AI Copyright Protection via Digital DNA Profiling
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Solution Overview
Problem
The integration of generative Artificial Intelligence (AI) systems with copyright law poses significant challenges, including the identification and enforcement of copyright, ambiguity in ownership of AI-generated content, and the risk of unlicensed content usage leading to infringement claims.
Innovation Solution
A method and system for optimizing copyright protection within AI systems, involving the analysis of original copyright works to create unique digital DNA profiles, storage of these profiles, and tracing of reference training data to identify original works influencing new derivative works, ensuring proper attribution and compliance with copyright laws.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If generative AI models are trained on large datasets to improve creative capabilities, then the quality and versatility of generated content is improved, but the risk of copyright infringement increases due to unlicensed content usage
Solution Approach 1:
The system performs preliminary actions by analyzing and creating digital DNA profiles of training data before the AI model is trained. This advance preparation enables later tracing and attribution of source materials, allowing the system to maintain creative capabilities while preventing copyright infringement through pre-established tracking mechanisms.
Solution Approach 2:
The digital DNA profile acts as an intermediary between the training data and the AI model. It provides a traceable link that mediates between the need to use copyrighted material for training and the need to protect copyright holders' rights, enabling attribution without preventing the training process itself.
2Reliability
If AI systems analyze and trace training data to identify original copyright works, then copyright protection and attribution are improved, but the complexity of the system increases
Solution Approach 1:
The system creates simplified digital DNA profiles that copy only the essential identifying features of original works rather than storing complete copies. This allows for effective copyright tracking and attribution while maintaining system efficiency and managing complexity through selective replication of key characteristics.
3Measurement precision
If digital DNA profiles are created and stored for all training data, then attribution accuracy is improved, but the storage requirements and processing time increase
Solution Approach 1:
The system extracts only the essential identifying characteristics needed for attribution into digital DNA profiles, separating these key features from the complete training data. This extraction process maintains high attribution accuracy while significantly reducing storage requirements by storing only the necessary identifying information rather than complete data sets.
Data Source
AI summary
A system and method of optimizing copyright protection within an Artificial Intelligence (AI) system, includes analysing an original copyright work to formulate a unique creative digital DNA profile of the work; storing one or more analysed copyright works, along with their digital creative DNA profiles; and upon a generative Artificial Intelligence (AI) model creating a new derivate work, tracing reference training data of the derivative work to identify one or more original copyright works that have informed the new derivative work.