Copyright - Authorship
The emergence of generative AI raises issues regarding disruptions to existing copyright norms. Frequently discussed in the literature are violations of copyright and intellectual property rights stemming from the unauthorized collection of text or image training data. Another concern relates to generative models memorizing or plagiarizing copyrighted content. Additionally, there are open questions and debates around the copyright or ownership of model outputs, the protection of creative prompts, and the general blurring of traditional concepts of authorship.
ENTITY
1 - Human
INTENT
1 - Intentional
TIMING
1 - Pre-deployment
Risk ID
mit83
Domain lineage
6. Socioeconomic and Environmental
6.3 > Economic and cultural devaluation of human effort
Mitigation strategy
1. Legal and Contractual Frameworks Establish comprehensive contractual agreements and enterprise licenses with all parties, including AI model providers and end-users. These agreements must clearly define the allocation of Intellectual Property (IP) ownership for model inputs, training data usage rights, and the copyright status of generated outputs. Critical elements include robust indemnification clauses to protect the organization against third-party IP infringement claims stemming from the model or its training data. 2. Comprehensive Internal AI Governance and Due Diligence Develop and enforce a cross-functional internal AI policy, engaging legal, compliance, and engineering expertise early in the development lifecycle. This policy must mandate rigorous vendor due diligence, assessing the vendor’s IP terms, security protocols, and compliance with data use laws. Furthermore, the policy should require continuous employee training to ensure strict adherence to copyright laws and data security protocols, safeguarding proprietary information used as input. 3. Creative Control Documentation and Output Clearance Implement a mandatory, auditable process for the legal review and clearance of all AI-generated content prior to its commercial use or public release, specifically to detect and prevent unintentional plagiarism or close resemblance to protected works. Concurrently, maintain meticulous documentation of the level of human creative control and substantive contributions to AI-assisted works to strengthen a claim for copyright protection under human-authorship requirements.