Practical guides
Practical methods for using AI
Twelve methods with examples, acceptance checks and independent references. Choose a goal and work through a result you can verify.
Practical methods for using AI
Ask a useful question to AI
A useful request identifies a result, the context that changes it and a way to check it. More instructions do not automatically mean a better answer; add only what helps the task.
Method →Verify an AI answer
Treat an AI answer as a collection of claims to examine. Confidence in the wording is not evidence. The amount of checking should depend on the consequences of an error, not on how polished the answer looks.
Method →Cite sources without overstating them
A citation should let another reader locate the evidence and understand what it supports. A URL or DOI identifies a resource; it does not automatically establish the truth of your sentence.
Method →Learn with AI while keeping the effort
AI can structure practice and explain a difficulty, but copying a solution does not demonstrate learning. Use it to create opportunities to recall, attempt and correct, then test yourself without the model.
Method →Summarise a document without losing its meaning
A useful summary preserves the author’s claims, scope and uncertainty. It should not silently turn a possibility into a certainty or combine statements that concern different populations or dates.
Method →Translate and localise a text carefully
Translation transfers meaning; localisation also adapts the text for its audience. Neither makes a foreign rule, qualification or product available locally. Keep facts and jurisdiction separate from wording.
Method →Compare options with explicit criteria
A useful comparison makes the decision understandable. Start with requirements, then compare documented values. An attractive overall score can hide a missing essential condition or an unsupported assumption.
Method →Plan a project around verifiable deliverables
A schedule helps when each step produces something that can be reviewed. A list of impressive tasks is not enough; make dependencies, owners and acceptance conditions explicit before assigning dates.
Method →Prepare and review an AI image
Start with the image’s purpose on the page, not only an attractive style. An illustration should help the reader understand something and must not pretend to document a real person, product or event.
Method →Build a presentation from verified material
A useful presentation follows the audience’s decision or learning need. First decide what they should remember or do, then organise evidence around that goal instead of filling a predetermined number of slides.
Method →Prepare an AI task without exposing data
Decide which information is necessary before sharing it. Removing a name does not always make a record anonymous; combinations of details may still identify a person or disclose a confidential situation.
Method →Build spreadsheet formulas you can verify
Begin with the data model and expected result. A formula suggested by AI is a proposal to run and inspect, not proof that a spreadsheet is correct. Test on a copy before applying it to important records.
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