Convergence of Blockchain and AI

Author: Muskan Bagrecha

Blockchain and AI are the hottest technologies propelling the next wave of digital transformation. Researchers are actively exploring the vast potential of combining these cutting-edge technologies. Essentially, artificial intelligence, as it is commonly referred to today, is a set of theories and practices for building machines that can perform tasks that require intelligence. Artificial neural networks, machine learning, and deep learning are among the cutting-edge technologies offering endless possibilities. Meanwhile, blockchain is a digital ledger of transactions that is replicated across multiple computers on the blockchain. Whenever a transaction occurs on the blockchain, an entry for that transaction is added to each participant's ledger. Thanks to blockchain technology, we can create tamper-proof, robust databases that can be accessed only by the authorized users. By combining decentralization, trust, and verifiability, it offers a unique combination of disrupting systems where trustworthiness is essential in party-to-party transactions. The combination of these ground-breaking technologies has been extensively studied from an academic perspective. In fact, some researchers believe that the convergence is inevitable as data and value are at the heart of both the technologies. While blockchain provides a secure means of storing and exchanging valuable data, AI can derive insights from data in order to generate value. Let’s explore some of the ways in which Blockchain and AI perfectly complement each other:

Keep Your Data Safe

Data is at the heart of AI. AI models typically require large volumes of data to train on. However, the process of gathering and storing massive datasets is extremely complex and expensive. This has limited the power of AI in the favour of companies that have the required resources and workforce. Blockchain, by its very nature, is highly secure which makes it ideal for storing highly sensitive data. This data, if handled properly, can unlock immense value. From healthcare systems that can make diagnosis based on historical data to Netflix's movie recommendation system which tells us what to watch next, AI can perform wonders on the data collected from us as we browse or engage with services. This data, more often than not, is highly personal, and businesses who deal with this data usually invest a significant amount of money in order to fulfill the security requirements. Despite this, there have been many instances of large-scale data breaches. Information stored on blockchain, on the other hand, is in an encrypted state. This simply implies that in order to secure the data, only the private keys have to be kept safe. These private keys are usually only a few kilobytes of data. The combination of blockchain and AI can help enhance security through detection of attacks from bad actors and by enabling privacy-enhanced usage of data for better data management. Essentially, you can possibly license your data via the blockchain ledger under your terms, conditions, and duration, much like a digital rights management system. Such a system can maintain proofs and permissions required to access the user data. Moreover, adequately enforced security measures can create better AI models through accurate, varied and ethically-sourced data. Leveraging blockchain can also lead to better quality of data as producers can be incentivised to offer high quality data so as to lure more buyers. Using blockchain, we could create enormous, highly decentralised data stores that do not need human curators but rather grow on their own over time. Human-developed or curated data sets have inherent limitations, according to some, and can thwart the development of truly independent, general AI. Data decentralisation, as commonly argued, is therefore a prerequisite of a truly decentralised AI whose actions aren't constrained by the choices of its creators nor swayed by the biases of some central entity. Meanwhile, an emerging field of Artificial Intelligence is concerned with developing algorithms capable of handling (processing and operating) data in its encrypted state. Since data processes that involve exposing unencrypted data pose a security threat, reducing these incidents could significantly improve security.

Understand The Decisions Taken By Your AI Model

Another groundbreaking application is addressing the challenges associated with Explainable AI. We produce enormous quantities of data every second, more data than people are capable of assessing and interpreting. AI models, on the other hand, are capable of evaluating large datasets and making connections among several variables that are relevant to its goals. Any important decisions taken by AI, however, should be verified by humans. Humans rely on Artificial Intelligence in many mission-critical and business-critical situations to make decisions which can come with serious consequences. It is, however, difficult for humans to see and understand the exact relationship between the inputs fed to the AI model and the outputs given by these models. So if something goes wrong, it is difficult to pinpoint the problem and fix it. In such a situation, it becomes imperative to make learning systems more interpretable to understand why and how a decision is made by an AI system. Using blockchain we can record the actions that lead to a final decision in a non-modifiable way, allowing us to go back and see where mistakes were made and fix them. Due to the unbiased nature of blockchain, as well as the convenience of network participants being able to see what is going on, this can foster greater trust. A decision is immutable since a third-party cannot modify records under any circumstances. Further, since the blockchain ledger is decentralized, no single party has full control over it. This makes it far simpler for humans to audit the decisions taken by AI systems, with the assurance that the records have not been altered. AI company, SingularityNET, leverages blockchain to record decisions made by AI systems and tackles the lack of interoperability in AI. “SingularityNET is a full-stack AI solution powered by a decentralized protocol and the first and only decentralized platform allowing AIs to cooperate and coordinate at scale, removing one of the major limiting factors to AI growth today — the lack of interoperability — which severely restricts the ability to leverage the strengths and capabilities of individual AIs.”

