Blockchain and Artificial Intelligence are on nearly every chief knowledge officer’s list of game-changing innovations, poised to transform industries. Both technologies have numerous advantages, but they also have their own set of limitations when it comes to adoption. It also is reasonable to suggest that the excitement around both technologies alone may be unparalleled, therefore the idea of combining these two ingredients may be considered as creating a modern-day version of IT pixie dust by some. Simultaneously, there is a reasonable approach to consider this mix that is both logical and practical. 

According to PwC, Artificial Intelligence will add $15.7 trillion to the global economy by 2030, resulting in a 14 percent increase in global GDP. Gartner predicts that the business value contributed by blockchain technology will reach $3.1 trillion by the same year. Hence, the opportunities for cryptography jobs and block mining jobs have increased.

What is blockchain? 

Blockchain technology is a type of distributed ledger technology that uses a chain data format to store information. It is a novel distributed infrastructure and computing paradigm that leverages encryption to assure data security and reliability. Moreover, it assures the dispersed node consensus process to check transaction information, and synchronize the entire network.  

What is Artificial Intelligence?

Artificial Intelligence (AI) encompasses the following key technologies: computational vision technology, language processing technology, cross-media rationale technology, intelligent adaptive technology, swarm-based technology, autonomous drone system technology, smart chip technology, and brain-computer interface technology, which can be extensively employed in a variety of industries, including medicine, automated cars, education development, sports, and amusement. 

Impact of AI and Blockchain technologies on different industries

1. Manufacturing 

Companies have begun to depend on blockchain-based procedures and smart contracts as part of the manufacturing process to facilitate manufacturing, openness, protection, and regulatory checks. Instead of creating set equipment periodic maintenance, AI and ML predictive algorithms are utilized to construct flexible plans that occur at the precise moments they should. Quality assurance and testing of the product have also become completely sophisticated, with adaptable and machine graphics algorithms employed to detect excellent and faulty items, particularly in extremely sensitive areas. Many of the best AI/ML consulting firms are assisting such businesses with their AI and blockchain implementations. 

For instance, an automotive company incorporates disruptive technology, using AI and Blockchain to increase vehicle capabilities and safety. Furthermore, the company employs blockchain technology to transmit data more safely and swiftly, providing its customers with peace of mind; whether it is for parking, recharging, or third-party access needs such as limited accessibility to a car or a shipment. 

2. Energy and Utilities

Blockchain technology is assisting in the facilitation of energy exchanges in the Energy and Utilities industrial sector. For example, an energy-based startup is adopting peer-to-peer blockchain energy utilization. Smart energy microgrids are also gaining prominence as a means of producing sustainable energy supplies. A blockchain-based invention is also being used by a New York-based startup, to enable energy creation, conservation, and trade for local communities. To track and control energy transfers, the technology use microgrid smart meters, in conjunction with smart contracts. 

3. Food

Blockchain plays an important role in food production mainly because there is a huge need of processing a vast amount of data. This accurate information is critical to the success or failure of the food production project. With blockchain and BPM, it is possible to track the journey of a food product from the field to the store shelves. Thus, companies have the opportunity to monitor the project in real-time, find possible errors fast, and assure transparency. Finally, blockchain can have the greatest impact in making it easier to verify the origin of food products. If the entire manufacturing process is recorded on the blockchain, businesses would be able to prove to customers that their product is genuine.

Ways to Combine AI and Blockchain

AI and encryption complement each other quite well

Data stored on a blockchain is, by definition, incredibly secure, thanks to the cryptography built into its file system. This implies that blockchain technologies are excellent for holding highly sensitive, personal information, which, when processed intelligently, may unlock a wealth of value and ease in our business life. Consider smart healthcare systems that make accurate assessments based on the health scans and data, or even the recommendation systems used by Amazon and Netflix to recommend what we should purchase or view next. 

The data supplied into these systems is quite personal. Businesses who deal in it must put up substantial sums of money in order to achieve the data security requirements that are expected by them. Nonetheless, large-scale data breaches resulting in the loss of private information are becoming more regular. 

Blockchain databases store information in an encoded fashion. This means that the secret keys — a few kilobytes of data – must be maintained safely in order for all of the data on the network to be protected. 

