Episode 67 — Handle Intellectual Property Risks: Training Data Rights and Output Ownership (Domain 1)
Intellectual property (IP) risks in AI represent a "two-way street" involving the data used to train models and the content generated by those models. This episode details the legal hazards of using copyrighted or proprietary data in training sets and the ongoing uncertainty regarding the ownership of AI-generated outputs. For the AAIR exam, candidates must be able to identify these IP boundaries and recommend controls such as "data provenance" checks and specialized licensing agreements. We discuss the risks of "prompt injection" leading to the accidental disclosure of trade secrets and the importance of implementing outbound content filters to prevent the model from reproducing copyrighted material. Scenarios include a developer inadvertently using open-source code with restrictive licenses to train a commercial model. By establishing clear IP policies and technical guardrails, organizations can leverage AI while protecting their own intellectual assets and respecting the rights of third parties. Produced by BareMetalCyber.com, where you’ll find more cyber audio courses, books, and information to strengthen your educational path. Also, if you want to stay up to date with the latest news, visit DailyCyber.News for a newsletter you can use, and a daily podcast you can commute with.
