Intellectual Property Guidelines for Generative AI in Research

Data Handling and IP Protection

  • Ensure that all data used in Generative AI applications, particularly sensitive or proprietary data, is handled according to strict university confidentiality protocols. Data used in training Generative AI models must be anonymized or de-identified where possible to prevent any inadvertent disclosure of personal or proprietary information.
  • Implement secure storage solutions and access controls for datasets used in Generative AI research. This includes encrypted storage, controlled access permissions, and regular audits to ensure that only authorized personnel have access to sensitive data.
  • Maintain meticulous records of data provenance. This involves tracking the source of all data used in AI projects to ensure compliance with copyright laws and data usage agreements.

Copyright Compliance

  • Researchers must ensure that all copyrighted materials used in Generative AI training and research are properly licensed or fall within the scope of fair use exceptions. This includes text, images, software, and any other copyrighted media.
  • Properly document and attribute all sources of copyrighted materials. This transparency not only respects the copyright of original creators but also enhances the credibility and reproducibility of research.

Licensing Agreements

  • Researchers must thoroughly understand the terms and conditions of any software and datasets used in Generative AI research. This includes restrictions on the use of licensed software and data, which may affect the publication of research results or the development of derivative works.
  • Where possible, negotiate licensing terms that align with the university’s research goals and IP policies. This may involve securing rights to modify, reuse, and publish results based on the licensed materials.
  • For Generative AI research that involves collaboration with external entities, develop clear licensing agreements that define the terms of use, ownership, and rights to any jointly developed IP. This includes specifying the handling of sensitive data and the distribution of benefits from potential commercialization.

Practical Steps for Implementation

  • Conduct regular IP review sessions with researchers using Generative AI to ensure that they are aware of IP issues and compliant with university policies.
  • Offer training sessions and workshops focused on IP management in the context of Generative AI research. These sessions should cover topics such as copyright compliance, data handling, and the drafting of licensing agreements.
  • Engage with the university’s Office of Technology Transfer & Commercialization early in the research process to identify and protect potentially patentable inventions that arise from Generative AI research.