AI has a lot to offer in terms of security as well. An emerging field of Artificial Intelligence is focused on developing algorithms capable of interacting with data while it is still encoded. Because any portion of a data process that exposes unencrypted data poses a security risk, eliminating these instances could assist to make operations much safer. 

Blockchain can help businesses track, analyze, and explain AI judgments

AI decisions can be difficult for humans to comprehend at times. This is due to their ability to examine a vast number of variables independently of one another and “learn” which ones are crucial to the overall task at hand. 

However, for a little longer, these judgments will need to be reviewed for accuracy by humans. But, given the wealth of information that might be considered, this can be a difficult undertaking. If judgments are documented on a blockchain on a datapoint-by-datapoint basis, they may be audited much more easily, with the assurance that the record has not been altered between the time the information was entered and the commencement of the audit process. 

To Sum up

No matter how plainly we can see that AI offers tremendous advantages in many industries, its utility will be seriously restricted if the public does not believe it. Storing decision-making processes on blockchains can be a step toward obtaining the kind of openness and understanding into robot minds required to achieve public confidence.

Blockchain technology is transforming countless industries and business disciplines, including Business Process Management (BPM) and Workflow Management. When most of us think of blockchain technology we think of Bitcoin or related innovations, such as hardware wallets. We might also think of the ways Bitcoin has challenged the traditional finance world, leading to new forms of banking and trade finance. What’s more, many bring to mind different digital platforms that enable consumers to trade or invest in popular cryptocurrencies. Most people don’t think of business processes or blockchain workflow automation. However, the utility of blockchain technology is vast. With the right datasets, properly applied, blockchain technology has the power to transform rapidly your business. 

How Does Blockchain Technology Work?

In order to keep things simple let’s begin with Bitcoin (BTC). Bitcoin acts as a store of value. When a trader, let’s call her “Laura”, purchases a Bitcoin using US dollars (USD) she is essentially converting her USD into BTC.  

This transaction is then recorded on a digital ledger, built out of “blocks” (records), confirming that Laura has ownership of this Bitcoin. In a traditional transaction, a centralised authority has to confirm this procedure. With blockchain, a network of individuals confirms all the transactions.  

There are several ways that transactions can be confirmed on a blockchain. Some, like Bitcoin, use Proof of Work consensus. This requires computers to solve transactions in order to “confirm” a transaction as legitimate. Others use Proof of Stake, which requires users to “lock” cryptocurrency to validate a block or nodes. This allows specific computers to approve transactions without the heavy computing power Proof of Work calls for.  

No matter how a blockchain secures itself, the end goal is to add barriers to making and sending transactions. This prevents users from spamming a network with false transactions and “double-spending” money that they don’t have.  

The most interesting thing about blockchain technology is that the contents of a block are completely irrelevant! In theory, Laura could be recording a housing deed, customer data, or even her vote using Bitcoin or another blockchain solution. 

This is exactly what has begun to happen thanks to the creation of smart contracts — computer programs that automatically run when given criteria are met.  

Blockchain Workflow Automation and Business Process Management Go Hand in Hand

Blockchain has high potential from a business process management perspective. It can bring multiple stakeholders together and provide them with transparent tools to improve processes across companies. For instance, this makes it easier for different participants to standardise their reporting processes. Furthermore, it enables far more scalable reporting systems than the ones currently exist.  

A key factor for a blockchain to work is structured data. This fact forces companies to review their internal processes and ensure that everything is being done correctly. It encourages operational excellence and helps to record and catch individuals not following the system. 

To understand how this works, let’s take a look at what would happen with a supply chain management case. Today you would need to trace all products based on their ID number. Then, you would need to work backward to figure out where the problem occurred. Every time you would hope that every person in a siloed supply system had followed business processes correctly. Consequently, this is expensive, time-consuming, and potentially risky to the public. 

Blockchain works as a shared database. Inside this database, each product would have a unique ID number.  This means that a company could track all those ID numbers and know exactly what happened and wherein the supply chain. It also enables them to quickly understand the scale of a potential threat and act accordingly. 

Case Study: Blockchain In Food Production  

The key benefit of blockchain from a business process management (BPM) standpoint is that it can make data easily accessible and untameable without the need for centralised confirmation. This is particularly useful in sectors such as charity or food production, where good information is critical to a project’s success or failure.  

