The GPTJudge: Justice in a Generative AI World

By: Maura R. Grossman, Paul W. Grimm, Daniel G. Brown, and Molly Xu Generative AI (“GenAI”) systems such as ChatGPT recently have developed to the point where they can produce computer-generated text and images that are difficult to differentiate from human-generated text and images. Similarly, evidentiary materials such as documents, videos, and audio recordings that are AI-generated are becoming increasingly difficult to differentiate from those that are not AI-generated. These technological advancements present significant challenges to parties, their counsel, and the courts in determining whether evidence is authentic or fake. Moreover, the explosive proliferation and use of GenAI applications raises concerns about whether litigation costs will dramatically increase as parties are forced to hire forensic experts to address AI-generated evidence, the ability of juries to discern authentic from fake evidence, and whether GenAI will overwhelm the courts with AI-generated lawsuits, whether vexatious or otherwise. GenAI systems have the potential to challenge existing substantive intellectual property (“IP”) law by producing content that is machine, not human, generated, but that also relies on human-generated content in potentially infringing ways. Finally, GenAI threatens to alter the way in which lawyers litigate and judges decide cases. This article discusses these issues, and offers a

Causation and Conception in American Inventorship

By: Dan L. Burk Increasing use of machine learning or “artificial intelligence” (AI) software systems in technical innovation has led some to speculate that perhaps machines might be considered inventors under patent law. While U.S. patent doctrine decisively precludes such a bizarre and counterproductive result, the speculation leads to a more fruitful inquiry about the role of causation in the law of inventorship. U.S. law has almost entirely disregarded causation in determining inventorship, with very few exceptions, some of which are surprising. In this essay, I examine those exceptions to inventive causality, the role they play in determining inventorship, and their effect in excluding consideration of mechanical inventors under current law. Download Full Article (PDF) Cite: 20 Duke L. & Tech. Rev. 116

Keeping Up With China: CFIUS and the Need to Secure Material Nonpublic Technical Knowledge of AI/ML

By: Anthony Severin Artificial intelligence (AI) and machine learning (ML) technologies will shape societies by the values they are programmed to respect. In part because of anti-competitive Chinese practices such as forced transfers of intellectual property (IP), companies based in the U.S. have lost the ability to compete in several fields. To avoid losing competitiveness in AI/ML sectors, the Committee on Foreign Investment in the United States (CFIUS) should promulgate rules blocking Chinese investors from acquiring ownership interests in U.S. companies when that ownership would allow access to material nonpublic technical knowledge of AI/ML. Such a categorical blacklist approach will limit forced transfers of IP and increase the influence of American values on the development of AI/ML technology. Download Full Article (PDF) Cite: 19 Duke L. & Tech. Rev. 59