Twinkle 07 / Brainstorming scenario
GP care: AI as a duty to check, not just type
A proposed standard of care would expect clinicians to use suitable, validated AI assistance when it improves ethical overcompliance: more thorough checks of consent, prescribing, interactions, follow-up and unusual problems. Unjustified failure to use an available beneficial tool would be reviewable as a possible lapse in care. AI could also return paperwork time to patients.
Ethical overcompliance means using useful checks to do more than the bare minimum. The idea includes prescribing checks, unusual-case investigation, consent and follow-up, with AI saving time and clinicians retaining judgement.
Explore the connected work
- UNGA81: Joyful Responsible Abundance - The connected proposal for capability, ownership, livelihoods, care and worthwhile futures, with a reference library. Source repository
- Ready S.E.T. Co-op intelligence node - A rack-scale community computing proposal, local learning, cultural permissions and links to the submissions. Source repository
- 500 Queens: care and participation - Voluntary contribution and care alongside women’s leadership, learning and paid enterprise pathways. Source repository
How it could work
- A clinician-controlled assistant could check medicines, allergies, interactions, missing information and follow-up duties, and prepare prescriptions for the clinician to verify and authorise.
- For irregular or unresolved problems, AI could help search evidence and alternative explanations, making uncertainty and source quality visible for professional review.
- The system could draft records and correspondence, flag missed obligations and record reasons for overriding a useful check. Care funding would reward time, continuity and prevention.
Everyday example
When symptoms do not fit the usual pattern, a GP could use a source-linked second check, review the medication history and follow up an unresolved issue rather than repeat a rushed default answer.
Who could act and how it could be funded
Clinical bodies, practices, public health services and regulators could develop the standard, approved tools, training and audit pathway. Funding would cover clinician time, integration, security and independent evaluation.
Fair-go safeguards
The negligence proposal concerns a future professional standard, not a claim about existing law. Clinicians remain accountable; AI does not prescribe autonomously. Consent, privacy, evidence quality and a non-AI care route are part of the design.
What would show progress
Missed issues detected; prescribing checks completed; useful follow-up; clinician time returned; patient outcomes; audit findings.
