Applications of Blockchain Technology with Artificial Intelligence

In this article, we discuss how blockchain and AI can enhance data manipulation capabilities, and some of their application uses.

5 min readFeb 13, 2020

The Blockchain Technology

Blockchain is an emerging technology that is widely focused by several countries and societies, with the potential to disrupt conventional models every industry. The decentralized system of blockchain technology is in contrast to the centralized systems of operation in use today. The blockchain technology uses a form of decentralized database architecture, where the record and authentication of certain operations are dependent upon the agreement of several parties rather than a single authority. This makes the blockchain technology, compared to the centralized technologies, safer, faster, and more transparent for everyone.

As you already know, this technology has been seen in the financial sector already, with the emergence of cryptocurrencies like Bitcoin, Ethereum, Litecoins and many other cryptocurrencies. However, the blockchain technology application is not only limited to the financial sector, it can also be extended to other areas such as smart city, healthcare, business logistics, security, etc.

Currently, researchers around the globe are attempting to incorporate blockchain into more sophisticated areas of technology such as IoT, Big Data, and, most significantly, Artificial Intelligence, which is what will be discussed in this article.

What Is Artificial Intelligence?

Artificial Intelligence (AI) is comprised of various subsets of technological advancements in fields which are concerned with machines being able to act more independently and efficiently, thus more intelligently. Some examples of AI technology exists such as speech-pattern recognition and self-driving cars. The goal of AI is to allow machines to learn from large streams of data that exists everyday and apply the knowledge to many kinds of services, thus making machines more independent and intelligent.

Blockchain together with AI

Simply said, blockchain is concerned with keeping accurate records, authentication, and execution; while AI helps in making decisions, assessing, and understanding certain patterns and datasets, ultimately making autonomous interaction. Blockchain and AI are able to work together and potentially produce seamless interactions, because they share several characteristics:

I. Data Sharing Requirement

Both blockchain and AI require some forms of data sharing. For blockchain, A decentralized database emphasizes the importance of data sharing between multiple clients on a particular network, where the data shared can be authenticated by different parties to ensure trust and security. AI relies greatly on Big Data, specifically, data sharing. With more open data to analyze, the predictions and assessments of machines are considered to be more accurate and correct, and the algorithms generated using the shared data sets are more reliable.

II. Security

In the financial sector, and of course not only limited to the financial sector, there is a big need for security when dealing with high-value transactions on the blockchain network. This is enforced via the existing protocols within the blockchain technology. For AI, the autonomous nature of the machines also requires a high-level of security in order to reduce the probability of a falsely made algorithm or data set that can result in catastrophic occurrences.

Some might say that AI requires access to several data sets, and it may compromise privacy issues. The blockchain technology is able to allow you to restrict or license the access to certain data, then what about AI? There is a technology within the AI field called Federated Learning, which is a machine learning technique that trains an algorithm across multiple decentralized devices or servers holding local data samples, without uploading or exchanging their data samples to other servers. This approach is in contrast to the traditional centralized machine learning techniques where all data samples are uploaded to one server. It enables multiple actors to build a common, robust machine learning model without sharing data, thus addressing critical issues such as data privacy, data security and data access rights.

III. Trust

The advancement and adoption of any widely-accepted technology require the element of trust, and neither AI nor blockchain are excluded. To facilitate machine-to-machine communication and data sharing in AI, there is an expected level of trust. Also, to execute certain transactions on the blockchain network, trust is required.

Application Examples

I. Blockchain Law Enforcement System

Cybervein has made use of both blockchain and AI technology in the law enforcement departments of different cities of Jiangsu province in China. The technology focuses on accelerating the integration of relevant information platforms of government departments and eliminating information silos. The data collected from the day-to-cases can be shared between the departments, where several algorithms can be produced by AI technology. The system included functions such as local team assignment, suspect characteristics validation, relevant crime cases determination, method of crime comparison, and ultimately, potential crime prediction.

The system reduces the time needed for decision making, excessive human labor required to analyse the data collected, and eliminates the potential of false analysis and report. The enhanced processes efficiently improved the work of law enforcers.

II. Medical Diagnosis

It is the policy for hospitals and doctors to keep the privacy sensitive data of the patients confidential. However, such data may help completing or enhancing certain illness data sets, where they can be used for the benefit of diagnosis for many other potential patients with the same illness or disease.

Cybervein’s Zhejiang University Cybervein R&D Center has utilized blockchain and federated learning technology to resolve the privacy issue surrounding medical data. The models built using the federated learning technology from the patient data sets stored at local blockchain nodes has successfully raised the accuracy of diagnosis for keratitis. Of course, this is done without compromising the sensitive data of the patients.

Such method can help improve the diagnosis accuracy of many other medical conditions, and will be able to help the doctors making the most appropriate treatment plans, saving millions of patients.

For the future

As both blockchain and AI are explored, more applications utilizing both technologies will surface. It will not only help improving the medical and security industries, it will help in developing smart cities, smart finance, smart business and citizen welfare. There is a lot to look forward to, the two most significant technologies of the recent years will most definitely change our way of life for the better.