Artists and Hackers

A Podcast On Art, Code and Community




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Apr 30th, 2024

Ep. 24 - From Monkey Selfies to Machine Learning: Generative Art and the Public Domain



In our final episode of the season we reconnect with Michael Weinberg, Director of the Engelberg Center on Innovation Law and Policy, for the recent legal cases revolving around generative AI models and the continuing impact of the monkey selfie legal case.


Machine Learning
Public Domain

This episode is the final one of the season in collaboration with the Engelberg Center on Innovation Law and Policy at NYU Law. This season we’ve talked to lawyers, artists and other scholars who have helped us unpack some of the thorny issues for those working in art and code as they unleash their work into the world.

When we first began our research for the season we started by speaking to Michael on a range of legal issues pertaining to creators and artists working today. Then I asked what I thought was a straightforward question and was amazed at the response. I asked Michael about generative AI, and especially things like artwork created through machine learning algorithms. It was at that point that I first learned of the Monkey Selfie Copyright Dispute.

In our previous episode Michael explained to me that the courts had ruled that works that are not created by a human cannot be copyrighted. And furthermore, that the U.S. Copyright Office had advised that this legal case would impact work created with generative A.I. When I first learned this, I was surprised and intrigued. Since that previous interview, Michael got back in touch to let me know that we finally had further legal cases relating to generative A.I. that specifically cite the monkey legal case as precedent. We revisit our earlier conversation then catch up with Michael for an update on these recent cases.


Michael Weinberg is the Executive Director of the Engelberg Center on Innovation Law and Policy at the NYU School of Law. His research centers on open source, open access, and innovation. He is also the Co-Director of the glam-e lab, a project that uses direct representation to develop model policies and terms for cultural institutions that are creating open access programs.

Copyright Registration Guidance: Works Containing Material Generated by Artificial Intelligence

US Copyright Office on Zarya of the Dawn

Thaler vs Perlmutter


This season of the podcast was produced with the Engelberg Center for Innovation Law and Policy at NYU.

Our host is Lee Tusman. Our audio production is by Max Ludlow.

All of the music on today’s episode are by our audio engineer Max Ludlow. The tracks are Body Memory, Poole and Relic, CC BY.

This episode is licensed under CC BY 4.0

From Monkey Selfies to Machine Learning: Generative Art and the Public Domain

Lee Tusman
You’re listening to Artists and Hackers, a podcast on art, code and community. We talk to programmers, artists, poets, musicians, botmakers, students and now legal scholars in an effort to look at online artmaking and a history of technology and the internet. We’re interested in where we’ve been and speculative ideas on the future.

Today’s episode is with Michael Weinberg, the Director of the Engelberg Center on Innovation Law and Policy at NYU. In our earlier episode, we covered a range of legal issues pertaining to creators and artists working today. Then I asked what I thought was a straightforward question and was amazed at the response. I asked Michael about generative AI, and especially things like artwork created through machine learning algorithms. First we’ll listen to our earlier conversation on the topic, then I’ll come back and speak with Michael again, for an update on the latest legal issues in generative art.

So one of the strange things that’s happening is artists and software writers, programmers and other people are making tools that are used to make artwork. Let’s say I make a tool, maybe I make some new kind of digital painting software, or I write a machine learning library that others can use to generate poetry or plays or dances. What are some of the structures around what I can kind of specify in terms of who uses that software to make artwork. If I make this tool to make digital paintings, do I own the digital paintings that other artists that use my software make? Is there any restrictions on the work that they make or that I can even say about what they make with my software?

