The emergence of generative artificial intelligence (AI) technology is introducing fresh challenges to intellectual property law. Existing laws are being called into question as concerns grow over how creators can be protected from potential threats posed by the booming industry. Lawmakers are also striving to balance regulation while keeping the US competitive in the global arena, particularly with patent law in mind. The Senate Judiciary Subcommittee on Intellectual Property held a hearing on Wednesday to review patent and innovation concerns, shining a spotlight on a range of AI issues. Senators from both parties highlighted concerns over how AI products are trained on language models and how this impacts writers and artists. Intellectual property concerns took center stage, with Senator Chris Coons (D-Del.), the Chairman of the Intellectual Property Subcommittee, stating that IP considerations should be included in AI regulatory frameworks. The ranking member of the subcommittee, Senator Thom Tillis (R-N.C.), said that the US needs to regulate effectively to stay atop the industry.
Mike Huppe, CEO of SoundExchange, said it is crucial for lawmakers to understand how AI systems work and the threats they pose. With policymakers currently exploring how best to regulate AI, Huppe believes that “thoughtful legislation and thoughtful guardrails and thoughtful regulation can have a real impact.” When OpenAI’s ChatGPT chatbot launched this year, AI became a focus for Congress and regulators. Fears about the technology go beyond intellectual property to concerns about potential national security threats, diminishing the workforce, and spreading dangerous misinformation.
The explosive growth of generative AI, such as OpenAI’s DALL-E, raises concerns about copyright law and large data sets. Robert Brauneis of the George Washington University Law School said most potential litigation over copyright infringement cases against AI companies will center on interpreting the “fair use” exception to copyright law. However, to date, legal disputes in this area have not made it through the courts. Brauneis argued that it is reasonable to train AI models by relating them to how humans learn, with human artists and authors learning by viewing and reading the works of others. The copyright analysis does not look into whether the creator has relied on others’ work, but determines whether the output is similar to the original. Meanwhile, AI-generated output may compete in the same market as the input, making it difficult to apply the “fair use” exception. The copyright law only recognizes humans as eligible creators. If a work is entirely AI-generated, it cannot receive copyright status under US law, while recordings containing “a little piece of AI” will likely qualify for regular recording rights.
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