generated and still score high on HQ if a human shaped it substantially.
Not a quality score. A piece can be well-crafted and have a low HQ. A piece can be rough and have a high HQ. HQ measures how it was made, not whether it's good.
Not a binary judgment. HQ is a spectrum. Most content lives in the middle — humans using tools, as they always have.
Not a legal framework. HQ does not determine copyright, ownership, or legal obligations. Courts and legislatures will sort those out separately.
Not a gatekeeping tool. HQ is descriptive, not prescriptive. It tells you what's there; it doesn't tell you what to do about it.

Self-Declared

The primary mode of HQ is self-declared. The writer is the one who knows how much effort they put in. The writer is the one making the contract. External verification (signed tokens, public registries) exists for contexts where the contract needs to be enforceable — but the primary mode is honesty between writer and reader.

Open Questions

Who scores? Self-declared by the creator, verified by a service, or a hybrid? Currently: self-declared, with verification available for enterprise contexts.
Transparency: Should scores be visible to audiences, or a behind-the-scenes signal for content owners? Both — the creator chooses.
Portability: Does the same scale apply to text, images, music, and code? The current rubric is text-focused; other media will follow.
Gaming resistance: How do we prevent people from optimizing for HQ? Anti-gaming architecture includes verifiable tokens, content hashing, and adversarial testing.
Context dependence: An HQ 3 work email is normal. An HQ 3 personal letter might feel cold. The score is information, not judgment.