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Expert systems

Expert Systems

What is an Expert System?

An Expert System is a computer program (software) that uses artificial intelligence (AI) to reproduce the judgment of a human with expert knowledge in a particular field.

A good Expert System solves a problem accurately, quickly and is easy to use. It doesn’t necessarily require technical wizardry. AI jargon can mask a bad Expert System.

Think of an Expert System as preserving the expertise of humans in a database of knowledge. An Expert System attempts to act like a human expert on a particular subject area. The data in the knowledge base is added by humans that are experts in a particular domain and the Expert System is used by a non-expert user to acquire information.

Expert Systems are often used to help non-experts when a human expert is too expensive, the results too slow if use a human(s), error rate too high with a human(s), unintentional human bias, or it is difficult for a person to reach the location.

Components of an Expert System

  • Knowledge base

This is where the knowledge (information) is stored. It is created from information provided by human experts. It is a collection of facts and rules. The better the quality of the information and the understanding of the problems for the end user the better the results.

  • Inference engine

This acts like a search engine, examining the knowledge base for information that matches the user’s query/search.

  • User interface

When you tap on the call button on your phone that is part of the user-interface. It’s the front end that you can see and interact with. The best ones are easy to use.

A good user interface allows non-expert users to query the Expert System (ask a question) and to receive advice (an answer that is easy to understand).

What an Expert Systems is capable of doing

  1. Advising
  2. Instructing and assisting human in decision making
  3. Demonstrating
  4. Deriving a solution
  5. Diagnosing
  6. Explaining
  7. Interpreting input
  8. Predicting results
  9. Justifying the conclusion
  10. Suggesting alternative options to a problem

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