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Machine Learning

Generative Artificial Intelligence in Medical Education: Enhancing Critical Thinking or Undermining Cognitive Autonomy?

Juan S Izquierdo-Condoy, Marlon Arias-Intriago, Andrea Tello-De-la-Torre, Felix Busch, Esteban Ortiz-Prado
November 3, 2025Journal of Medical Internet Research31 citations
DOI

31

Citations

1

Influential Citations

Journal of Medical Internet Research

Venue

2025

Year

Abstract

Generative artificial intelligence (GenAI) enables the production of coherent and contextually relevant text by processing large-scale linguistic datasets. Tools such as ChatGPT, Gemini, Claude, and LLaMA are increasingly integrated into medical education, assisting students with a range of tasks, including clinical reasoning, literature review, scientific writing, and formative assessment. Although these tools offer significant advantages in terms of productivity, personalization, and cognitive support, their impact on critical thinking—a cornerstone of medical education—remains uncertain. The aim of this viewpoint paper is to critically assess the influence of GenAI on critical thinking within medical training, examining both its potential to enhance cognitive skills and the risks it poses to cognitive autonomy. Users have reported increased efficiency and improved linguistic output; however, concerns have also been raised regarding the risk of cognitive overreliance. Current evidence presents a mixed picture, indicating both improvements in learner engagement and potential drawbacks such as passivity or susceptibility to misinformation. Without curricular integration that prioritizes ethical use, prompt engineering, and critical evaluation, GenAI may compromise the cognitive autonomy of medical students. Conversely, when thoughtfully embedded into pedagogical frameworks, these tools can act as cognitive enhancers—supporting, rather than replacing, clinical reasoning. Medical education must adapt to ensure that future physicians engage with GenAI in a critical, ethical, and context-aware manner, especially in complex decision-making scenarios. This transformation demands not only technological fluency but also reflective practice and sustained oversight by faculty and academic institutions.

Analysis

Why This Paper Matters

This viewpoint paper addresses a critical tension in modern medical education: the integration of generative AI tools that can both enhance and undermine the cognitive skills essential for clinical practice. As tools like ChatGPT, Gemini, and Claude become ubiquitous, educators face the challenge of leveraging their benefits—such as personalized learning and efficient literature review—without fostering dependency that erodes critical thinking. The paper is timely because medical schools worldwide are rapidly adopting AI without clear pedagogical frameworks, risking a generation of physicians who may rely on AI outputs rather than developing independent clinical reasoning.

The significance lies in its balanced perspective: it does not dismiss GenAI as harmful nor blindly endorse it, but instead calls for thoughtful curricular integration. This resonates with ongoing debates in AI ethics and education, making it relevant beyond medicine to any field where AI-assisted decision-making is becoming the norm.

Technical Contributions

  • Framework for assessing cognitive impact: The paper categorizes GenAI's effects into enhancement (e.g., improved efficiency, linguistic output) and risks (e.g., cognitive overreliance, passivity).
  • Identification of key pedagogical requirements: Emphasizes prompt engineering, critical evaluation, and ethical use as necessary components for safe integration.
  • Distinction between cognitive support and replacement: Argues that GenAI should act as a cognitive enhancer, not a substitute for clinical reasoning.
  • Call for reflective practice: Advocates for sustained faculty oversight and institutional accountability.

Results

As a viewpoint paper, no experimental results or quantitative metrics are presented. The evidence cited is qualitative: user reports of increased efficiency and improved writing, alongside concerns about passivity and misinformation susceptibility. The paper does not provide benchmarks, comparisons, or statistical analyses, limiting its empirical weight.

Significance

This paper contributes to the growing discourse on AI in education by focusing specifically on cognitive autonomy—a concept often overlooked in technical discussions. It challenges the assumption that AI tools are inherently beneficial and highlights the need for deliberate pedagogical design. For AI practitioners, it underscores that deploying generative models in sensitive domains like medicine requires not just technical fluency but also ethical frameworks and continuous human oversight. The call for curricular adaptation may influence how AI literacy is taught in professional schools, potentially shaping future standards for AI-assisted learning.

generative-aimedical-educationcritical-thinkingcognitive-autonomychatgptclinical-reasoningpedagogy
PromptingReasoning

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