Module 1: Foundations of AI · BoK IV.A
Expert systems
An older flavour of AI that mimics a human expert in one field via a knowledge base, inference engine and user interface. The canonical example is a medical diagnosis system, designed to support and assist humans, not replace them.
An Expert system is an older flavour of AI that mimics the decision-making of a human expert in one specific field, drawing inferences from a knowledge base. It has three parts:
- Knowledge base - organised collection of facts from human experts in one domain. Sometimes allowed to pull extra information from external sources
- Inference engine - extracts relevant knowledge and applies it via a rule-based approach. Often includes a module letting users review the decision-making process
- User interface - the end user inputs a problem or question and receives an output, the resolution
Exam flash
Canonical example → a medical diagnosis system helping doctors determine a cancerous growth's type and stage. Deployed in finance, healthcare, agriculture, engineering. Designed to support and assist humans, not replace them.
Key terms - quick answers
What is “Expert system”?
Older AI mimicking a human expert in one field via a knowledge base, inference engine and user interface.
What is “Knowledge base”?
Organised collection of facts from human experts in one domain within an expert system.
What is “Inference engine”?
Expert-system component applying knowledge via a rule-based approach, often showing its reasoning.