Responsible AI in practice: bias, privacy and governance checklists

Before you build

1. Say what decision the system supports and who is affected by it.
2. Decide whether AI is needed at all.
3. Name who is accountable for the system.

Data and privacy

• Know what data is used, where it came from and whether you may use it for this purpose.
• Minimise personal data and keep it out of prompts and logs where you can.
• Check where a provider stores and processes data, and under what terms.

Bias and fairness

• Test results across the groups the system affects, not only on average.
• Look at how errors are distributed, not just how many there are.
• Give people a way to challenge an outcome.

In operation

• Keep a human in the loop for consequential decisions.
• Monitor for drift and for new misuse.
• Keep records so decisions can be explained and audited.
• Review the system on a schedule, and when the law or the use changes.

IICTP is a new independent credential and is not ISO/IEC 17024 accredited.