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Related Concept Videos

Accountability and Responsibility of a Nurse II01:09

Accountability and Responsibility of a Nurse II

Professional accountability in nursing is a multifaceted concept that encompasses professional ethics, legal standards, and employment expectations. This framework ensures that nurses maintain and elevate the quality of care while upholding the values of their profession. It compels them to treat patients, families, and colleagues with respect, compassion, and integrity.
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Autonomy
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Related Experiment Videos

Authorship, moral responsibility, and generative AI in nursing.

Raymond Zakhari1

  • 1Hunter-Bellevue School of Nursing, City University of New York (CUNY), New York, NY, USA.

Nursing Ethics
|July 9, 2026
PubMed
Summary

Generative artificial intelligence (AI) in academic writing is ethically permissible when human authorship, responsibility, and verification are maintained and transparent. Ethical issues arise from abdicating moral responsibility, not from AI use itself.

Keywords:
Academic integrityAuthorshipGenerative artificial intelligenceMoral responsibilityNursing scholarship

Related Experiment Videos

Area of Science:

  • Nursing Scholarship
  • Academic Integrity
  • Artificial Intelligence Ethics

Background:

  • Generative artificial intelligence (AI) integration in academic writing raises ethical concerns about authorship, responsibility, and professional integrity.
  • Current discourse often frames AI use as either deceptive or efficient, overlooking the core moral structure of its ethical implications.
  • A fundamental question remains: under which conditions does AI-assisted writing uphold, rather than erode, moral responsibility and professional trust?

Purpose of the Study:

  • To advance a normative analysis of generative AI in academic writing, grounded in principles of moral agency, responsibility, and authorship.
  • To conceptually distinguish the roles of author, writer, editor, and assistant, and situate generative AI within this framework.
  • To establish ethical permissibility criteria for AI-assisted writing in scholarly contexts.

Main Methods:

  • Normative analysis based on first principles of moral agency, responsibility, and authorship.
  • Conceptual distinction between author, writer, editor, and assistant roles, drawing parallels with existing scholarly practices.
  • Analysis of generative AI as a delegated instrument, not a moral agent or author.

Main Results:

  • Authorship is defined by accountability for claims, interpretations, and consequences, not solely by textual production.
  • Generative AI is ethically permissible if and only if authorship, responsibility, and verification remain fully human and transparent.
  • Ethical failures stem from the displacement, obscuring, or abdication of moral responsibility, not AI use per se.

Conclusions:

  • Disciplined role clarity, verification, and transparency offer a robust ethical framework for AI-assisted writing in nursing scholarship.
  • Addressing objections regarding authorship dilution, AI-human analogies, verification feasibility, and international norms is crucial.
  • Maintaining human oversight and accountability is paramount for preserving professional trust and integrity in the face of AI integration.