Skip to content

Human, hybrid and automated education in paramedic practice

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.

View source

Similar papers

Review Open access Aug 2026

AI-Empowered Nuclear Medicine Education, Part 1: Theoretical and Ethical Foundation

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 · 1 citation
Open access Jul 2026

Continuing Medical Education as a Workforce Learning System for Artificial Intelligence in Clinical Practice

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 · 1 citation
Review Open access Aug 2026

AI-Empowered Nuclear Medicine Education, Part 3: Practical AI Applications for Learners

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 · 0 citations
Review Open access Aug 2026

Development of AI competencies within the medical curriculum

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. · 0 citations

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.