Bitcoin and Ethereum dominated the first decade’s worth of conversations around blockchain and cryptocurrency, leading most in the enterprise world to assume that “blockchain” was synonymous with “cryptocurrency.” This is, of course, a fallacy: The latter is just a single application of the former, more foundational technology.
But given the massive volume of data used to train AI models, implementing AI governance and audit systems poses a difficult challenge. This coupled with the lack of transparency into AI training models to date threatens to stifle broader AI adoption, despite its clear potential. Enter blockchain: an immutable, highly serialized ledger that gives companies a secure, cost-effective way to track the process of building and training AI systems.
Nevertheless, common beliefs and values vary widely across the globe. It’s important that AI systems are equipped to enforce ethics that best align with their specific user bases. Blockchain governance tools not only make that possible, but offer a highly secure and cost-effective option for businesses relative to traditional databases.It’s no secret that supply chain management is a notoriously legacy-driven industry that relies on outdated technologies and processes.