Journal of AI, Data Science and Cyber Systems

Blockchain-Enabled Trusted Data and AI Ecosystems use distributed technologies to create trust, transparency, and integrity in data sharing and AI processes in decentralized multi-stakeholder environments. Such ecosystems have data created, shared, and utilized by entities across organizations, devices, or AI agents that may distrust one another. Ecosystem participants have data that is generated, exchanged, and consumed in environments where others do not fully trust one another. In blockchain ecosystems, all participants share, access, and verify records without relying on a single, centralized authority. When combined with AI and other data platforms, blockchain technologies allow secure data market places, trustworthy model training, and responsible governance of AI. Automated smart contracts help with the management of data policies, management of consent, distribution of incentives, and regulation of compliance, while retention policies and encryption keep data unmodified and access controlled. AI systems can offer models with reliable and transparent data in order to avoid and reduce risks like data poisoning, model hacking, and unlawful reuse. In sectors such as healthcare, blockchain systems combined with AI and uncomplicated data technologies offer the most apparent tools to enhance trust, accountability, and decentralized collaboration.