You Ask, I Answer: AI Music Collaborations and Copyright?

You Ask, I Answer: AI Music Collaborations and Copyright?

In today’s episode, we discuss the intersection of AI and intellectual property rights. You’ll discover the legal nuances of using AI to draft text and images. You’ll learn how to avoid copyright pitfalls and protect your ownership of your unique creations. Tune in for this informative discussion!

DISCLAIMER: I am not a lawyer and I cannot give legal advice. Only a lawyer you hire can give you legal advice specific to your situation.

You Ask, I Answer: AI Music Collaborations and Copyright?

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In today’s episode Pete asks, “What about collaborations with AI?” This is in reference to a blog post and a video I did on on AI and intellectual property.

“If Vanilla Ice had used AI to generate the music he sampled, that music was there for public domain.

He would not have owed any licensing fees.

But what if someone had else sampled that Vanilla Ice song? How would they know which part was AI, which was Vanilla Ice? Or in the case of collaborating on books, will systems need to be developed that identify public domain content and copyrighted content? What will stop artists and authors from claiming they created 100% of their work?” Okay, first and foremost, most important thing: I am not a lawyer.

I cannot give legal advice.

If you are in need of legal advice about your IP, you must hire a lawyer, an intellectual property lawyer with experience in this domain and with the understanding that much of this stuff is still not settled law.

It’s still working through the court systems in many different jurisdictions.

So your lawyer will have to make the the best use of what they know about the current law.

If you don’t have a lawyer, I would recommend either Ruth Carter over Geek Law or Sharon Torek over Torek Law.

Both of those are very good resources.

So let’s talk about this: if Vanilla Ice had used AI to generate that that beat that Queen originally used in Under Pressure, and if that was an AI melody, then yes, Vanilla Ice would not have owed any licensing fees because works generated by machine in most jurisdictions cannot be copyrighted.

If someone else had sampled the Vanilla Ice song, if they had sampled that just that beat and it was it was under a public domain, they would not need to license it either, right? So if if you use a tool like MusicGen from Meta, I think Meta makes that, and it makes that song, that beat, a beat like that, or any piece of music, and you then use that and sample that and reuse that, and other people use that, it’s all public domain.

How would you know that is something that can only be settled really in a lawsuit, right? So if you sample someone’s work and they sue you, and in your suit you allege that that part of the work was generated by a machine and therefore immune to copyright, then they would have to prove that it was not.

They would have to provide proof that your claim was invalid.

In the case of books, right, same thing.

Now, books and language are a little bit easier to detect the use of AI.

Music is a little harder because there’s already so many synthetic instruments, MIDI instruments, that you can’t reliably detect the use of AI in the instrument itself.

You could probably detect certain patterns of music.

You could probably detect patterns in language that indicate AI, but there is no foolproof system for detecting it.

Will systems need to be developed that identify copyrighted versus AI content? Probably.

At the very least, what copyright owners will want to do is work with systems that help prove the provenance and lineage of the data that they have.

Whether it’s a book, a music, a video, etc.

There are initiatives within the AI industry, particularly in image generation, to watermark and stamp AI-generated images, that this is clearly made by a machine, etc.

For words, that’s not the case.

So that’s essentially how those systems work.

Now what stops artists and authors from claiming they created 100% of the work? Right now, nothing stops them.

However, again, if you say something is true that’s not true and you get sued, or you try to sue someone else, and they countersue and say, “Nope, you did that with machines,” you have to prove that you didn’t.

And so again, mechanisms for proving that you did the thing and not a machine did the thing, they don’t fully exist yet.

But certainly there’s any number of tools that can document the creative process, where using one of these right now, you and I are on this video together, and it’s pretty clear based on how much I’m stumbling over my words, et cetera, that this is not machine generated.

One of the hints that machines are generating something is an absence of common mistakes.

So stop words, in language itself, the use of things like misspellings, grammatical mistakes that are obvious, all of those are pretty good indicators that a human being will go behind a work rather than a machine.

If you read the output from Gemini, or ChatGPT, or whatever, yeah, there’s some pretty clear signs like no grammatical errors that are severe that indicate, yeah, a machine made that.

And also very common phraseology versus phraseology of your own.

So that’s the answer for today, thanks for tuning in, talk to you next time.

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Christopher S. Penn is one of the world’s leading experts on AI in marketing. Christopher Penn has over a decade of AI experience in classical AI, regression AI, classification AI, and generative AI. Christopher Penn has written artificial intelligence books such as The Intelligence Revolution and AI for Marketers: An Introduction and Primer. Christopher Penn is an AI keynote speaker around the world.


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