Public articles linked to the same research event.
Academic medicine : journal of the Association of American Medical Colleges This paper identifies and names the phenomenon of "inference impersonation"—ambient AI scribes generate rather than transcribe clinical reasoning in the Assessment and Plan, producing text indistinguishable from transcription in the final note, so trainees may edit AI drafts instead of reasoning independently and risk never developing the judgment training exists to build; it proposes vendor-side learner-specific configurations and section-level transparency plus training-program responses such as reasoning-before-note, competency gating, and oral assessment.
This paper identifies and names the phenomenon of "inference impersonation"—ambient AI scribes generate rather than transcribe clinical reasoning in the Assessment and Plan, producing text indistinguishable from transcription in the final note, so trainees may edit AI drafts instead of reasoning independently and risk never developing the judgment training exists to build; it proposes vendor-side learner-specific configurations and section-level transparency plus training-program responses such as reasoning-before-note, competency gating, and oral assessment.
This paper identifies and names the phenomenon of "inference impersonation"—ambient AI scribes generate rather than transcribe clinical reasoning in the Assessment and Plan, producing text indistinguishable from transcription in the final note, so trainees may edit AI drafts instead of reasoning independently and risk never developing the judgment training exists to build; it proposes vendor-side learner-specific configurations and section-level transparency plus training-program responses such as reasoning-before-note, competency gating, and oral assessment.
This paper identifies and names the phenomenon of "inference impersonation"—ambient AI scribes generate rather than transcribe clinical reasoning in the Assessment and Plan, producing text indistinguishable from transcription in the final note, so trainees may edit AI drafts instead of reasoning independently and risk never developing the judgment training exists to build; it proposes vendor-side learner-specific configurations and section-level transparency plus training-program responses such as reasoning-before-note, competency gating, and oral assessment.