Aug 2026· Journal of Paramedic Practice· 0 citations· 9 references
TL;DR
Which elements of paramedic training should remain inherently human, which are best delivered through hybrid human–AI models, and which tasks can be ethically and safely automated with oversight are examined.
Abstract
Paramedic education is entering a pivotal era as artificial intelligence (AI) rapidly evolves from decision-support tools to sophisticated learning and simulation technologies. This article examines which elements of paramedic training should remain inherently human, which are best delivered through hybrid human–AI models, and which tasks can be ethically and safely automated with oversight. Core relational competencies such as delivering bad news, communicating prognostic uncertainty and demonstrating empathy are identified as irreducibly human owing to their emotional, ethical and interpersonal complexity. Hybrid approaches show promise in simulation, assessment and clinical reasoning, where AI can enhance exposure, personalise feedback and support structured decision-making, while retaining expert supervision. Certain pattern-recognition or administrative tasks, including electrocardiogram (ECG) interpretation and teaching-material generation, can be responsibly automated within governance frameworks. The authors propose a curriculum-design framework and implementation strategy to guide educators in developing AI-literate, compassionate practitioners while ensuring transparency, safety and ongoing evaluation.
This curriculum offers a generalizable, no-cost model for closing the AI evaluation skills gap in healthcare education, combining interactive correction with a mandatory, learner-defined capstone project.
Hiba Hamdar· Journal of Medical Education...· 0 citations
Effective AI techniques are described that can be applied to meet the demands of increased NM volumes and expanded professional opportunities, and require explicit safeguards, including AI guardrail incorporation, privacy protection, expert review, AI output transparency, and healthy skepticism.
Keith M. Jacobs, J. Peacock· Journal of Nuclear Medicine...· 1 citation
It is argued that AI-focused CME should be designed as a longitudinal organizational learning system rather than a discrete instructional event, and implications are offered for technology integration, faculty development, and organizational learning in clinical education.
T. Murphy, Rob E. Carpenter· International Journal on Int...· 1 citation
Expanding clinical volumes, evolving radiopharmaceuticals, and new imaging technologies shape the training environment for nuclear medicine (NM) learners. Additionally, artificial intelligence (AI) tools are increasingly available. These tools can draft study guides, generate questions, simulate patient interactions, c...
Keith M. Jacobs, J. Peacock· Journal of Nuclear Medicine...· 0 citations
Artificial intelligence should ultimately enhance rather than replace nurses’ clinical judgement, ethical responsibility, communication, and compassionate care, and professional practice.
Nan Zhang· Advances in Vocational and T...· 0 citations
Evidence indicates a transition from isolated AI educational initiatives toward competency-based and longitudinal curriculum integration and effective AI education extends beyond technical literacy and increasingly incorporates ethical, clinical, and professional competencies necessary for responsible AI adoption in he...
M. Morales-Cevallos, Diego Fabián Vique López, Catherine Hortensia Martínez Avalos et al.· Frontiers in Medicine· 0 citations
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