Knowledge Elicitation

The systematic process of extracting knowledge from individuals or groups and transforming it into structured, machine-usable representations.

The process typically involves two phases: collection (gathering knowledge through interviews, observation, or other techniques) and encoding (transforming that knowledge into formal structures like ontologies, rules, or knowledge graphs).

Historically developed for expert systems in early AI, knowledge elicitation now spans applications from training data curation to organizational knowledge capture to ontology engineering.

The core challenge remains the tacit knowledge problem: experts often can’t articulate what they know. This makes elicitation inherently incomplete, you capture what can be expressed, not what informs practice.

Related: 06-atom—tacit-knowledge, 06-molecule—seci-framework