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Integrating AI Into Blockchain Can Help The Economy In More Ways Than You Think

Integrating AI Into Blockchain Can Help The Economy In More Ways Than You Think


Artificial intelligence is one of the major driving forces of innovations loved by entrepreneurs and users alike. It has disrupted numerous industries including customer service, agriculture, manufacturing, healthcare, tech support and many more.



Blockchain technology is another force to be reckoned with. Although it is presently popular in the BFSI sector, there are endless uses for Blockchain technology, such as, education, transportation, voting, law and enforcement, among others.

Blockchain, though powerful on its own, becomes enhanced to a whole new level when coupled with AI. New features and capabilities become unlocked, enhanced, and more secure through their convergence.

How AI Can Add On To Blockchain

The confluence of AI in blockchain creates perhaps what is the world’s most reliable technology enabled decision making systems that are virtually tamper-proof and provides solid insights and decisions. It holds several benefits like:

  • Improved business data models
  • Globalised verification systems
  • Innovative audits and compliance systems
  • Smarter finance
  • Transparent governance
  • Intelligent retail
  • Intelligent predictive analysis
  • Digital Intellectual Property Rights

Technical Enhancements That AI Can Enable

Security: With the implementation of AI, Blockchain technology becomes more secure by creating secure future application deployments. AI algorithms which are increasingly making decisions about whether financial transactions are fraudulent and should be blocked or investigated is a good example of it.

Efficiency: AI can help optimise calculations to reduce miner load which results in less network latency for faster transactions. AI enables to reduce the carbon footprint of blockchain technology. The cost which is applied upon miners would also be reduced along with the energy spent if AI machines replace the work done by miners. As the data on blockchains grows by the minute, AI’s data pruning algorithms can be also be applied on the blockchain data which automatically prunes the data which is not required for future use. AI can introduce even new decentralised learning systems such as federated learning or new data sharing techniques that make the system much more efficient.

Trust: The iron cast records of blockchain is considered one its USP. Applied in conjunction with AI means that users have clear records to follow the system’s thinking process. This, in turn, helps the bots trust each other, increasing machine-to-machine interaction and allowing them to share data and coordinate decisions at large.

 

Better Management: When it comes to cracking codes, human experts get better over time with practice. A machine learning-powered mining algorithm will eliminate the need for human expertise as it could almost instantaneously sharpen its skills if it is fed the right training data. So, AI also helps in managing blockchain systems better.

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Privacy And New Markets: Making private data secure invariably lead to it being sold, resulting in data markets/model markets. The markets get easy, secure data sharing that helps smaller players gain Blockchain’s privacy can be more increased by executing “Homomorphic encryption” algorithms. Homomorphic algorithms are the ones using which operations can be performed on encrypted data directly.

Storage: Blockchains are ideal for storing the highly sensitive, personal data which, when smartly processed with AI, can add value and convenience. Smart healthcare systems that make accurate diagnoses based on medical scans and records is a good example of that.

Real-Life Applications:

  • Triggmine, a product converges AI in blockchain within a single marketing automation system. It has led to the company being one of the world’s first decentralised platform for marketing automation.
  • Mithril is a social media app which makes content creation and engagement on social media worthwhile for users, in the form of crypto. Their social media platform enables what Mithril has termed “social mining” in which users are rewarded for the impact and influence of their content. They also make extensive use of AI in their overall working.
  • Bubblo is an AI-based real-time discovery app that uses blockchain technology and virtual reality to build a marketplace allowing users to monetise their personal information for rewards. It provides users personalised recommendation of bars, restaurants and other venues.
  • Back in India, Signzy couples artificial intelligence with the blockchain to make secure, compliant and user-friendly transactions in banks. It is harnessing the power of AI and blockchain to enable their clients to adapt digitisation and offer fully digital experiences to their users. It offers products such as RealKYC which is a bank-grade digital KYC and Digital contracts which is a secured digital contract enabled by Aadhaar and Biometrics
  • EVS is an employee verification platform created by SpringRole which verifies employees’ credentials and skills. It uses blockchain as a platform where the feedbacks registered are fed into an AI system along with using a smart contract method which digitally facilitates, verify, or enforce the negotiation or performance of any contract.

Outlook

As the industries are seeing newer developments, there will be more blockchain and non-blockchain based products looking to leverage the advantages that AI can offer.

The long-term potential for both blockchain and AI is staggering, so combining the two certainly makes such projects worth beneficial. It enhances each other’s capabilities as seen in few instances above while offering opportunities for better oversight and accountability. These developments simply point towards why AI should not be brought into blockchain.


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