Let’s take a look at the example of food production. This industry has 3 key pain points at the moment:  

1.  Lack of communication between a large number of participants operating in information silos.
2. A complicated supply chain where the correct information is essential in order to fight fraud and avoid costly recalls.  
3. Consumers find it difficult to verify where their food is from and whether they get what they pay for.   

Blockchain can solve all of these problems and help to encourage better business operation practices thanks to the necessity of maintaining good data. With blockchain workflow automation, it is possible to track the journey of a food product from the field to the shop shelves. 

The most immediate area where blockchain technology can make a positive impact is in breaking down information silos. Blockchain can be accessed by anybody with a public key, but the information can’t be altered. 

This would enable companies to monitor the status of a project in real-time, and be forewarned of any potential problem. It can even use IoT technology to collect metadata about refrigeration and transport requirements and append that to each individual shipment.  

When something does go wrong, blockchain makes it much easier to get correct information about where the error happened. Each participant in the chain can be given a unique ID, thus ensuring transparency and trust in the overall chain. Also, this means that it is easier for companies to act quickly and limit the scale of threats.  

At last, the final area where blockchain can make its biggest impact is by making it less difficult to verify the origin of food products. If the entire production process was placed on the blockchain, with each step recorded, it would be possible for companies to prove to customers that their product is legitimate. 

Conclusion

This use case isn’t just a pipe-dream. Many businesses have implemented a significant number of blockchain projects in the real business world. Blockchain workflow automation improves almost every aspect of business operations: from product sourcing to financial agreements, providing customers more transparency.

To sum up, as scalability continues to improve, it is likely just a matter of time until your business implements a blockchain solution of its own.

Chapter 1: Introduction

As mentioned consistently across the internet, Blockchain technology is, in a way, a decentralized network of nodes that stores blocks of data. It’s supposedly secure, reasonably fast and free of any central governing body. Thousands of independent computer systems uphold nodes that can be part of a blockchain network. Thus, this technology improves the integrity of the stored data.

Contracts, transactions, and the proof that those happened are among the defining structures in our economic, legal, and political systems. They define assets and construct organizational boundaries. What’s more, they establish and approve identities and chronicle events. They are the tool that governs interactions internationally, between organizations, communities, and individuals. They are the guidelines of managerial and social action. And yet, the tools that are already in place to handle this plethora of interactions, fail majestically. They’re like a rush-hour gridlock trapping the fastest F1 car in the world. In a digital world, we should drastically change the way we process and handle data, to ensure that these interactions are meaningful.

Chapter 2: What are the problems that real people face in the digital age?

Let’s look at the world from a prism of a global, boundless economy. Taking also into consideration the rules that a free market model encapsulates, the number of problems seems indefinite. Ιf one takes a step back and captures the big image, one can observe that all these problems tend to get down to the same fields. Which are these fields? Communication, repeatable actions (aka automation), transportation and the providing of action confirmation. Those exact fields are the foundation blocks where any BPM system tries to provide a neat solution. Every industry revolving around these fields (almost each and everyone) is facing constant challenges that sometimes prevent it from achieving a set target. Although the actual product that the industry is responsible for might be absolutely fine, the way that the industry handles business processes might result in bottlenecks. These bottlenecks could have a large impact on the delivery of that exact product.

Real-world challenges that society currently faces include the endless amount of bureaucracy, which almost every acting entity has to face, in order to achieve the desired result. Τhe centralization of networks, applications, and data could potentially lead to catastrophic attacks on a global scale – including and not limited to –  banking systems. The never-ending debate upon electronic voting and how it could be carried out securely and at the highest score of integrity constitutes an additional problem. Organizations and businesses have also to face the real-estate trading that constantly gets manipulated by the largest stakeholder and the growing needs of infrastructure in order to operate at the desired level.

All these never-ending never -solved and never-concluded problems get larger and larger as data gets bigger.
Solutions that rely upon infinite resources, such as a Blockchain network of computer systems dispersed across the globe, are the best practice in order to avoid a data Armageddon.

Chapter 3: How can Blockchains solve critical real-life problems

Due to the nature of a Blockchain, every member that joins it, is privileged and obliged at the same time. Privileged, because of the free or by payment access to the resources that this network provides. Obliged, because of being a part of this expanded network that aims to give resources to solutions that handle big-data applications and manage large-scale transaction handling.

