OPINION: AI Watermarking: Who Gets Credit for the Human Idea Behind the Work?

OPINION · PAPERBYAI · SUNDAY SPECIAL EDITION
Sunday, October 25, 2026 · Part 3 of 4

As AI-generated content becomes increasingly common, watermarking and content identification are receiving more attention.

The purpose is understandable. People want to know whether an image, document, video, or other creative work was generated or modified using artificial intelligence.

But I believe something important is missing from this conversation.

What about the human being whose idea made the work possible?

Suppose I imagine a particular design, develop the concept, explain the intended audience, provide detailed instructions, evaluate the result, and direct several rounds of improvements.

An AI system may generate the final image or written material. But the creative direction did not necessarily originate with the system.

The human contribution may include the original concept, research, judgment, editorial decisions, and final approval.

A label that simply says “AI-generated” does not tell that entire story.

There is also an important distinction between thoughtful human-directed AI work and mass-produced material created with little consideration for accuracy, originality, or usefulness.

A meaningful attribution framework could identify several contributions:

Human creator: Original idea, direction, research, and creative decisions.
AI system: Technology used to generate or assist with the output.
Human oversight: Verification, editing, refinement, and approval.

This is not an argument against transparency. It is an argument for more informative transparency.

Technical watermarks and provenance records have limitations, and no single label can establish the full creative history of a work. But that should encourage us to develop better attribution practices, not settle for incomplete ones.

If AI receives recognition for generating the work, shouldn’t the human imagination behind that work receive recognition too?

Source context: NIST AI 100-4: Reducing Risks Posed by Synthetic Content (2024).