Is the system trained on large datasets?

e.g., training datasets for machine learning

Is specific experiential knowledge incorporated into the development?

e.g., encoding of expert rules or domain-specific algorithms

Are data from ongoing operations used for further development?

e.g., feedback loops or A/B testing

Does the system rely on statistical analyses of historical data?

e.g., trend detection or pattern analysis

Does the system perform complex optimizations during runtime?

e.g., adaptive algorithms or reinforcement learning

Does the system automatically adapt to new situations?

e.g., autonomous adjustment of parameters

Does the system use goal-seeking or optimization algorithms?

e.g., search for optimal solutions to complex problems

Does the processing go beyond simple if-then rules?

e.g., complex decision trees or neural networks

Is there significant discretion in the system's results?

e.g., different but equally valid solutions possible

Does the system generate creative or unpredictable outputs?

e.g., text generation or image creation

Are the results based on probabilities or estimates?

e.g., predictions or recommendations

Can the results be interpreted differently by people?

e.g., subjective assessments or evaluations