The Challenges and Development of Artificial Intelligence in the Nursing Ethics Curriculum: Ethical Reconstruction in the Technological Revolution

The deep integration of artificial intelligence (AI) into nursing is reshaping nursing practices and ethical decision-making frameworks. This paper systematically examines the core challenges posed by AI to the Nursing Ethics curriculum, including ambiguities in accountability, privacy and security risks, algorithmic bias amplification, alienation in human-machine relationships, and educational lag. Concurrently, it proposes developmental pathways through the expansion of ethical frameworks, innovation in teaching tools, cultivation of practical competencies, and international collaboration. By analyzing global governance practices and Classic documentation, the study advocates for dynamic curriculum updates and interdisciplinary integration to construct a nursing ethics education system suited to the era of "human-machine collaborative care."

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-04-07
DOI
https://doi.org/10.5281/zenodo.15165383
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00
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article

The Challenges and Development of Artificial Intelligence in the Nursing Ethics Curriculum: Ethical Reconstruction in the Technological Revolution

Zenodo (CERN European Organization for Nuclear Research)
Artificial Intelligence in Healthcare and Education
article

The Challenges and Development of Artificial Intelligence in the Nursing Ethics Curriculum: Ethical Reconstruction in the Technological Revolution

article en

Abstract

The deep integration of artificial intelligence (AI) into nursing is reshaping nursing practices and ethical decision-making frameworks. This paper systematically examines the core challenges posed by AI to the Nursing Ethics curriculum, including ambiguities in accountability, privacy and security risks, algorithmic bias amplification, alienation in human-machine relationships, and educational lag. Concurrently, it proposes developmental pathways through the expansion of ethical frameworks, innovation in teaching tools, cultivation of practical competencies, and international collaboration. By analyzing global governance practices and Classic documentation, the study advocates for dynamic curriculum updates and interdisciplinary integration to construct a nursing ethics education system suited to the era of "human-machine collaborative care."

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 57%
Artificial Intelligence in Healthcare and Education
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