Project · Curriculum integration

AI Competencies in the Curriculum Ongoing

Weaving AI competencies into the curriculum students already have — the pre-clerkship Foundations of Practice course and the Intersessions weeks that punctuate the clinical years — rather than bolting on a standalone AI course.

What's running now

• Foundations of Practice (pre-clerkship) — the AI Clinical Reasoning Tutor is embedded in the course itself, so students' first sustained AI experience is a supervised, faculty-calibrated educational tool, not an unsanctioned shortcut.
• Intersessions AI workshops (clinical years) — dedicated ~2-hour AI workshops in the intersession weeks, covering practical and critical AI use in clinical work.
• Class-wide sessions — dedicated lectures for first- and second-year students on AI in medical education: why it matters and how to use it wisely.

Signature teaching frameworks

Two framings we teach recur across sessions:

• "Run the Gate" before any clinical AI use: is this use Appropriate · Responsible · Safe · Effective · Legal?
• Discrepancy detection and escalation — the explicit skill of noticing "the AI suggested X, but my clinical reasoning says Y," and knowing what to do next. We treat this as a core clinical skill of the AI era, not an afterthought.

Mapped, not assumed

Every session is mapped against our unified AI competency framework with an honest status vocabulary — aligned, thin, touched-lightly, deliberately deferred, priority gap, or whitespace — so that "we cover AI" is a claim backed by a topic-level map rather than a syllabus bullet. A defined subset of framework topics is designated as the UME priority set (foundational and applied tiers — advanced tiers are deliberately deferred beyond UME), and the mapping has been independently re-verified by a second AI system in a read-only pass, with disagreements adjudicated by the PI.

Why it matters

The AAMC's emerging AI competencies will only reach students through actual curricular hours. Integration into existing required courses — with a mapped, auditable link between sessions and competencies — is our answer to how a school makes an "AI-ready physician workforce" a measurable commitment instead of a slogan.