Responsible AI in Healthcare: A Practical Checklist
A practical checklist for evaluating AI tools in healthcare: purpose, evidence, human oversight, privacy, bias, workflow fit, accountability and monitoring.
Convergence
Ethical principles for AI and digital systems in care
Principles are only useful if a project can be checked against them before it launches, and again afterwards.
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Quick answer
Quick answer
What ethical rules should a health technology project follow?
Collect only the data the purpose requires, take informed consent for anything beyond care, limit who can see what, show patients what is held about them, test for unequal performance across groups, keep a named person accountable for every automated action, and monitor after launch rather than trusting the launch tests.
Data with dignity
Health data can reveal patterns in follow up, outcomes and service quality that help a practice improve. It is also among the most sensitive data a person has. Collection should be purposeful, consent informed, access limited and analysis designed so that insight does not come at the cost of privacy.
- Purpose stated before collection, not after
- Consent that a worried person can actually understand
- Access limited by role, and logged
- Retention with an end date
- Aggregation and anonymisation wherever individual records are not needed
Fairness and accountability
A model performs differently on groups that were under represented in its data. In healthcare that is not a statistical footnote, it is a safety issue, and it needs testing by group rather than a single overall score.
Accountability does not transfer to software. Every automated action needs a named owner, a log that shows what happened and why, and a way to switch it off. If nobody can answer who is responsible, the system is not ready for patients.
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Questions
Questions about ethical principles
Who is responsible when an AI tool contributes to a mistake?
The organisation that deployed it and the person who approved its use in that workflow. Vendors carry product responsibility, but clinical accountability stays with the practice.
How long should health data be kept?
Only as long as the stated purpose and the applicable regulation require, with the retention period written down and applied rather than left to inertia.
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