Michael Weinberg
First off, owning the copyright in a tool does not necessarily or automatically give you ownership in the things that are made with the tool. If I type something in Microsoft Word, if I write a book in Microsoft word, Microsoft does not own my book. Now we’re using podcast recording software to record this interview. The company that makes the software to record the interview does not own a copyright in the podcast. Or the company that makes the editing software you use to edit everything together and and remove all of my ums and stammers does not own the output, the thing that you create with the tools. Now that distinction can feel like it breaks down a little bit when you have some of these, especially some of these machine learning-based tools that feel like instead of a person using the tool to create a work it’s kind of the tool doing all of the work itself and there isn’t really a person involved. There’s a little bit of debate, I mean there’s a little bit of debate in legal world as to what should happen in that case. I think the best answer and the answer that has been the case up until now and probably will continue to be the case for the foreseeable future is that you need a person to have a copyright. And so if it is actually true that just a robot made whatever the work is, that’s great. The work exists in the world but the robot doesn’t own the copyright. And this is actually very similar to a case that was high profile or at least high profile in copyright legal nerd world a couple years ago where it was called the “monkey selfie case” and it was a situation where there was a picture that went viral on the internet. And the story of the picture was that some monkeys had stolen a photographer’s camera out of his bag and taken a bunch of pictures of themselves because they were… or they’d come up to a camera because they were seeing their reflection in the lens and they were kind of fascinated with it and so they were they were taking pictures of themselves basically. And so it went viral. The pictures were very cute. And then the photographer tried to assert copyright over the pictures. And the court, and ultimately this is the copyright office, has put this in their big book of copyright rules, it’s called the Compendium of Copyright. The monkeys took the picture, but monkeys aren’t people and so monkeys can’t have copyright. And so it feels like monkeys taking selfies is very different from an elaborate AI machine learning algorithm generating art. But I think the principle was the same which is you need a person involved in order to be able to have a copyright in the first place. And there are lots of good reasons for that. One of which is if you want to use that photograph or the image or whatever it was generated, you need a license from somebody. And you know a monkey can’t give you a license, can’t enter into a licensing agreement. A robot can’t enter into a licensing agreement. So there just needs to be a person for the system to work at all.

What about the person that wrote the robot software or… I guess I’m trying to push at the limits here. I’m trying to figure out where does that end and the robot begins.

Yeah, right? I mean this is a good question. And I think it becomes a little bit of a fact specific question. If the person who wrote the software is really the driving creative force behind the output then you can probably argue that the person who wrote the software is sort of working all the way through the process. If you can really draw a straight line between the person who wrote the software and the output then maybe there’s an argument for that. But in that case, the the software isn’t really a tool in the sense that you know a word processor is a tool, right? It’s more kind of part of the work that they are doing, and it’s a tool being manipulated by the creator as as she’s creating it. potentially if the creator, if someone creates a tool and then someone else comes along and uses the tool to achieve some sort of creative output, in that case, it probably is the case that that person who’s using the tool is providing the creative spark and so maybe they’re the person who should own the copyright and you can make up hypotheticals that really kind of finally, that draw really fine distinctions here and those hypotheticals will probably pop up in reality over the next couple years. But I think you still get to a situation where the fundamental question is, who is the person who is ultimately responsible for the creative spark behind this specific work?

And that’s where we left off with monkey selfies and generative art in episode 20 when I spoke to Michael last year. But recently he let me know that we finally have legal cases playing out in courts pertaining to the monkey selfie case. Ever since I’d last spoken to him I had brought up the story to family and at parties, I’m pretty sure my friends are sick of hearing about it. But now, the monkey selfie case is back in the news, at least legal news, just as predicted. So I spoke again with Michael, to find out the latest.

So I think the good news is that everything that we talked about earlier is still correct and everything we talked about is still right, and these these questions that we were talking about of the line between when the human is the creator and when the monkey or the AI or the machine is the creator are still really important questions and really key questions. And the thing that has changed since we last talked is that we’ve actually seen in the US, the US Copyright office weigh in on some attempts to register copyrights for works that were created either by AI or in collaboration with AI and so it gives us a little bit more context. It makes the hypotheticals a little bit more concrete to understand how the lines are drawn.

And what are some examples of these?

So there are two high profile examples. One is an example where someone tried to register a picture that they said was made by their AI program, a generative AI program. And so they wanted to register the picture, and the author they wanted to be the generative AI program itself. So not someone who said I made this by prompting generative AI and therefore I want to be to owner of the copyright, but someone who said I think the robot is the author 100% and the copyright office said no. Robots cannot be the authors. AI cannot be authors. You need a person in the process, touching on that monkey selfie case that we talked about before. And so it’s clear right now that the copyright of the US copyright office position is that AI, and you know robots or software alone cannot be the creator of a copyright protected work. It can create paintings but those paintings, or anything else, don’t get copyright protection. They’re just right now, they’re just in the public domain.

And can you say a little bit more about that? Did they explicitly state that that’s the case or just because it’s not possible to copyright them we or lawyers understand that to mean that it’s in the public domain?

Yeah, I mean they rejected the registration. They said it’s not eligible for copyright protection. This is now being litigated. The person who submitted the work, the painting, is someone who is I think it’s safe to call him a kind of an activist who has tried to have his computer programs get patents in the past. he’s someone who really wants his software to have the full scope of creative ability within the law and so the copyright office was very explicit. They rejected the registration. They said that there is no, there’s no human creator and so this is not eligible for copyright protection. The person who tried to do it sued and appealed that and it’s now kicking around the appellate court. But it’s been very explicit, if we’re just talking about generative AI there’s no human and so there’s no human to own the copyright. No one owns the copyright in the work.

