Why Licensing AI Training is Legally Illogical and Creatively Harmful

The push to license AI training is not just a bad idea. It is a fundamental misunderstanding of how AI works, what copyright protects, and where the real threat to creators lies. If we continue down this path, we will waste time, confuse the law, and leave artists vulnerable to the real harm that AI can cause.

Let me be clear. I do not support licensing AI training. I do not believe AI training violates copyright. And I do not believe the answer to protecting creators is to charge machines for learning. That may sound provocative, but it is legally sound, logically consistent, and ethically necessary if we want a creative future that works.

AI Training is Not Reproduction

AI does not memorize songs. It does not download images. It does not store your video. AI models observe patterns statistically. When AI trains on data, it abstracts certain traits—like melody structure, lyrical themes, cadence, visual framing, and tonal balance—into numerical weights within a vast mathematical model. These weights represent patterns, not copies.

In legal terms, that means AI training does not reproduce a work. Reproduction under copyright law requires that a work be fixed and materially recognizable. AI training does not do that. It studies many things, mixes them, and builds something else. That is transformation, not duplication.

To license training is to pretend that studying is stealing. It is like saying a painter cannot be inspired by other paintings or a student cannot learn from a textbook without paying every author they have ever read. That is not how culture works, and it is not how law is meant to work either.

Training is Transformative Use

Courts have long recognized that transformative use matters. If a new work does something different, adds new meaning, or changes the function of what it uses, it may qualify as fair use. AI training is a textbook example of this. It does not compete with the original. It does not substitute it. It builds a model to generate something new, often using thousands or millions of different sources.

Trying to license AI training under copyright law is like trying to license inspiration. It ignores what copyright was created to protect—the expression of ideas, not the study of ideas.

Licensing Training Harms Creators

Some argue that licensing training would give creators new revenue streams. But this is a false hope. Licensing training does not stop AI from generating synthetic content that mimics your style. It only stops someone from feeding your work into a model—if you can even prove it happened.

The real harm to creators happens when AI generates a voice that sounds like yours, a song that feels like yours, or a style that competes with your identity. That is where exploitation lives. That is where revenue is lost. That is where the law is silent.

Licensing training gives the illusion of protection. It focuses on the input and ignores the output. It locks up access to cultural expression while doing nothing to stop AI from impersonating the very artists it claims to protect.

We Need to Protect Outputs, Not Inputs

The only logical and ethical response to this moment is to create a new legal tool that protects the creative pattern of a human being. Not a single song or photo, but the artistic fingerprint that defines their voice, their style, their identity.

That is why I have proposed Creative Pattern IP. A new category of rights that allows creators to register their unique style as a pattern and receive compensation when AI outputs mimic that pattern. This is not about blocking innovation. It is about building accountability where harm actually happens.

Instead of charging for what AI learns, we should charge for what AI delivers. That is the only place where reproduction and distribution really occur. That is where the market is created. That is where creators deserve protection.

Licensing AI training is a dead end. It is legally weak, technologically flawed, and economically deceptive. It will not stop the exploitation of artists. It will not prevent identity mimicry. It will only slow progress and confuse the law.

We do not need to rewrite copyright. We need to extend it where it ends. We need to face the truth about how AI works. And we need to protect the place where human expression is most at risk—in the outputs, not in the learning.

Creative Pattern IP is the answer. Not because it blocks the future, but because it makes the future fair.