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Where medical education meets artificial intelligence: ‘Does technology care?’

隐喻 人工智能 心理干预 复杂度 干预(咨询) 计算机科学 技术哲学 新兴技术 工程伦理学 具身认知 精密医学 心理学 科学哲学 社会学 医学 认识论 社会科学 工程类 病理 语言学 哲学 精神科
作者
Anneke G. van der Niet,Alan Bleakley
出处
期刊:Medical Education [Wiley]
卷期号:55 (1): 30-36 被引量:103
标识
DOI:10.1111/medu.14131
摘要

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.
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