Literature DB >> 32078175

Where medical education meets artificial intelligence: 'Does technology care?'

Anneke G van der Niet1,2, Alan Bleakley3.   

Abstract

'COLD' TECHNOLOGIES AND 'WARM' HANDS-ON MEDICINE NEED TO WALK HAND-IN-HAND: Technologies, such as deep learning artificial intelligence (AI), promise benign solutions to thorny, complex problems; but this view is misguided. Though AI has revolutionised aspects of technical medicine, it has brought in its wake practical, conceptual, pedagogical and ethical conundrums. For example, widespread adoption of technologies threatens to shift emphasis from 'hands-on' embodied clinical work to disembodied 'technology enhanced' fuzzy scenarios muddying ethical responsibilities. Where AI can offer a powerful sharpening of diagnostic accuracy and treatment options, 'cold' technologies and 'warm' hands-on medicine need to walk hand-in-hand. This presents a pedagogical challenge grounded in historical precedent: in the wake of Vesalian anatomy introducing the dominant metaphor of 'body as machine,' a medicine of qualities was devalued through the rise of instrumental scientific medicine. The AI age in medicine promises to redouble the machine metaphor, reducing complex patient experiences to linear problem-solving interventions promising 'solutionism.' As an instrumental intervention, AI can objectify patients, frustrating the benefits of dialogue, as patients' complex and often unpredictable fleshly experiences of illness are recalculated in solution-focused computational terms. SUSPICIONS ABOUT SOLUTIONS: The rate of change in numbers and sophistication of new technologies is daunting; they include surgical robotics, implants, computer programming and genetic interventions such as clustered regularly interspaced short palindromic repeats (CRISPR). Contributing to the focus of this issue on 'solutionism,' we explore how AI is often promoted as an all-encompassing answer to complex problems, including the pedagogical, where learning 'hands-on' bedside medicine has proven benefits beyond the technical. Where AI and embodied medicine have differing epistemological, ontological and axiological roots, we must not imagine that they will readily walk hand-in-hand down the aisle towards a happy marriage. Their union will be fractious, requiring lifelong guidance provided by a perceptive medical education suspicious of 'smart' solutions to complex problems.
© 2020 John Wiley & Sons Ltd and The Association for the Study of Medical Education.

Entities:  

Mesh:

Year:  2020        PMID: 32078175     DOI: 10.1111/medu.14131

Source DB:  PubMed          Journal:  Med Educ        ISSN: 0308-0110            Impact factor:   6.251


  5 in total

1.  Medical artificial intelligence readiness scale for medical students (MAIRS-MS) - development, validity and reliability study.

Authors:  Ozan Karaca; S Ayhan Çalışkan; Kadir Demir
Journal:  BMC Med Educ       Date:  2021-02-18       Impact factor: 2.463

2.  Who Gets Cured? COVID-19 and Developing a Critical Medical Sociology and Anthropology of Cure.

Authors:  Maria Berghs
Journal:  Front Sociol       Date:  2021-01-12

3.  Reflections on epistemological aspects of artificial intelligence during the COVID-19 pandemic.

Authors:  Angela A R de Sá; Jairo D Carvalho; Eduardo L M Naves
Journal:  AI Soc       Date:  2021-11-27

4.  Artificial intelligence in medical education curriculum: An e-Delphi study for competencies.

Authors:  S Ayhan Çalışkan; Kadir Demir; Ozan Karaca
Journal:  PLoS One       Date:  2022-07-21       Impact factor: 3.752

5.  Are We Ready to Integrate Artificial Intelligence Literacy into Medical School Curriculum: Students and Faculty Survey.

Authors:  Elena A Wood; Brittany L Ange; D Douglas Miller
Journal:  J Med Educ Curric Dev       Date:  2021-06-23
  5 in total

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