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6. Socioeconomic and Environmental1 - Pre-deployment

Impact on Intellectual Property Rights

The extent and effectiveness of legal protections for intellectual property have been thrown into question with the rise of generative AI. Generative AI trains itself on vast pools of data that often include IP-protected works.

Source: MIT AI Risk Repositorymit525

ENTITY

1 - Human

INTENT

1 - Intentional

TIMING

1 - Pre-deployment

Risk ID

mit525

Domain lineage

6. Socioeconomic and Environmental

262 mapped risks

6.3 > Economic and cultural devaluation of human effort

Mitigation strategy

1. Mandate a comprehensive Intellectual Property audit of all AI training datasets, prioritizing ethical and legal sourcing with explicit rights clearance or reliance on licensed/public domain content to proactively mitigate large-scale copyright infringement claims related to model ingestion. 2. Develop and enforce a rigorous internal Generative AI use policy that includes: a) clear legal frameworks for defining IP ownership of AI-generated content, and b) strict protocols to prevent the input of proprietary or confidential organizational data into unvetted or public models, thereby safeguarding trade secrets. 3. Institute a mandatory, multi-stage vetting process for all public-facing AI-generated content, employing both technical tools (e.g., similarity and plagiarism detection software) and human expert review/editing to minimize the risk of substantial similarity to protected works and ensure compliance with copyright and trademark laws.