AI Can Help Keep Blockchain More Reliable and Efficient

Blockchain data can be monitored with machine learning algorithms. In this way, it helps users become aware of potentially problematic situations by detecting patterns and anomalies in the type of data stored on the blockchain. Additionally, due to the encrypted nature of the data, computers require substantial computing power to implement algorithms such as hashing algorithms to mine blocks. AI comes to rescue as the tasks can be performed in a more intelligent manner. Essentially, an AI-based mining algorithm can perform better if it is fed with the right training data. This is very similar to the concept of how humans can perform better if trained for prolonged periods, except in the case of AI, it is way faster. Various AI techniques can be employed at the data entry point to detect anomalies in the data, thereby identifying any “bad” data before it can be recorded on the ledger. Such an analysis is imperative in improving the quality of the data and consequently the performance of the AI model. It can also improve the security of the blockchain platforms. The system could reduce fraud, increase safety, and enhance efficiency as well as help with contingency planning. In short, with AI systems blockchain can be safer, more dependable, and efficient.

Monetizing Data Without Compromising With Sensitive Information

Imagine a self-driving car discovers a better route and wants to sell this knowledge to other autonomous vehicles at some price. It can do so using Blockchain’s machine to machine transaction. Monetization of collected data can be a lucrative source of revenue for large companies. Blockchain can be leveraged to keep the data secure and monetize it in an appropriate manner without compromising with sensitive information. As for the AI algorithms which require huge volumes of data, a decentralised data marketplace can make the entire process more transparent. This is especially beneficial to small companies that do not generate their own data but rely on other companies instead. The process makes it incredibly cheaper to source data and keep it private.

AI Can Make Smart Contracts “Smarter”

Thanks to state-of-the-art technology, AI-enabled smart contracts are no more just a theoretical concept. It is a reality. Smart contracts tech is extending beyond the rule-based system. For example, expert systems designed for intelligent negotiation are on the rise. Intelligent systems generate and execute smart contracts by analyzing vital information, thus making them far more efficient. In that regard, when it comes to contract negotiation and determining the best strategy for achieving an agreement, Artificial Intelligence can analyze previous negotiations and determine how the parties have negotiated in the past with the help of historical data. AI can also suggest the parameters that will have the best chance of securing an agreement. For instance, the system could suggest the clause that can be the most effective. Artificial Intelligence can also analyse past contracts to identify variables that were previously overlooked. This can serve as an opportunity to leverage these variables into future contracts. This way, Artificial Intelligence can examine former smart contracts in order to determine whether improvements can be made to them in the future.

Leveraging the Convergence of Blockchain and AI

Although the specific use cases of integrating blockchain and AI will vary from business to business, data will be at the core of such convergence. Innovative companies are harnessing the power of big data and leveraging the trust and verification offered by blockchain along with the value provided by AI in any business. Dr. Steve Deng, Chief AI Scientist at Matrix AI Network, stated, “As indicated by Einstein, the measure of intelligence is the ability to change, or as pointed out by Stephen Hawking, intelligence is the ability to adapt to change. AI offers effective methods to learn from history, while blockchain allows us to build trusted relations by following business networks. Together, they give us the ability to adapt to changes. Moreover, trustworthy data is the life-blood of artificial intelligence, while the blockchain is designed to maintain trustworthy data. My colleagues from MATRIX share a consensus, which is ‘blockchain integrates time and space, while AI predicts the future from history.” The first step is for companies to determine their business requirements and identify if blockchain and AI can meet the requirements. A blockchain ecosystem could allow companies to monetize valuable data by facilitating the sharing of data with AI developers. Companies can prepare themselves to develop combined AI and blockchain solutions by improving their digital and data capabilities. Digital transformation is a precursor to AI and blockchain adoption. Managing data and business processes using digital systems provides AI initiatives with firm-wide data, enabling AI implementation at scale. Executives must also understand how to upgrade current data infrastructure to enable future AI and blockchain adoption. They must understand what kind of data needs to be collected and where the current gaps are. Building these core capabilities is like laying the foundation for a house — it greatly improves the chances of building successful blockchain and AI solutions.

Some Challenges Along The Way

Technological challenges

The most important step in building a convergent system is to ensure that the required infrastructure is in place. All the individual technologies will have to exhibit good performance. This is a concern right now, especially with blockchain, a technology that is still in its infancy and faces challenges associated with interoperability. It is also imperative to ensure that there are adequate cybersecurity measures in place for all parts of the convergent system. Especially in case of large scale systems, even a small mistake can turn out to be extremely expensive.

Quality of data

Poor quality data is perhaps the biggest hindrance in the way of Artificial Intelligence. AI models can be considerably undermined by bad data that is highly irrelevant, corrupt, or has sparse information. In such a scenario, the model can miss some important patterns or learn incorrect patterns altogether.

Wrapping up

Blockchain and artificial intelligence are two technological trends that, while groundbreaking on their own, are poised to become even more revolutionary when leveraged together. Both provide opportunities for improved oversight and accountability, while enhancing the capabilities of one another. Bringing these technologies together opens up a multitude of possibilities in the way data is used and monetized. Ultimately, blockchain can provide the trust and confidence that end users need to fully embrace and leverage AI-based business outcomes. As for the future, it seems highly likely that this combination of two independent technologies will introduce significant improvements across an array of industries, some of which may face unique challenges that this powerful duo could address.