Artificial Intelligence should support engineering decisions rather than generate automatic instructions without explanation.
Recommendations produced by the platform should always be understandable within the engineering context from which they originated.
Whenever practical, recommendations should include the principal factors that contributed to the proposed conclusion.
For example, an irrigation recommendation may reference:
- current soil moisture
- recent evaporation trends
- predicted rainfall
- historical behaviour of the installation
- observed root-zone conditions
Providing transparent reasoning increases confidence in the platform while facilitating engineering validation.