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Artificial intelligence and blockchain are trending technologies that are improving business models and transforming entire industries. Deloitte refers to them as the most exciting trends of 2022, and Gartner predicts their rapid development for decades to come.
Don Tapscott, Blockchain Research Institute founder, talks about the possible merging of blockchain, AI, and the Internet in a trivergence. This trivergence will be the basis of the second era of the digital age, where blockchain will record and protect data as AI will analyze it.
Let's take a look at how blockchain and AI can work together.
Many people consider distributed ledger technology, or blockchain, to be synonymous with cryptocurrency. This isn't the case, as cryptocurrency - while being the most popular - is just one of the many ways that blockchain technology can be harnessed.
A blockchain database is distributed over blocks linked together in a chain. Entries in a block are hashed so that no one can change or delete the information. For transactions to be carried out honestly, a consensus mechanism works in the network when blockchain participants confirm or reject unauthorized actions.
These features are adopted by industries to prevent fraud, protect information, and/or manage business-critical transactions.
AI, on the other hand, is a set of deep and machine learning algorithms that mimic human thought. AI processes and arranges volumes of data that are beyond the extent of human capabilities.
Furthermore, AI takes the burden off people by automating routine manual operations. For enterprises, it is becoming a business intelligence tool or a mechanism for protecting against cyber-attacks. AI can be applied to everything from writing articles for the Associated Press to early detection of diseases.
Since AI and blockchain are not related in any way, how then can they work together?
Despite the dissimilarity between the two technologies, they can be used to complement each other and eliminate each other's shortcomings. Thus, blockchain will create more trust in AI platforms, maintaining security and privacy. AI will strengthen the protection of transactions, and contribute to the monetization of information. Blockchain will also clarify the work of AI by recording in detail the data on which decisions made by smart algorithms are based.
AI, in turn, can support the scalability of blockchain applications by automating the management procedures of a decentralized network. It allows businesses to collect, analyze and apply the data received, while blockchain allows them to check, record, and perform certain actions with them.
AI and blockchain are like the yin-yang of the digital world, providing businesses with the missing harmony. According to Yoav Vilner, CEO of Walnut, these technologies enhance each other, and entrepreneurs should explore their implementation options to gain a deeper understanding of business.
The convergence of blockchain and AI opens up many new business opportunities. Let's look at promising use cases of this powerful combination of technologies.
1. Enhanced data protection mechanism
Blockchain is considered synonymous with security because every block in a chain is encrypted with a hash algorithm. It is almost impossible to decrypt the data because a unique key is created for each block. In addition, this key changes when a new block is added to the chain. A user has a personal key to access information and a public key to conduct transactions.
Despite such multi-layered protection, vulnerabilities can be found in blockchain-related applications. Take, for example, the DAO hack, when the company lost over 3.6 million ether, or the attack on the Bitfinex cryptocurrency exchange when an amount of 119,000 Bitcoin was stolen.
AI strengthens the existing blockchain security mechanism, bringing the risks of attacks to a minimum. A smart algorithm analyzes anomalies in the blockchain, and in the future, it will learn how to work with encrypted data. It will analyze arrays of protected data and find potential bottlenecks so that developers can deal with them.
For example, say a person invests a fixed amount of money in EFT every month. Suddenly, an investment exceeds the usual sum by 10 times. AI evaluates such a transaction as suspicious, and an anti-fraud mechanism is triggered to stop anomalous activities in time.
2. Validation of decision-making process by AI algorithm
Explainability is one of the unresolved issues that is hindering the widespread adoption of AI. It is difficult for people to rely on AI when they do not understand why a certain solution is proposed. For greater confidence, people need the logical validity of the proposals put forward by AI.
LIME, a method elaborated by scientists to increase the transparency of AI, and attention techniques are still far from ideal and are still being developed. Blockchain claims to be the third and more justified solution to the problem of explainability of AI.
Blockchain can make the secret and the incomprehensible in the work of AI transparent and explainable. The distributed database stores each decision made by AI in blocks so that the user can view and analyze it. At the same time, decentralization and enhanced encryption of the registry ensures that information is protected from unauthorized access.
When people begin to understand how the decision-making mechanism of AI works, they will trust the technology more. This, in turn, will accelerate the pace of implementation of AI in healthcare, fintech, logistics, and other areas of human activity.
Such a move towards transparency would make AI-powered blockchain medical applications a common practice. Logistics companies will launch blockchain and AI-based infrastructure to monitor the supply chain in real-time. Cadastral companies, like Sweden's Lantmäteriet, will use blockchain and AI to store and track documents for property sales.
Soon, blockchain and AI might be able to comply with the conditions of the GDPR specified in Article 22 and WP29. A person will receive an explanation of decisions and with it the right to accept or challenge them to control AI.
3. Improved data control and monetization
The volume of data generated by mankind is growing rapidly and, according to Statista experts, will increase from 64 zettabytes in 2020 to 180 zettabytes in 2025. Such a large stream of data needs to be processed, analyzed, and stored securely, providing access only to the owners.
The data that businesses collect may relate to individual customers, suppliers, and products. They also need to be correctly extracted and researched to be used for critical business processes, key business forecasts, and fundamental decisions for development. AI takes over this function by working with data in a decentralized secure network.
At the same time, the convergence of AI and blockchain makes possible a new type of income - the monetization of personal data. An owner can store personal information in a decentralized network and sell it to interested parties: research organizations, medical institutions, and other companies. For a certain amount, a user can open temporary access to personal data. Information-selling platforms like Hu-manity.co are creating a marketplace for data that can be used for business purposes.
Each organization will be able to leverage the convergence of AI and blockchain in different ways, depending on the goals and type of underlying data. Firms that are first to adopt these technologies will see immediate results and gain an edge over companies that are just starting to introduce innovations.
4. Reducing power consumption when mining
To keep the Internet running, servers need to be operating 24 hours a day, 365 days a year. They need a constant flow of electricity - about 1% of the world's supply, and most of it goes to cool data centers. Planetly estimates that maintaining the Internet can cause 0.3% of global CO2 emissions.
Tech giants began to look for ways to reduce the negative impact on the environment. So, Google has been using the DeepMind algorithm to manage the data center for more than 5 years. Trained on an array of historical data, the neural network “knows” how to rationally use the cooling system. As a result, Google managed to reduce energy consumption by 40%.
A similar control mechanism can be introduced into the mining process to cool large data centers. AI in this case will not only reduce environmental pollution but also lead to lower prices for mining hardware.
The four AI and blockchain use cases mentioned above are not just theories. Organizations are testing possible ways to apply technologies in a single project. As smart algorithms and decentralized ledgers improve, it will be possible to implement profitable business solutions.
AI needs blockchain to show how a smart algorithm works. Blockchain benefits from stronger AI defenses, better smart contracts, and lower power consumption. Soon, we will surely witness discoveries related to the joint use of AI and blockchain. The reality that seemed fantasy is approaching.