Responsible AI is not a separate project. It is a set of everyday habits that keep systems useful, fair and understandable once they are part of the working day.
Be clear about purpose and limits
Document what each AI-assisted process is for, what information it uses and where it should not be relied on. Make this easy for staff and customers to find.
Clear boundaries reduce misuse and build confidence.
Keep people accountable
Decide who is responsible for outcomes, who can override a result and how concerns are raised. Technology can support a decision, but a person remains accountable for it.
Make escalation simple and expected.
Check quality on an ongoing basis
Performance changes as data and conditions change. Review samples of results regularly, look for patterns of error and record what you learn.
Small, routine checks catch problems long before they become incidents.
Handle information with care
Limit the data used to what is needed, protect it properly and be open about how it is handled. Respecting privacy is part of delivering a trustworthy service.
Good practice here also makes the system easier to explain and maintain.
- State the purpose and limits of each use.
- Keep a named person accountable.
- Review results routinely, not only at launch.
- Use only the information you need.
