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The Training Wheels are Off: The Copyright Implications of Training Generative AI

By Marc J. Rachman of Davis+Gilbert LLP, Sarah Benowich of Davis+Gilbert & Eva M. Jiménez of Davis+Gilbert on March 22, 2023
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With the introduction of several readily available applications, artificial intelligence (AI) has leaped into the mainstream and brought with it a host of legal questions. 

Following the release in November of the now popular generative AI platform ChatGPT by OpenAI, companies including Microsoft and Google are rushing to release their own generative AI services or integrate them into their existing offerings. With a growth in attention-grabbing AI antics, like actor Ryan Reynolds using ChatGPT to craft, in his words, a “mildly terrifying” ad for Mint Mobile, companies are increasingly contemplating how AI will change the nature of work. 

AI’s myriad of applications all depend on the strength and quality of the algorithm, which relies on training data. Several recent, high-profile lawsuits raise the issue of whether such training algorithms violate copyright law’s restrictions on creating derivative works without the creators’ consent.

What is Generative AI?

Falling within the broad category of AI and machine learning, generative artificial intelligence (GAI) refers to algorithms, such as ChatGPT, DALL-E and Stable Diffusion, that can interpret text prompts to generate new content. The content can include images, text and software code based on data on which the algorithm was “trained.” These models work by interpreting an input — for example, text prompts such as: “write a 500-word blog post about AI” or “design an image of a cat in a hat in the style of Picasso” — and generating a new output based on the training data. This singular output is one of the contrasts between GAI and typical searches on Google or Bing, which point to various links to different possible answers rather than generating a singular output based on the merging of different inputs.

To create and refine these outputs, GAI must be “trained” on massive data sets, such as images, sentences or sounds. That “data” typically includes other creators’ copyrighted material.

What is a Derivative Work?

Training data implicates, among other things, the Copyright Act’s limitations on creating derivative works, one of the exclusive rights that the Act grants to copyright owners. Title 17, section 101 of the Act defines a “derivative work” as any work “based upon one or more preexisting works.” Common examples of derivative works, according to the Copyright Office Circular 14, include “translations, musical arrangements, motion picture versions of literary material or plays, art reproductions, abridgments, and condensations of preexisting works.” To prepare a derivative work without being considered an infringing work, the new creator would need authorization from the original copyright holder, and copyright protection would extend only to new elements or changes (or the new creator would need to establish that their work is protected under the fair use doctrine).

GAI algorithms would appear, by their very nature, to run the risk of violating copyright holders’ exclusive rights: existing works are fed to the algorithm, which then generates a new work based on those preexisting works. If the algorithm acquires these works without obtaining the rights holder’s consent, and the use does not fall within the fair use protections of the Copyright Act, then it could potentially be found to have infringed on those holders’ copyright rights.

Two Recent GAI Cases

Two recent cases highlight potential copyright issues implicated in the use of GAI tools. 

Andersen et al. v. Stability AI Ltd. et al.

The first, Andersen et al. v. Stability AI Ltd. et al., concerns three artists who filed a proposed class action in California federal court against Stability AI, Midjourney and DeviantArt, all of which released GAI art tools based on Stable Diffusion, an image-generation program created by Stability AI. The artists claim that Stable Diffusion was trained on a dataset of hundreds of millions of copyrighted images and their captions, which were copied and scraped from web pages like Getty Images, Shutterstock and Adobe Stock, and other sources without image owners’ or website operators’ consent. 

The plaintiffs argue that Stable Diffusion amounts to nothing more than a “21st century collage tool.” The artists claim that any resulting image that draws upon copyrighted material is an infringing work and that the derived images compete in the marketplace with the original images, as they allow a user to create derivative works “in the style” of a particular artist without compensating the artist. The plaintiffs note that works generated by Stable Diffusion in the style of certain artists can be found for sale online. 

Although Stability AI publicly denied any infringement of artists’ work, it announced on Twitter that it will allow artists to opt-out of the training data set for Stable Diffusion’s next release. 

Getty Images (U.S.), Inc. v. Stability AI, Inc.

In Getty Images (U.S.), Inc. v. Stability AI, Inc., photograph image bank Getty Images also sued Stability AI. The lawsuit, filed in Delaware federal court, accuses Stability AI of scraping at least 12 million copyrighted images — along with their associated text and metadata — from Getty Images’ websites to train the Stable Diffusion model. Getty asserts that the Getty Images website terms and conditions expressly prohibit downloading or re-transmitting website contents without a license and using data mining or similar data-gathering methods.

Getty also claims that Stable Diffusion frequently produces images that are highly similar to and derivative of Getty’s proprietary content, and at times even regenerates specific images that were used to train the GAI model. 

Despite Stability AI’s attempts to remove the Getty Images watermark from proprietary images, Getty states, some of the output images generated by Stable Diffusion still contain distorted versions of the Getty Images watermark.

  • The watermark, which is usually incomplete but reminiscent of the original mark, not only infringes on Getty’s copyright, but also falsely implies an association between Stable Diffusion and Getty Images, raising concerns of trademark infringement as well. 
  • Moreover, Getty argues, because Stable Diffusion often produces images that are “bizarre” or “grotesque,” the incorporation of the Getty Images mark tarnishes Getty Images’ reputation, giving rise to a claim for trademark dilution. 

Stability AI, Getty claims, is aware that its program produces images including the Getty watermark, but has done nothing to prevent the issue from recurring. 

