Using AI Tools Responsibly: Practical Best Practices
Generative AI tools that write text, summarise documents, produce images or suggest code have become everyday software. Used well, they save time on drafts and routine tasks. Used carelessly, they can spread errors, leak private information or produce work that misleads. These best practices apply whichever tool you use.
Understand what the tool is doing
Large language models generate text by predicting likely sequences of words based on patterns learned from training data. They do not look facts up in the way a search engine or database does unless the tool is specifically connected to a search or document source. This is why they can produce confident, fluent answers that are wrong, sometimes called "hallucinations". Treat output as a first draft from a fast but unreliable assistant.
1. Verify facts, figures and references
- Check names, dates, numbers and quotations against a primary source before using them.
- Be especially careful with citations: AI tools have been known to invent articles, legal cases and links that look real but do not exist.
- For anything with legal, medical or financial consequences, have a qualified person review the result.
2. Protect private and confidential information
Text you paste into an online AI service is sent to the provider and, depending on the product and settings, may be stored or used to improve the service. Before sharing anything:
- Read the tool's privacy and data-use settings, and your organisation's policy if you have one.
- Avoid pasting personal data about other people, passwords, customer records or confidential business documents into tools that are not approved for that purpose.
- Where possible, remove or anonymise identifying details first.
3. Keep a human in the loop
Decisions that affect people, such as hiring, lending, grading or access to services, should not be handed over to an AI tool without meaningful human review. Someone should understand the output well enough to explain and, if necessary, override it.
4. Watch for bias
Models learn from large collections of existing text and images, which contain the biases of the world that produced them. Output can reflect stereotypes or leave groups out. Review content that describes people, and test prompts with different examples to see whether results change unfairly.
5. Be open about AI assistance
Many workplaces, schools and publishers now have rules on disclosing AI use. Even where there are none, being transparent builds trust. A short note that a draft or image was produced with AI assistance and reviewed by a person is usually enough.
6. Respect intellectual property
The legal position on AI-generated content and on training data is still developing and differs between countries. Avoid asking tools to reproduce copyrighted material, check licensing terms for commercial use of generated images, and do not present generated work as entirely your own where that matters.
7. Write clear prompts
Results improve when instructions are specific. Useful elements include the goal, the audience, the format you want, any constraints (length, tone, what to avoid) and relevant background material. Asking the tool to list its assumptions or to flag uncertain points can make review easier.
8. Know when not to use AI
Some tasks are better done without it: highly sensitive communications, situations where accuracy is critical and checking would take longer than doing the work, or anything that requires accountability a tool cannot provide.
A simple checklist
- Is this an appropriate task for an AI tool?
- Have I removed private or confidential data?
- Have I checked every fact, figure and reference?
- Would a reader be misled about how this was made?
- Is a person accountable for the final result?
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