Redefining Digital Licensing Agreements in the Era of Artificial Intelligence

Abstract

Intellectual property laws are encountering challenges due to Generative AI technologies. These laws were enacted to protect human creative works and had to deal with technologies that create a content with a quality of that of the human one, using data that might be legally protected, triggering issues over ownership of the AI-created content, as well as the liability that might result out of violations. This research uses the descriptive analytical approach to scrutinize the digital licensing agreements and assess their capacity to accommodate the terms aimed to regulate using the Generative AI, such as disclosing sources of the data used in training. The research shows that the existing legislations refuse to recognize the role of Generative AI when it partakes in creating a content with man, indicating that digital licensing agreements are more flexible tools in regulating and defining liability, through inserting terms that oblige developers to disclose sources of training data, setting rights to use and amend the created content, and distributing liability on AI developer and the ultimate user. The developed licensing agreements can help bridge the existing legislative gaps in order to achieve balance among rights of parties and promote innovation.