The Bottom Line

  • Two pending lawsuits are among the recently filed cases that will test how copyright law will be applied to AI.
  • Given the novelty and rapidly evolving nature of GAI, individual creators and companies using GAI need to tread carefully to avoid claims of infringement and to protect their IP.
  • As this is an emerging issue, stay tuned for more Davis+Gilbert alerts on the use of GAI and best practices recommendations.
Photo of Marc J. Rachman of Davis+Gilbert LLP Marc J. Rachman of Davis+Gilbert LLP

Marc Rachman, a partner in the Litigation + Dispute Resolution and Intellectual Property + Media Practice Groups, focuses on intellectual property (IP) counseling and litigation, advertising disputes and challenges, and complex commercial disputes. Marc’s experience spans the full range of IP, including trademark…

Marc Rachman, a partner in the Litigation + Dispute Resolution and Intellectual Property + Media Practice Groups, focuses on intellectual property (IP) counseling and litigation, advertising disputes and challenges, and complex commercial disputes. Marc’s experience spans the full range of IP, including trademark, copyright, false advertising, rights of publicity, trade secret and patent infringement disputes. He helps clients of all sizes assess, protect and optimize the value of their intellectual property.

Insightful and pragmatic, with a deep knowledge of his clients’ businesses and industries, Marc gets to the root of a matter quickly with strategic insight and practical solutions. His experience as a media planner before pursuing his legal career gives him a unique perspective when advising on advertising and media matters. Marc represents industry-leading advertising and marketing, financial services, digital media and adtech businesses, world-renowned entertainers, small businesses, and technology startups, among others.

Marc works closely with clients to assert and defend IP infringement claims, provides pre-litigation and litigation avoidance counseling, and advises on the use of IP in advertising, marketing and promotions. He has an impressive record in prosecuting and defending cases, and his knowledge of the courts and the alternative dispute resolution process helps him guide clients in deciding when to fight and when to settle. He is exceptionally swift and effective in resolving IP matters in court, before the USPTO and its Trademark Trial and Appeal Board, and at the negotiating table.

Marc’s experience extends to copyright disputes concerning music, photo, pictorial, sculptural and literary works. He has also worked on trademark matters relating to word and design marks, trade dress, and nontraditional trademarks — including sounds and product designs — as well as celebrity images and personas. In recent years, he has been a driving force in developing and building the firm’s niche practice in defending graffiti art copyright infringement claims.

Marc has helped several celebrity clients address online reputation management issues. He also has extensive experience handling complex commercial disputes involving the enforcement of advertising agency-client agreements, digital advertising sales agreements, partnership dissolutions, employment terminations, and restrictive covenants and real estate leasing disputes.

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Photo of Sarah Benowich of Davis+Gilbert Sarah Benowich of Davis+Gilbert

Sarah Benowich helps clients resolve disputes efficiently and effectively, always aligned with their goals and priorities. Working with media and technology companies, advertising agencies, major brands and individual entrepreneurs, she has developed a deep understanding of their unique needs at different stages of…

Sarah Benowich helps clients resolve disputes efficiently and effectively, always aligned with their goals and priorities. Working with media and technology companies, advertising agencies, major brands and individual entrepreneurs, she has developed a deep understanding of their unique needs at different stages of growth. As a result, she adeptly leverages legal strategies and practices to achieve business-oriented solutions.

Sarah litigates and counsels businesses on disputes in a wide a range of subjects, including contract, trademark, copyright, employment and other commercial matters. When clients are less familiar with litigation and dispute resolution, Sarah guides them through the process and identifies strategic opportunities for the efficient use of resources. She helps with initial consultations, pre-suit negotiations and settlements. If litigation is necessary, she manages all aspects of discovery, drafts briefs and argues motions. Sarah is also experienced in preparing appeals.

Clients involved in cross-border matters also appreciate her experience with international clients and her familiarity with different jurisdictions. Her advanced language skills in French and Hebrew have been a valuable asset. Before joining Davis+Gilbert, Sarah was an associate at Pearl Cohen and began her career at Hogan Lovells.

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Photo of Eva M. Jiménez of Davis+Gilbert Eva M. Jiménez of Davis+Gilbert

Eva Jiménez supports creative and practical solutions in complex commercial litigation, employment matters and real estate disputes. She helps technology companies, creative agencies, real estate firms and financial institutions find productive and efficient resolutions to minimize litigation risk and avoid protracted litigation.

Eva…

Eva Jiménez supports creative and practical solutions in complex commercial litigation, employment matters and real estate disputes. She helps technology companies, creative agencies, real estate firms and financial institutions find productive and efficient resolutions to minimize litigation risk and avoid protracted litigation.

Eva draws on her strong research and writing skills to help position clients for positive outcomes. She uncovers recent and relevant developments that inform strong arguments. Her persuasive and plain-English writing explains complex legal considerations while keeping the lines of communication open with opposing counsel. In commercial contract disputes, Eva researches viable claims and arguments to draft memos in-house counsel can use to weigh their position and make informed decisions. During her clerkship, she gained early experience in effective litigation practices while learning how judges write, analyze motions and review the facts.

A native Spanish speaker, Eva provides a valuable asset in matters involving clients, opposing parties or witnesses who are native Spanish speakers.

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  • Posted in:
    Intellectual Property, Technology and AI
  • Blog:
    ILN IP Insider
  • Organization:
    International Lawyers Network
  • Article: View Original Source

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