The Rise of AI-Generated Art: Why We Need Legal Protection for Human Artists
“Art is dead, dude. It’s over. A.I. won. Humans lost,” said Jason M. Allen, who won an art prize for his AI-generated artwork (Roose).
With simple prompts, AI can produce incredible artwork using programs trained with billions of images (What is Artificial Intelligence). As an amateur artist myself, I was deeply intrigued by AI, for it enables anyone, regardless of artistic abilities, to create something beautiful. I excitedly entered my prompt, and a gorgeous picture appeared. Compared to the months of work that usually go into my paintings, this one took seconds. While drowning in curiosity and excitement for this new technology, I noticed a vague silhouette of an artist’s signature on the bottom of the image that is neither mine nor the AI’s. I can’t help but start questioning whose signature it is. Was this even my art if the only thing I contributed was a three-word prompt? If not, whose art is it?
AI art functions by creating connections between words and images (Tiernan). When it receives a prompt, it collects and combines images to fit the prompt. However, it fails to comprehend the meaning and origin of the images, let alone create something original. Even the signatures of the original artists are just more meaningless pixels for it to gather and combine. What AI art is currently doing is not emulation to create new pieces but blatant imitation of existing ones. Therefore, faced with ethical issues such as AI appropriating artists’ work without consent and imitating their work, there must be legal solutions to allow AI to flourish while giving credit and compensation to artists.
While AI-generated art is still art, the datasets it uses lack the consent of original artists, making it “a nonconsensual collage of other artists’ work” (YUP). AI text-to-image generators like Stable Diffusion are built on datasets like LAION 5b, which can take almost every image from the internet, including entire portfolios, without proper attribution (Edwards). LAION can accomplish this because, legally, it is a nonprofit organization, but it was funded by the company that created Stable Diffusion (Andersen). The use of such datasets is problematic because it involves the unauthorized use of other artists’ work, which completely disrespects the artists’ consent.
Some argue that AI drawing from datasets is equivalent to artists taking inspiration, but I disagree because AI may lack the transformative aspect of “fair use.” Transformative works add new ideas with a different purpose to the original artwork while acknowledging their sources; they are protected by copyright law under “fair use” (Vincent). However, I believe AI-generated art is simply a recombination or manipulation of existing works without adding significant creative output or giving due credit to the sources, making it not transformative. This is particularly true when AI-generated artwork directly competes with the market for original artists by imitating a particular artist’s style.
For some artists, the emergence of AI poses a highly personal threat to their livelihoods for its ability to replicate their distinct styles. Greg Rutkowski’s situation is a prime example: his artworks were used to train Stable Diffusion without his consent, and now AI has learned his style so effectively that his name has become a mere descriptor for fanciful AI-generated images (Hill). AI undermines the unique value and originality of Mr. Rutkiwski’s work, and his livelihood has suffered as a result. Afterward, Mr. Rutkowski received far fewer jobs, while Stability AI raised $101 million from investors off the backs of artists like Mr. Rutkowski (Roose). As AI-generated art proliferates, human artists are in desperate need of legal protection to ensure their original efforts are not compromised.
Currently, the outdated legal approach of the US Copyright Office guidelines fails to protect artists who face ethical issues surrounding AI (Efthimiadis). Current copyright laws still do not protect computer programs or machine-generated works unless substantial creative input is provided by a human, which creates a serious threat to artists who may have their copyrighted works used without compensation or consent (Kaplan).
In response, artists and organizations have started to challenge the ethics of AI art, urging their respective governments to provide legal solutions. In the United Kingdom, the House of Lords’ Communications and Digital Committee released a report urging the government to take timely action to prevent new technologies from harming the industry, maintain intellectual property rights, and provide financial support for small artists (House of Lords). The stock photography company, Getty Image, is also accusing Stable Diffusion of “brazen infringement of its copyright and intellectual property” for copying over 12 million images from its database “without permission or compensation” (Vincent).
The outcome of these lawsuits remains uncertain, but legal solutions are needed to allow generative AI to thrive while addressing ethical concerns by giving credit and compensation to creators. One possible solution is to treat AI art like music, with licensing agreements that respect copyright (Vincent). If we could combat music piracy concerns in the 2000s by challenging the legality of free music download services like Napster and bringing in content legitimately, then new agreements that respected copyright could be accomplished in the AI art industry (Hill). Another possible regulation is to create databases with no possibility of copyright infringement, like “The Stack,” a dataset that only uses the most permissive open-source licensing and offers developers a way to remove their data on request (Vincent). The Stack’s approach can be adapted to other media, giving consent back to artists by allowing them to opt in or out of AI training.
As the art world grapples with the rise of AI-generated art, one thing is clear: the debate is far from over. While I believe modern artists can embrace AI as a tool like painters did with the invention of cameras, it must happen with respect for current artists and without infringement on their rights. Lawmakers must protect artists’ rights and ensure the ethical use of AI in art, whether through a copyright system like the music industry or an opt-in dataset like “The Stack.”
Works Cited:
Andersen, Sarah. “The Alt-Right Manipulated My Comic. Then A.I. Claimed It.” The New York Times, The New York Times, 31 Dec. 2022, https://www.nytimes.com/2022/12/31/opinion/sarah-andersen-how-algorithim-took-my-work.html?searchResultPosition=5.
Benj Edwards — Sep 15, 2022 9:04 pm UTC. “Have AI Image Generators Assimilated Your Art? New Tool Lets You Check.” Ars Technica, 15 Sept. 2022, https://arstechnica.com/information-technology/2022/09/have-ai-image-generators-assimilated-your-art-new-tool-lets-you-check/?comments=1&comments-page=1.
Hill, Kashmir. “This Tool Could Protect Artists from A.i.-Generated Art That Steals Their Style.” The New York Times, The New York Times, 13 Feb. 2023, https://www.nytimes.com/2023/02/13/technology/ai-art-generator-lensa-stable-diffusion.html?searchResultPosition=2.
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Tiernan, Jonny. “Is Ai Really an Art and Design Killer?” Vectornator Blog, Vectornator Blog, 10 Feb. 2023,
https://www.vectornator.io/blog/will-ai-replace-artists/.
United States, Congress, U.S. Copyright Office, and Rhea Efthimiadis. Copyright Registration Guidance: Works Containing Material Generated by Artificial Intelligence, National Archives, 16 Mar. 2023. https://www.federalregister.gov/documents/2023/03/16/2023-05321/copyright-registration-guidance-works-containing-material-generated-by-artificial-intelligence.
Vincent, James. “Getty Images Sues AI Art Generator Stable Diffusion in the US for Copyright Infringement.” The Verge, The Verge, 6 Feb. 2023, https://www.theverge.com/2023/2/6/23587393/ai-art-copyright-lawsuit-getty-images-stable-diffusion.
Vincent, James. “The Scary Truth about AI Copyright Is Nobody Knows What Will Happen Next.” The Verge, 15 Nov. 2022, https://www.theverge.com/23444685/generative-ai-copyright-infringement-legal-fair-use-training-data.
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