Risks of copyright infringement
The use of vast amounts of data for training general- purpose AI models has caused concerns related to data rights and intellectual property. Data collection and content generation can implicate a variety of data rights laws, which vary across jurisdictions and may be under active litigation. Given the legal uncertainty around data collection practices, AI companies are sharing less information about the data they use. This opacity makes third- party AI safety research harder.
ENTITY
1 - Human
INTENT
3 - Other
TIMING
3 - Other
Risk ID
mit1032
Domain lineage
6. Socioeconomic and Environmental
6.3 > Economic and cultural devaluation of human effort
Mitigation strategy
1. **Establish a Rigorous Data Provenance and Licensing Framework:** Mandate comprehensive, auditable due diligence on all AI training datasets, ensuring lawful acquisition and clear, compatible licensing that permits commercial use. This framework must align with emerging global regulations (e.g., EU AI Act, California TDTA) by requiring the publication of training data summaries to enhance transparency and mitigate foundational intellectual property (IP) infringement risk. 2. **Implement Mandatory Output Clearance and IP Compliance Protocols:** Develop and enforce a cross-functional internal AI policy that includes rigorous pre-deployment testing and a systematic review process for all model outputs. This protocol must utilize technical detection tools to prevent the "regurgitation" of copyrighted material and ensure that all AI-assisted projects document human contribution sufficiently to establish copyright eligibility for derivative works. 3. **Secure Contractual Indemnification and Defined IP Assignment:** Prioritize the procurement of AI services through enterprise-grade licensing agreements that contain explicit, robust indemnification clauses against third-party copyright claims arising from model training or output. Simultaneously, the agreements must clearly and unequivocally assign all IP rights for generated content to the end-user organization to minimize liability and establish clear ownership.