blockchain and AI

Blockchain Explained

Understanding the link between Blockchain and AI

November 19, 2021

How private blockchain adds trust and accountability to AI

Blockchain and Artificial Intelligence (AI) are proving to be a powerful double act, coming together to deliver unique features and benefits for a growing list of industries and applications. In fact, you can already find blockchain integration with AI adding value and security to everything from food supply chains and healthcare record systems to managing media royalties and financial services.

On its own, blockchain is a distributed digital ledger or database shared across peers or nodes on a network that must all agree on a transaction before it is added as a block to the blockchain. Each block contains the data and an immutable record of exactly when it was created, which cannot be corrupted, lost or changed without the network knowing about it.

While AI means different things to different people, it is essentially the ability to simulate human intelligence using machine leaning to process and analyse vast amounts of data and make fast and accurate decisions. However, if we are going to rely on these machine-based decisions – even put our lives in their hands – it is critical that we can build trust and have confidence in their outcomes. And like all technologies producing automated conclusions, we should be able to verify and audit the end-to-end process.

The EU General Data Protection Regulation (GDPR) states that any decisions made by a machine or algorithm must be readily explainable with the right to obtain details and if desired, to opt out of any machine-based decisions completely. It is backed up by impressive fines if breached.

This is where blockchain comes in to establish the attribution, understanding and justification of those decisions and outcomes. Blockchain is the perfect instrument for peeling the layers of complex AI algorithms to understand their decision-making processes. By connecting a distributed, decentralised and immutable ledger, it is possible to record the data that goes into making a decision made by machine learning. By storing the key data elements in the decision-making process as transactions on a blockchain, the system can be meaningfully verified, audited and if necessary, adjusted.

There are a number of blockchain AI projects already in operation. For example, at the Swedish mapping, cadastral and land registration authority, Lantmäteriet, all the data from land transactions are fed into an AI process then used by chatbots, instead of humans, to answer FAQs. Instead of recording and dissecting thousands of conversations, each inquiry can be tracked and the stored answers and data reviewed and audited, then refined for future use. This also makes it possible to trace and determine why decisions are made – in effect blockchain’s key function of building trust and transparency forces AI to explain itself and its actions, making it the perfect complementary technology. A number of AI and blockchain healthcare applications are also being developed.

More sustainable blockchain

Public blockchains – mostly associated with crypto currencies – require considerable processing power to perform tasks and for mining the next block. But AI can make a difference by determining the capability of each machine and allocate different tasks and node types based on past performance and specification levels. With thousands of nodes, this use of AI enables rapid allocation of processing power to optimise the public network and boost blockchain efficiency.

But when it comes to enterprise blockchain applications, the use of public blockchains pose several challenges around privacy and control. It may not suit a business to allow every participant full access to the entire contents of the database. Instead, private blockchains have a single authority or organisation that ultimately retains control, and no one can enter this type of network without proper authentication. Private blockchains are generally ‘permissioned’ and offer all the distributed benefits of a public blockchain, while retaining overall control to improve privacy and eliminate many of the illicit activities often associated with public blockchains and cryptocurrencies. In addition, for reasons of performance, accountability and cost, private blockchains are more suited to enterprise applications, where the technology empowers and supports the business rather than individual users.

Better together

It is clear that blockchain and AI are two of the most exciting and influential technologies of this decade. AI is expected to create $391bn in business value by 2025 according to a report by Grand View Research, Inc., while private blockchains look set to become the main contributor to blockchain market growth. According to Gartner, the business value generated by blockchain will grow rapidly, reaching $176 bn by 2025 and $3.1 trillion by 2030. In the final phase of the Gartner blockchain model, post 2025, it says that enhanced blockchain solutions will fully harness complementary technologies such as AI and IoT.

Private blockchains combined with AI provide more opportunities to utilize the technology for B2B use cases where they deliver higher efficiency, privacy, reliability, and transparency. Large enterprise blockchain solutions will be custom developed according to their specific business needs and SMEs will take advantage of cost-effective pre-packaged solutions and Blockchain-as-a-Service options. The convergence of blockchain and AI is still in its infancy but expect to see more AI blockchain companies and the convergence of these technologies gaining pace to become mainstream across sectors from financial services, supply chain and telecoms to health and insurance.

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