Microsoft is using blockchain to help businesses trust AI technology more.

Microsoft is aggressively developing blockchain technology and attempting to use it to alleviate its enterprise customers' fears of artificial intelligence.

Just as the general public remains wary of AI, enterprises are uneasy about placing their complete trust in a black box where machine learning algorithms are applied indiscriminately to vast datasets, even making judgments and decisions. This is a major reason why many are hesitant towards AI.

Microsoft is helping thousands of companies manage their data and claims that blockchain can increase trust and a certain level of transparency, alleviating such concerns.

The Blockchain Data Manager from Microsoft retrieves on-chain data and connects it to other applications. Therefore, transaction data from nodes or smart contracts can be sent to other databases or data stores. Microsoft believes these are areas where AI can be deployed, or in the case of supply chains, can carry IoT messages.

Backing this functionality is a new tool called Azure Blockchain Data Manager, which the software giant announced at the annual Ignite conference in Orlando, Florida. Azure Blockchain Services aim to simplify the definition, creation, and management of compliant tokens built on industry standards. The company also provides generic pre-built templates and a gallery for partner-created templates expected to be added in the future. The announcement reads as follows:

With this latest offering, we can now provide customers with an end-to-end experience, not only managing the blockchain network itself through Azure Blockchain Services, but also easily creating and managing tokens for physical or digital assets using Azure Blockchain Tokens.

The company's Principal Program Manager, Marc Mercuri, stated:

From manufacturing to energy, public sector to retail, AI is digitizing operations across industries. Blockchain can ensure that everything going in and out of algorithms with their data is trustworthy.

Mercuri explains that before AI analyzes data, you can use a distributed ledger to view the data's origin. We can ask these questions: Where did it come from? Where did it transform? What code was used to transform it? What were the inputs and outputs of that transformation? These answers are easily obtainable in the blockchain. Avivah Litan, Vice President and Distinguished Analyst at Gartner Research, also agrees that this concept is sound.

Litan mentioned that we can combine blockchain, AI, and IoT to track organic beef imported from Argentina. In this scenario, the blockchain would allow participants to agree on all conditions and exact locations of the goods and further inform distribution strategies offline, which is where AI can come into play to perform the translation work and coordination between them.

Tracking food doesn't necessarily require blockchain, but with blockchain, we can have a shared single version of truth and immutable audit trails, making it a better data source to meet the needs of your AI models. The cost we've historically paid for trust has been too high, and blockchain gives us a way to address that.

KPMG also plans to release its trusted AI version based on blockchain in January, with Arun Ghosh, Head of US Blockchain at KPMG, believing that a significant part of machine learning is not data science but data engineering. He stated:

It's about cleaning, organizing, and integrating information, and then running algorithms, and we find that you can compress the data engineering process by adding an essentially immutable layer of trust.

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