Does that have implications for how people use things like Dalle?

I think it does. I think they’re really potentially very interesting because what it suggests pretty explicitly is that the works coming out of Dalle are not eligible for copyright protection, the works coming out of Dalle are in the public domain. And so right now we have this situation where we haven’t had for like a century where brand new works are entering the public domain directly. They’re not being protected by copyright for any period of time. They’re just generally available to anyone to do whatever they want with.

That’s incredible! And I’m curious what the second legal case is that you had mentioned?

So the second legal case was a little bit more nuanced. This was someone who had made a graphic novel and they had written the novel themselves but they had basically turned to Dalle or one of the other generative AIs to create the images in the graphic novel. And they had registered the graphic novel itself and there was a little bit of back and forth but eventually the copyright office rejected copyright registrations for the images. So the copyright office said you the person did a lot of work. The generative AI was also very involved, but the generative AI doesn’t get to be a co-author from a copyright standpoint. But you as the person who wrote the book, you own the book. And also if you think of the book, a graphic novel as a compilation, a thing that combines the text and those images. Those images are positioned on the page a specific way. They’re kind of ordered in a specific way. That entire work, you can be the sole author of, but you can’t claim copyright in the images themselves. And the AI doesn’t get copyright in the images themselves either. And so if someone else wants to come along and copy the entire book they’ll be infringing on the author’s copyright. But if you take the images alone out of that graphic novel, those are not protected by copyright. Those are in the public domain. So this case is a little bit more of an example of that kind of collaborative approach that we had touched on. But it’s still, you get in the same place, right? The parts of the creativity that the person was directly involved with, those are eligible for copyright protection. The parts where it’s mostly generative AI, those are not eligible for copyright protection. And I think what we’re going to see over the next couple months and years is where that line is between, you know the human parts and the generative AI parts.

Well that’s fascinating. Michael thank you so much for updating us. I appreciate it.

Thank you so much.

This was our final episode of the season, which was made possible by support from the Engelberg Center on Innovation Law and Policy at NYU. Prior to this season, I had a more limited knowledge of the legal issues we covered this season, despite working in new media art and music for a long time, and I thought that other folks would want to learn more as well. While we’ve only scratched the surface, we hope to cover more of these areas going forward, not only because new ethical, social and legal issues constantly come up when working with new technology, but also because they of course suffuse our society overall.

I was genuinely surprised by the monkey selfie legal case, especially when Michael first presented the idea, that a guidance relating to a monkey that cannot legally hold a copyright could be the key to interpreting legal decisions based on algorithms. So I was surprised again when Michael said this decision had been upheld and the implication was that new generative works created through these kinds of machine learning algorithms are new works, are considered to be in the public domain. Especially since we covered the public domain in episode 22 where we spoke with Brewster Kahle from the Internet Archive where he spoke about the law of copyright being automatically applied to almost all works, for 70 years after a creator’s death, unless an author explicitly waives or grants exemptions.

In my first interview with Michael, he ended our conversation with an idea that has stuck with me. He said, “when you’re making decisions, try and empower the good users and not spend a lot of time trying to limit the bad faith users. Think about who you want to be using this and how you want them to be using it and put in place the licensing structure that allows them to do it.”

When speaking with Dr. Jane Anderson and with Courtney Papunee in episode 23 I was inpsired by the innovative creation and testing by Local Contexts, which grows out of needs of indigineous and local communities where they’ve been ignored or mistreated by unsupportive laws. It’s an example of how communities are working to ensure their culture, community, heritage, even their data are used or presented respectfully.

Local Contexts, and initiatives like Creative Commons, free and open source and ethical open source licenses, are genuinely exciting, important tools, that I hope will strengthen artists and creators work and help lead to the creation of healthy and supported creative communities.

If you have a response to this episode or the season as a creative practitioner, researcher or scholar, or are working on new initiatives, licenses and tools, please get in touch to let us know about it.

This season of the podcast was produced with the Engelberg Center at NYU Law. My name is Lee Tusman and our audio producer is Max Ludlow. Our designer is Caleb Stone.

All of the music on today’s episode is by our audio engineer Max Ludlow with the tracks Body Memory, Poole and Relic.

You can find full episodes, transcripts and links to find out about our guests and topics on our website You can find us on mastdon at artistsandhackers at and you can always write to us on our website. Please leave us feedback wherever you get your podcasts. Thanks for listening.