By boosting transparency and trust in the following ways, blockchain technology can play a critical role in increasing human confidence in AI-based systems.
Integrity of data
How data integrity is maintained over time is one of the most difficult difficulties in AI-based systems. Data is collected from clients and stored in a centralised server in typical applications with a client-server architecture. Duplication of information is reduced to a large extent when Blockchain technology is integrated into AI applications. Complete transparency, traceability, and accountability
Privacy and security of data
The dispersed type of data sharing has the potential to significantly reduce the trust gap in AI applications. Because there is no single place where hostile actors may assault data, it is extremely safe. Furthermore, because it is decentralised, distributed ledgers provide greater openness and responsibility for real-time data.
Decision-making and consensus
Consensus-based transactions are one of the most important features of Blockchain technology. Every choice must be agreed upon by all parties involved, and unauthorised data access or tampering becomes extremely difficult without the users’ consent.
Developing a sense of trust
People often worry how and when AI-based services will use personal data, which is one of the most significant problems AI developers confront. In blockchain-enabled AI apps, on the other hand, no one can access data without the user’s permission. Users can use a blockchain ledger to licence their data to the AI application or the provider depending on their terms and conditions.
Data dissemination and decentralisation
People have a lot of scepticism when it comes to data governance, which includes data collecting, storage, and use with AI. AI applications can store their data in a distributed and decentralised environment using blockchain technology. For data governance and dissemination, Distributed Autonomous Organizations (DAOs) and Smart Contracts can be used efficiently.
