In simple words: Use predictions to support a clearly defined decision and check the consequences.
Start with the decision
Ask what decision the model supports, what data is available, and what a wrong answer costs. Deep learning is useful for complex text, images, speech, and video, but a simple rule or conventional model may be enough for a simpler problem.
People are more than scores
Past data can reflect unfair treatment. A model trained on it can repeat that bias. Check quality and fairness, protect personal data, and keep human review for important career, health, lending, or relationship decisions. A predicted probability is never a guarantee about a person.
See the flow
For customer support, a model can sort incoming messages by topic for staff review. It should not decide that a person will “succeed” or “fail” in life.
Remember: Use predictions to support a clearly defined decision and check the consequences.