When correctly incorporated, artificial intelligence can assist your company in becoming ready for new revenue streams. It has demonstrated success in several industries, including data security, healthcare, eCommerce, and fraud detection.

It is now even more essential to comprehend the fundamental ideas and principles of artificial intelligence and prepare for its implementation as organizations have grown more familiar with the terms artificial intelligence, machine learning, and big data. Expert Systems is one such idea. Let’s talk about expert systems in AI and learn more about them.

What is an expert system?

A computer system or piece of software known as an expert system simulates the judgment and decision-making of an expert human or artificial intelligence organization. This is done by locating pertinent data in its knowledge base and analyzing it in the context of the user’s issue.

An expert has loaded and tested a knowledge base, a collection of learned experience, into the system. Specialists in a particular field update the knowledge base, and non-expert users utilize this software to find information.

Expert systems’ knowledge can be improved by expanding the knowledge base or the rules. The performance of the expert system will improve as more experience is added to it.

Expert systems are designed to tackle complex problems by reasoning through bodies of knowledge, primarily represented as if-then rules instead of standard procedural codes. Expert systems are characterized by their excellent reactivity, reliability, understandability, and performance. 

Expert systems specialize in a specific field of study, such as engineering, science, or medicine. Some well-known expert system examples include DENDRAL, MYCIN, R1/XCON, PXDES, and CaDet.

Expert systems offer the following benefits

• Enhances the quality of decision-making.
• Cost-effective because it eliminates the need to pay for expert human consultation when an issue needs to be solved. 
• Offers quick and reliable solutions to challenging issues in a particular field. 
• It gathers limited knowledge and effectively utilizes it. 
• Provide coherence when responding to repeated problems.
• Keeps a good deal of information. 
• Provide prompt, precise responses.
• Gives a suitable justification for the choice made.
• Resolves difficult and complex problems. 
• Works steadily and without getting tired.

Components of Expert Systems

Knowledge Base: The Knowledge Base consists of fundamental concepts, procedures, and intrinsic knowledge pertinent to the problem domain. 

It includes all information about the area of concern. It resembles a vast repository of information from numerous specialists on a particular subject.

User Interface: The expert system interacts with users via an interface, receives user queries in a readable format, and sends those queries to the inference engine. After receiving the inference engine’s response, it shows the user the output. To put it another way, it’s a user interface that enables a non-expert user to interact with an expert system to address a challenge.

Interface Engine: The inference engine serves as the brain of the expert system. It chooses facts and rules to utilize to respond to the user’s query. It’s a general control technique for using deductive knowledge from the knowledge base to task-specific data to arrive at a solution or conclusion.

Applications of Expert Systems

Expert systems excel at pattern recognition, classification, configuration, diagnosis, and reasoning. It is often used in many different industries, such as planning, scheduling, games, accounting, medical diagnostics, and coding. The American Medical Association approved the Pathfinder system as the first expert system. 

The hematopathology diagnosis decision-theoretic expert system was created in the 1980s at Stanford University. It is also employed in the banking sector to help bankers make business loan decisions and spot any potential fraud or suspicious activity. Automobiles and other electronic items like cameras are also designed and developed using expert systems. In addition, expert systems are used in the knowledge domain to provide the client with the necessary knowledge.

Conclusion

Think about the various benefits that Artificial Intelligence and expert systems can provide as your business prepares its plans for future expansion. The advantages of implementing a modern high-tech solution for your company are endless, ranging from cheaper expenses to improved efficiency and production rates. Making a wise decision can be as easy as selecting an intelligent system to handle routine chores and deal with issues that prevent your business from reaching its full potential.