Blockchain-smart-contract-driven decentralized ai training data collecting and labeling method

A blockchain-smart-contract-driven decentralized AI training data collecting and labeling

• method, comprising the following steps:
• S1:
• deploying a decentralized workflow engine to a target blockchain, the workflow engine being used to manage distribution and validation of tasks;
• S2:
• configuring roles and permissions based on the workflow engine deployed in S1, including but not limited to permissions of workers, verifiers, reviewers, and publishers;
• S3:
• publishers creating tasks according to the role permissions configured in S2, uploading original datasets to be collected and labeled, setting requirements of collecting and labeling, and escrowing corresponding funds through a smart contract;
• S4:
• a system automatically splitting the original datasets into multiple small tasks according to the tasks created in S3 and allocating the multiple small tasks to suitable workers based on the role configuration in S2;
• S5:
• workers accepting tasks and performing data collecting and labeling according to the tasks allocated in S4;
• S6:
• verifiers reviewing the collecting and labeling results submitted by workers in S5 and reaching data consistency through a BFT consensus algorithm;
• S7:
• the system automatically executing a payment process through the smart contract based on the data consistency reached in S6.