Expert System
An early AI system that mimics human expertise in a specific domain using a knowledge base of rules and facts. Expert systems were the dominant AI approach in the 1980s.
Why It Matters
Expert systems demonstrate that AI does not always need deep learning. For well-defined domains with clear rules, they remain effective and interpretable.
Example
MYCIN (1970s) diagnosing bacterial infections using ~600 rules like 'IF the infection is primary-bacteremia AND the site is gastrointestinal THEN consider E. coli.'
Think of it like...
Like a very detailed decision flowchart created by capturing everything an expert knows — it follows their logic perfectly but cannot learn new things on its own.
Related Terms
Symbolic AI
An approach to AI that represents knowledge using symbols and rules, and reasons by manipulating those symbols logically. Symbolic AI dominated before the deep learning era.
Knowledge Base
A structured or semi-structured collection of information used by AI systems to retrieve factual data. In the context of RAG, it typically refers to the document collection that the system can search.
Decision Tree
A supervised learning algorithm that makes predictions by learning a series of if-then-else decision rules from the data. It creates a tree-like structure where each internal node tests a feature and each leaf provides a prediction.