ABSTRACT
Generative AI models like ChatGPT raise novel issues for trade secret law. This Essay identifies three major developments and explains how the law will likely respond based on analogies to past technologies and past case law.
First, widespread use of generative AI poses new risks to companies’ existing trade secrets. For example, trade secret owners’ own employees might inadvertently share trade secrets with a generative AI tool like ChatGPT, which might disseminate this information to competitors or third parties. I argue this new disclosure risk, at the margins, raises the bar for keeping trade secrets. But companies will likely adapt their risk management strategies, as they did in the face of prior information-distribution technologies, such as the internet.
Second, generative AI will add to the universe of information that can be protected under trade secret law. Trade secret law will be available even for information that is not protected by patent and copyright law. Patent and copyright law have human creator requirements. But trade secret law has no human creator requirement. Therefore, purely AI-generated outputs that do not qualify for patent or copyright protection can be protected as trade secrets.
Third, companies that develop valuable new generative AI tools will be able to rely on trade secrecy to protect that technology, even when other forms of IP are unavailing. Trade secret law, especially when supplemented by restrictive contractual ‘terms of use’, can protect various types of information related to generative AI, including information that does not qualify for copyright or patent protection.
Even though generative AI models will initially benefit from a combination of trade secrecy and contract protection, the models are highly vulnerable to ‘reverse engineering’. For example, OpenAI, the maker of ChatGPT, recently accused the makers of the new AI model, ‘DeepSeek’, of engaging in ‘knowledge distillation’ to develop their competing system – using the larger, more complex, and more expensive ChatGPT model to build a smaller, simpler, and cheaper one. Trade secret law, although it generally permits reverse engineering, may or may not condone this conduct. Courts might construe these activities as a violation of contract law, since knowledge distillation seems to violate OpenAI’s contractual terms of use, but courts may also view these activities as a violation of federal and state trade secret law. In software cases, courts have held that using cutting-edge techniques like data scraping to access trade secrets constitutes acquisition by ‘improper means’, and thus misappropriation, especially when contractual terms of use explicitly prohibit this conduct. The makers of DeepSeek claim they independently developed their model, but if this is not true, trade secret law could provide an avenue for legal liability.
Hrdy, Camilla Alexandra, Trade Secrecy Meets Generative AI (February 1, 2025), Rutgers Law School Research Paper Forthcoming; ‘Disrupting AI’ Symposium Issue of the Chicago Kent Law Review, Forthcoming 2025.
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