Blockchain technology has the potential to enhance data integrity, facilitate secure data sharing and collaboration, enable tokenization and incentives, and support decentralized AI governance, all of which can contribute to the reliability and openness of AI systems.
Enhanced data integrity
The immutability and transparency inherent in blockchain technology can improve the integrity of data used in AI systems. By providing tamper-proof and verifiable data, blockchain allows AI algorithms to generate more precise and dependable predictions and insights.
For example, blockchain can be utilized in supply chain management to keep track of and document the movement of items, with AI systems then analyzing the data to identify patterns, anomalies and improve logistics procedures.
Secure data sharing and collaboration
As AI systems require access to diverse and vast datasets, blockchain provides a safe and decentralized platform for data sharing. With blockchain, data can be shared among multiple parties without relying on a single entity, while maintaining privacy and control over sensitive data.
In the healthcare industry, for instance, patient records kept on a blockchain can be securely shared with AI models for research or diagnosis, while ensuring the privacy of sensitive information.
Tokenization and incentives
Blockchain technology can make it simpler to incentivize and monetize AI environments by creating tokens or coins. These tokens can be used to compensate individuals who provide computational resources, train models, or offer data. These rewards can foster teamwork and encourage participation in AI research and development.
For example, SingularityNET is a platform that integrates blockchain and AI to create a decentralized marketplace where AI agents can provide services and be compensated with tokens for their efforts.
Decentralized AI governance
By leveraging smart contracts and decentralized autonomous organizations (DAOs), blockchain technology can facilitate decentralized governance and decision-making processes for AI systems. This ensures fair and transparent stakeholder participation in decision-making.
Decentralized governance can be particularly useful in areas like policy enforcement or the selection of AI models. Ocean Protocol, for instance, employs blockchain to create decentralized data marketplaces and governance frameworks, enabling participants to decide on data access and sharing as a group.
