Increased amounts of consumer data exposure, fake news and videos, and biased AI, have caused organisations to shift from trusting central authorities (government registrars, clearing houses) to trusting algorithms. Algorithmic trust models ensure the privacy and security of data, provenance of assets, and the identities of people and things.
For example, “authenticated provenance” is a way to authenticate assets on the blockchain and ensure they are not fake or counterfeit. While blockchain can be used to authenticate goods, it can only track the information that it is given.
To adequately track assets, they must be tracked from their source. For example, if a counterfeit item is added to the blockchain as a genuine version, the blockchain will continue to verify its authenticity based on the bad original data input. Due to the nature of the immutable ledger, it can never be modified or deleted.
Gartner believes increased interest in blockchain will create increased digital authentication and verification options.
Other emerging technologies in the algorithmic trust trend include differential privacy, responsible AI and explainable AI.