AI glossary · AI basics
Rule-based AI
Rule-based AI makes decisions by following “if this, then that” rules written by people, rather than learning patterns from data.
Also called symbolic AI, expert system, traditional AI
In more detail
Before machine learning took over, much of AI worked this way. Expert systems in the 1980s, for example, encoded the knowledge of doctors or engineers as long lists of rules.
Rule-based systems are predictable and easy to explain, but they break when they meet situations nobody wrote a rule for. Many products still combine rules with learned models.
Example
A simple customer-service bot that replies “Our opening hours are 9 to 5” whenever a message contains the word “hours”.
Related terms
Machine learning (ML)Machine learning (ML) is a way of building AI where computers learn patterns from examples, instead of being given step-by-step rules.AlgorithmAn algorithm is a step-by-step set of instructions a computer follows to solve a problem or complete a task.ChatbotA chatbot is a program you talk to in text or voice that replies like a person would. Modern AI chatbots like ChatGPT are powered by large language models.
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