Artificial Intelligence and Blockchain technologies working together will become the new dynamic duo. Blockchain — encrypted, distributed ledgers will unlock new frontiers for artificial intelligence (AI) — another cutting-edge technology.
AI is the theory and practice of developing and building machines capable of performing tasks that require knowledge. Today, cutting-edge technologies striving to make this a reality include machine learning, artificial neural networks and deep learning.
Meanwhile, the blockchain, at its core is a new filing system for digital information. Moreover, it stores the data in an encrypted, distributed ledger format and saves copies across many computers. This enables the creation of tamper-proof, highly robust datasets which are read and updated only by those with permission.
The academic community has written extensively on the potential of combining AI and blockchain technologies. However, real-world applications are sparse now. This situation will change soon.
Here are three ways in which blockchain and AI will work well together.
AI and encryption working together
Data on a blockchain is by its nature highly secure, due to the cryptography which is inherent in its filing system.
Thus blockchains are ideal for storing the highly sensitive and personal data. When smartly processed, with appropriate authority, so much value and convenience in our lives can be unlocked. For example, smart healthcare systems that make accurate diagnoses based on our medical scans and records. Also, the recommendation engines used by Amazon or Netflix to suggest what we might like to buy or watch next.
The data in these systems that are being collected from us when we browse or interact with services is highly personal. These entities need to invest to meet the standards expected of them regarding data security. However, large-scale data breaches are increasingly common and increasingly large. These breaches lead to the exposure of our private data.
We see vividly — painfully — how technology can harm rather than help. Platforms and algorithms that promised to improve our lives can actually magnify our worst human tendencies." — Tim Cook
Artificial intelligence and blockchain technologies provided security by design
Technological stewardship is the behaviour that ensures technology is used to make the world a better place for all — more equitable, inclusive, just, and sustainable.
As we’re designing the [technological] system, we’re designing society. Ethical rules that we choose to put in that design [impact the society]… Nothing is self-evident. Everything has to be put out there as something that we think will be a good idea as a component of our society.” — Tim Berners-Lee
Blockchains hold their information in an encrypted state. Thus only the private keys must be kept safe – a few kilobytes of data – for all the data on the chain to be secure.
AI has plenty to offer regarding security, too. This emerging field of AI. It is concerned with building algorithms which can process data while it is still encrypted. Any part of a process which involves exposing unencrypted data represents a security risk. Thus reducing these data breach incidents will make things much safer and secure. Systems designed to use the power of artificial intelligence and blockchain technologies together will be much more secure.
Using Blockchain to track, understand and explain AI decisions
The decisions made by AI may be difficult for us to follow. AI can assess many variables independently of each other. It continually is “learning” which ones are important to the overall tasks it is trying to achieve.
For example, AI algorithms are increasingly used in making decisions about whether financial transactions are fraudulent. I am working with MindBridge AI as it introduces the world’s first AI Auditor. Using AI, we can look at every transaction 29 different ways to detect anomalies. Current auditing tools and practices sample about 3% of the transactions. Credit card companies are using AI to determine which transactions should be blocked or investigated.
However, until AI is implemented, it will be necessary to have these decisions audited for accuracy by humans. Moreover, given the vast amount of data that needs to consider, this will remain a complex task. Walmart feeds months’ worth of transactional data across all of its stores into its AI systems. The AI platform makes decisions on what products should be stocked, and where.
As the ongoing recording decisions on a datapoint-by-datapoint basis on a blockchain, it makes it far simpler for auditing them. Auditors have confidence that the record was not been tampered with from the time when the information was recorded to the start of the audit process.
AI offers considerable advantages in many fields. However, if the public does not trust it, then AI’s usefulness will be limited. Recording the decision-making process on blockchains is a step towards achieving the level of transparency and insight needed to gain public trust.
AI manages blockchains more efficiently than humans
Traditionally, computers have been merely high-speed processors. However, without explicit instructions on how to perform a task, these machines cannot complete the work. Due to its encrypted nature, operating with blockchain data on “task-oriented” computers requires vast amounts of computer processing power. For example, the hashing algorithms that are used to mine blocks on the Bitcoin blockchain take a “brute force” approach. The computer tries every combination of characters until they find one which fits to verify a transaction.
AI moves away from this brute force approach. It manages tasks in a more intelligent, thoughtful manner. A human expert on cracking codes will become better and more efficient at code-breaking as they successfully break more and more codes. The machine learning-powered mining algorithm would similarly tackle this job. However, rather than having to take a lifetime to become an expert, machine learning instantaneously sharpens its skills when provided with the right training data.
Blockchain and AI are two ground-breaking technological trends. They will become even more revolutionary — the new dynamic duo — when we design systems that have them working together. Both enhance the capabilities of the other, while also offering opportunities for better oversight and accountability.
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