This creates a network model that expands asynchronously in relation to the growing resource requirements. For example, if in a given network each client is also a server and traffic gets spread to every node then, as resource requirements grow, resource availability grows, too. Maybe not in a 1-1 ratio, but at a specific rate in order to handle today’s and tomorrow’s computing needs.

Also, because of the decentralized model of Blockchain technology, data integrity is totally assured. Various mechanisms ensure that copies of data are stored in multiple nodes across the network. If one system is compromised and data gets deleted or corrupted, validation mechanisms can ensure that data remain intact.

Chapter 4: A conclusion on blockchains and their immediate future

In sum, blockchains can be a powerful tool for every organization and business that aims to solve real-life problems.  This powerful tool is useful to deal with large-scale data and a countless amount of transactions. The key to success is to go beyond simply using this technology. Success leads to the execution of the same processes faster and cheaper.

Solutions should presuppose that blockchains do not just become another platform in which, existing solutions reside. The solution’s architecture should differ according to the specific nature of the blockchain technology. This won’t be an easy path. Organizations need to evolve from the service provider business model that they have used for decades.  At the same time, they should forge partnerships in order to aggregate a broader portfolio of services. A decade from now,  industries such as the telecom market and logistics will look dramatically different. The only question is whether traditional ones have the foresight to take the steps necessary to win.

Artificial Intelligence (AI) – especially Machine Learning and Deep Learning – has become popular among businesses and many organizations have begun adopting this technology in their operations.
Artificial Intelligence refers to the feature of having the ability to provide computational power for creating cognition in machines. This means that machines can perform human activities such as planning, reasoning, problem-solving, etc.
More and more enterprises have started to identify the need of implementing systems that are powered by AI in their procedures.

What are the Risks of Centralized AI Solutions?

The current AI solutions are completely centralized and involve a lot of risks for the companies that implement any of them. Some of those risks are:
The Rich Get Richer Problem: Many of the AI solutions in the market are provided by large companies that control huge datasets. These datasets keep increasing constantly as the more data they own, the more datasets they produce.
Dataset Owners Influence Populations: Centralized AI systems can influence populations and direct knowledge based on their willingness. For example, imagine the influence that political campaigns launched on Google, Facebook, Twitter, etc. have and how they can impact the outcome of an election.

What is Decentralized Artificial Intelligence (AI)?

Decentralized AI is one of the most promising trends in the AI space. These models provide the opportunity for large companies that control huge datasets to be independent.
Blockchain technology has contributed a lot to the development of this trend. It has paved the way for a decentralized ecosystem where data scientists, data providers, consumers, and all other involved parties collaborate in order to create AI architectures without the need for a centralized control authority.

How Decentralized AI can be Achieved?

Many subsets of cryptography have been already developed, which helps the empowerment of a Decentralized AI environment. These techniques offer ways of distributing datasets among many counterparts securely and ensuring the confidentiality of data.

Homomorphic Encryption

Homomorphism is one of the greatest technological advances in the cryptography space. This type of encryption allows the execution of specific types of computations to be done in the ciphertext and provides results that are also encrypted in the ciphertext. Having said that, this allows parties to execute computations in datasets without any need for decrypting them. The two types of homomorphic encryption algorithms that exist are Partial Homomorphic Encryption (PHE) and Fully Homomorphic Encryption (FHE).

Adversarial Neural Cryptography or GAN Cryptography

GAN cryptography is a model that was pioneered by Google and is explained thoroughly in the “Learning to Protect Communications with Adversarial Neural Cryptography” paper that was published at the end of 2016. With Adversarial Neural Cryptography, the confidentiality of datasets is ensured, and data are exchanged among different parties by maintaining high levels of privacy.
This technique gains great momentum through time and has the potential to be mainstream in decentralized AI applications.

Secured Multi-Party Computations (sMPC)

sMPC is the foundation of the development of new blockchain protocols. This security technique ensures the computation of a public function based on private data while keeping their inputs secret. Owing to that, sMPC architectures enable the creation of AI models without revealing the datasets to any third party.
Creating a decentralized AI environment needs an environment that is emphasized in high levels of security and data integrity protection. There are several techniques that can be implemented for the development of a decentralized model that allows parties to make computations of datasets without any central authorities.

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