What can you expect from 2023?
Blockchain is considered a shared and permanent ledger that will be used for encryption of data in the future. AI engine, on the other hand, enables an individual to analyze and make decisions from the collected data. It is worth mentioning that each technology has its many skin tones, but artificial intelligence and blockchain together will bring many advantages.
This combination of the inherent strength of blockchain to provide immutable data that can be trusted implicitly and AI’s ability to draw valuable insights from that data is very complementary.
Advantages to highlight for 2023:
Due to the distributed ledger’s immutability and cryptography, the data in a blockchain is well protected. A blockchain is ideal for storing highly sensitive personal data such as medical notes or investment portfolios.
On the other hand, AI requires data continuously and in high volumes. What is underway now are algorithms that allow AI to work with encrypted information without revealing it.
However, it must be noted that the blockchain is secure at its base, and several layers and applications are vulnerable. So machine learning in the financial industry will help improve the deployment of blockchain apps and predict possible system breaches, improving security.
User trust
There is an actual trust deficit between AI’s decision-making abilities and the public’s trust in the accuracy of such decisions. Regardless of its performance, people won’t use AI if they don’t trust it. Putting the brakes on the wider use of AI is the impossibility of explaining decisions made by the computer. With blockchains able to record the decision-making process, AI can gain public trust much faster.
Blockchain and AI can make the way computers think more transparent. A distributed ledger can store all decisions made by AI, data point by data point, and make them available for analysis.
Blockchain and the distributed ledger can store large amounts of encrypted data, and AI can manage and analyze it efficiently with each new use case. This synergy will give rise to new markets for the combination of the two, giving rise to data, model and AI marketplaces.
Giant Web2 monopolies such as Google, Facebook and Amazon have access to vast amounts of data useful for AI processes for analysis and decision making. Yet these monopolies ensure that this information is unavailable to others. Financial and voluntarily shared Web3 data can provide an antidote to such hoarding.
AI can benefit the security of online blockchain operations like exchanges by improving how we work with data. Computers process encrypted data by going through multiple combinations of characters in search of the correct one to confirm a transaction. Like a human hacker, AI learns and sharpens its skills with each successful code crack. But unlike a hacker, AI doesn’t need a lifetime to learn the combinations. With the right training data, AI can do that almost instantly.
Optimizes energy consumption and reduces IT’s carbon footprint
When it comes to data mining is a very energy-intensive process. AI has proven tools via machine learning to handle the problem. Google’s data centers have reduced energy consumption by 40% by training DeepMind AI on historical data from thousands of sensors in a data center. The same principle can be applied to mining, leading to lower prices of mining hardware.
Smart contract audit and verification
Blockchain systems have thousands of smart contracts programmed to release and transfer funds automatically when certain conditions are met. Network consensus must be achieved to operate smart contracts on the blockchain. Most smart contract codes are public and can be reviewed by anyone. Hackers can patiently and thoroughly go through every line of code looking for loopholes. AI can help verify smart contracts and predict exploitable vulnerabilities.
Final thoughts
Every time a new technology has emerged, critics have picked out flaws in it or been afraid to engage their business and fully exploit its benefits.
When cloud storage was introduced, critics bemoaned its privacy and security risks. AI was met with more serious warnings, with reports of “the increasing use of AI systems to lead to the expansion of existing threats, the introduction of new threats, and a change in the typical nature of threats.”
Blockchain is seen in a similar light using terms such as “black money” or the “underground economy”. Nevertheless, each of the above technologies is adapted to cover these concerns by creating hybrid models or fixing security issues.
The year 2023 will be a year for an amalgamation of AI and blockchain to build expert systems that can optimize and make reliable predictions in dozens of business verticals, from supply chain to food safety and from HR to determining consumer preferences.
