They used to be little more than buzzwords, but that’s not the case anymore. Blockchain and artificial intelligence (AI) have evolved into leading technologies that power innovation across almost every industry.

Artificial intelligence refers to machines that are built to perform intelligent tasks that have traditionally been accomplished by humans. Blockchain is a decentralised network of computers that records and stores data to display a chronological series of events on a transparent and immutable ledger system.

It goes without saying that each technology has its own individual degree of complexity, but both AI and blockchain are in situations where they can benefit from each other and help one another, and it can take the exploitation of data to new levels. At the same time, the integration of machine learning and AI into blockchain, and vice versa, can enhance blockchain’s underlying architecture and boost AI’s potential.

Additionally, blockchain can also make AI more coherent and understandable, and we can trace and determine why decisions are made in machine learning. Blockchain and its ledger can record all data and variables that go through a decision made under machine learning.

Our Data going into AI – why Blockchain?
Through data, AI receives information about the world and things happening on it. Basically, data feeds AI, and through it, AI will be able to continuously improve itself.

On the other side, blockchain is a technology that allows for the encrypted storage of data on a distributed ledger. It allows for the creation of fully secured databases which can be looked into by parties who have been approved to do so. When combining blockchains with AI, we have a backup system for the sensitive and highly valuable personal data of individuals.

Medical or financial data are too sensitive to hand over to a single company and its algorithms. Storing this data on a blockchain, which can be accessed by an AI, but only with permission and once it has gone through the proper procedures, could give us the enormous advantages of personalised recommendations while safely storing our sensitive data

Monetising Our Data – Our Choice!
Monetising collected data is a huge revenue source for large companies, such as Facebook and Google.

Having others decide how data is being sold in order to create profits for businesses demonstrates that data is being weaponised against us. Blockchain allows us to cryptographically protect our data, and have it used in the ways we see fit. This also lets us monetise data personally if we choose to, without having our personal information compromised. This is important to understand in order to combat biased algorithms and create diverse data sets in the future.

The same goes for AI programs that need our data. In order for AI algorithms to learn and develop, AI networks will be required to buy data directly from its creators, through data marketplaces. This will make the entire process a far fairer process than it currently is, without tech giants exploiting its users.

AI & Blockchain
As AI algorithms become smarter through learning, it will become increasingly difficult for data scientists to understand how these programs came to specific conclusions and decisions. This is because AI algorithms will be able to process incredibly large amounts of data and variables. However, we must continue to audit conclusions made by AI because we want to make sure they’re still reflecting reality.

Through the use of blockchain technology, there are immutable records of all the data, variables, and processes used by AIs for their decision-making processes. This makes it far easier to audit the entire process.

With the appropriate blockchain programming, all steps from data entry to conclusions can be observed, and the observing party will be sure that this data has not been tampered with. It creates trust in the conclusions drawn by AI programs. This is a necessary step, as individuals and companies will not start using AI applications if they don’t understand how they function, and on what information they base their decisions.

Let’s look at some use cases….

Coffee anyone?
Certain companies in the coffee sector use mobile apps, bots and blockchain for their supply chain to create a more transparent and ethical journey from bean to cup. The AI measures the quality of coffee beans and predicts weather and growing patterns, while the blockchain immutably records the farm where the beans originated and the exact specifications of a coffee shipment. It even acts as a payment ledger to ensure that all parties are paid quickly and fairly.

Your health deserves one version of the truth
One of partners, BurstIQ, have created a “Health Wallet,” which combines AI, blockchain and big data to holistically manage a patient’s data. The Burst IQ wallet gives a patient’s team of healthcare professionals access to his or her health records and wellness plans. The healthcare professionals can use or trade patient data for different scientific studies or to learn more about a specific disease. However, the blockchain lets patients keep private their personal identifying information while sharing only big-picture health data.

Arty Tech
For the art sector there is an application using artificial intelligence and blockchain to certify and verify works of art in real-time. The blockchain allows artists to create tamper-proof certificates of work that ensure credit and immutability. The blockchain-backed certificates feature encryption and time-stamping that instantly stop fraudulent copies from being sold as originals. While older pieces of art and collectibles will still need to be verified by experts, blockchain can immutably document the origin of every new work.

Conclusion
Putting AI and Blockchain together has the potential to use data in ways never before thought possible. Data is the key ingredient for development and enhancement of AI algorithms, and blockchain secures this data. It allows us to audit all intermediary steps AI takes to draw conclusions from the data and allows individuals to monetise their produced data.