AI is reshaping how doctors train

AI is reshaping how doctors train

UC College of Medicine's approach featured

For generations, physicians have trained through a cognitive apprenticeship model, practicing under supervision, receiving feedback and learning how experienced clinicians solve complex problems.

By repeatedly performing clinical tasks, trainees gradually develop the expertise, judgment and self-awareness needed to practice medicine independently.

But as Forbes recently reported, artificial intelligence is forcing the medical community to quickly reconsider how it trains physicians, even as many of the technology's educational effects remain unknown.

Laurah Turner, PhD, the University of Cincinnati College of Medicine's associate dean of artificial intelligence and educational informatics, argues that medical educators are rushing to apply their familiar toolkit - policies, competencies, and curricula - to a phenomenon they do not yet fully understand.

Some argue that these responses are necessary and that trainees should develop AI competence, including the ability to critically appraise AI outputs.

Training large groups of medical students, residents and fellows has traditionally required educators to teach to the average learner and to assess what is easiest to measure: knowledge recall.

Now AI is creating opportunities to evaluate trainees' capabilities and personalize their training in ways that were previously impossible.

For Turner and UC, this means partnering with learners to co-create new training approaches and embracing newer models, such as design-based research and implementation science.

Read the full Forbes article.

Featured image at top: iStock/Vertigo3d.

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