AI Multimedia Copyright Verification via Blockchain
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Solution Overview
Problem
Current systems for managing copyrights of AI-generated multimedia lack effective origin verification and fail to adequately recognize the contributions of all involved parties, leading to limitations in royalty distribution and technical challenges in implementing blockchain technologies.
Innovation Solution
A system and method that integrates a multimedia generation module, a copyright claiming module, and an asset exchanging module within a blockchain framework, enabling users to claim and exchange copyrights for AI-generated multimedia by verifying originality and facilitating transactions using non-fungible tokens (NFTs), while ensuring compliance with system policies and legal regulations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If AI systems generate multimedia without human intervention, then productivity and creativity are improved, but copyright protection and origin verification become problematic
Solution Approach 1:
The system performs preliminary actions by embedding origin information and copyright metadata into the multimedia content at the moment of AI generation. This preliminary tagging ensures that when the content is later exchanged or verified, the origin and copyright status are already established and can be automatically validated through blockchain verification, resolving the contradiction between automated generation and reliable copyright protection.
2Reliability
If copyright management is automated through blockchain, then transparency and trust are improved, but system complexity and implementation difficulty increase
Solution Approach 1:
The patent introduces an intermediary layer that sits between the AI generation system and the blockchain network. This intermediary handles the complex tasks of metadata extraction, blockchain transaction formatting, and smart contract interaction, while presenting a simplified interface to users. This mediator absorbs the system complexity while maintaining transparent and trustworthy copyright management.
3Reliability
If all involved parties are recognized in the creation process, then fairness and equity are improved, but royalty distribution complexity increases
Solution Approach 1:
The system segments the contribution recognition by creating distinct metadata fields for different types of contributors (AI model creators, data providers, human operators, etc.). Each contributor type has its own identification and reward mechanism. This segmentation allows fair recognition of all parties while keeping the royalty distribution logic modular and manageable through smart contracts that automatically allocate rewards according to predefined contribution weights.
Data Source
AI summary
A method for creating and exchanging a copyright for each artificial intelligence (AI)-generated multimedia is described. An AI model and a reference input for a multimedia is received from a user. If the reference input complies with system policies, an AI-generated multimedia is generated from the reference input using the AI model. The AI-generated multimedia is compared against works of a same type in a blockchain and decentralized file storage and if the AI-generated multimedia fails to match the works, the AI-generated multimedia is categorized as having originality. A copyright for the AI-generated multimedia and the AI-generated multimedia is stored. An exchange is facilitated with a buyer using cryptocurrency and is written to a blockchain.


