Open Access. Powered by Scholars. Published by Universities.®

Law Commons

Open Access. Powered by Scholars. Published by Universities.®

Science and Technology Law

Duke Law

Artificial Intelligence

Publication Year

Articles 1 - 2 of 2

Full-Text Articles in Law

The Gptjudge: Justice In A Generative Ai World, Maura R. Grossman, Paul W. Grimm, Daniel G. Brown, Molly (Yiming) Xu Dec 2023

The Gptjudge: Justice In A Generative Ai World, Maura R. Grossman, Paul W. Grimm, Daniel G. Brown, Molly (Yiming) Xu

Duke Law & Technology Review

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 …


Keeping Up With China: Cfius And The Need To Secure Material Nonpublic Technical Knowledge Of Ai/Ml, Anthony Severin Mar 2021

Keeping Up With China: Cfius And The Need To Secure Material Nonpublic Technical Knowledge Of Ai/Ml, Anthony Severin

Duke Law & Technology Review

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 …