Knowledge Engine, Wisdom System: Aligning Generative AI With the Relational and Epistemic Foundations of Primary Care
Abstract
Many patients now turn to generative AI for health advice before seeing a doctor. However, there is little evidence about how well it works in primary care. Research focused on general practice is limited, and real-world harms are often missed because there is no standard way to record AI-related incidents. The gap between what AI provides and what general practice needs is not just technical; it is structural and requires active oversight. AI can recognise patterns, summarise documents, and organise data, but it does not have the judgement, long-term patient knowledge, or moral reasoning that define good general practice. Evidence shows that careful use of AI can help, but careless use can cause real harm. To safely use AI, we must protect what makes primary care effective: knowing patients over time, reasoning through diagnoses across visits, and building healing relationships that combine clinical skill with whole-person care. No training set or workforce change can replace this. Evaluation should look beyond accuracy, considering continuity of care, the risk of losing clinical skills, patient experience, and fairness. General practitioners (GPs) must take an active role in guiding how AI is used, rather than simply adding it to current practice.
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