Blockchain is a widely hyped market, where technology providers and customers demand all kinds of capabilities, whether it is possible or not. So does the combination of AI and blockchain have to be twice as much hype or twice as much value?
Blockchain has also proven its value in a number of applications and industries, and AI offers real material value. So perhaps the combination of AI and blockchain will add twice as much value as what we are talking about today, when we put it together.
What Support Does Blockchain Offer AI?
Blockchain is a decentralised trade repository containing so-called smart contracts. The network is distributed, with transactions taking place at each end point without the need for central coordination. The information stored on the network can be stored at any end point that has access to the data without the need for a central server.
Whether it is a financial exchange or even a repository from the chain, blockchain can record a list of interactions between two different parties in a register that records transactions and shows when things have changed hands over time. The concept of a blockchain is that each block has its own information, and this information is contained in the connections between the blocks before it, which evolve into a chain that provides a verifiable on-chain repository. Blockchain also helps to ensure trust and verifiability of the data, as each block of the blockchain contains different information that is encrypted.
To change the chain, a consensus must be reached between all parties on the change, and this chain has countless other places to distribute it to other parties. A single actor can change the information in a block, which invalidates the entire information chain of that particular block and breaks the chains.
If two parties want to conduct secure and trustworthy transactions without the use of intermediaries, this would be ideal for a blockchain. The blockchain concept complements this by triggering decentralised code parts when certain off-chain measures are fulfilled. So how can blockchain help AI in machine learning and its potential applications in artificial intelligence? The first advantage is that machine learning can be shared between parties without middlemen, and vice versa.
A good example is facial recognition software: when other devices upload their own facial recognition data, they can also use it for face recognition models without having to upload it themselves. There is no central control over facial recognition, as is the case with blockchain, and as such the data is stored and owned by the company.
AI systems can also use blockchain to facilitate data exchange between multiple models. This approach also allows learning to be done through machine learning, which is integrated with AI in the blockchain. A good example is the use of blockchain as a platform for cross-platform data exchange between different AI systems, such as neural networks.
When an online shop knows a shopper’s preferences and the customer then switches to another website, the two sites can be linked together to share trustworthy personalisation information. This could potentially be a great solution for small trading sites that want to share personalised information. The advantage for customers is that they can receive a tailored shopping experience in exchange for the sharing of their information. Instead of collecting their own personalisation data, these companies can share it with others to compete with companies like Amazon and Walmart, which have already developed the ability to collect information about their customers through data mining and other forms of data sharing.
Data breaches can be prevented by storing and passing on information about payment systems on the blockchain instead of a central data server.
So Blockchain can Benefit AI?
Blockchains can be used to exchange models and data, but they can also play an important role as a way to exchange masterminds between multiple AI systems. Combining things that can be learned from the environment and sharing them with an AI system in a network is a way to bring together the shared learning benefits of blockchain and AI. I cannot be impartial in the face of the sheer amount of information that comes in from different areas and angles.
In reality, neural networks are black boxes without any real transparency or explanation. If something goes wrong in a neural network, you have no idea how to identify and correct the problem. The problem is that there is no clear idea of which inputs lead to which outputs, and there are no rules for how the entire sequence is affected. These applications are challenging an explicable AI, but in reality they are a black box with no real transparency and explanations.
But by using blockchain, we can record how individual actions lead in a non-serious way to a final decision that allows us to go back and see where things went wrong and then fix the problem. Blockchain would be used to capture all of this in a way that would not be altered later. Anyone can go in, see what has happened, and trust is increased because the blockchain element is impartial and only serves for storage and analysis.
After all, AI systems can be used to improve blockchain in general, and machine learning can keep an eye on what happens to blockchain.
You can scan the system for normal behaviour and use it to warn users when something that seems unusual happens. You can search the type of data stored on a particular server and perform actions, or you can use a system with certain parameters, such as the name of the server or the number of users on the network that can be used to alert the user about what has happened.
While the world of AI and blockchain may be full of hype, there are two new technologies that can be mutually beneficial to achieve real results for those who want to implement AI or blockchain in their environment today. AI systems can help make blockchains safer, more reliable and more efficient.