Navigating Professional Accountability in AI-Assisted Nursing Practice: Ethical and Legal Imperatives for the Digital...

Area of Science:

• Healthcare Ethics
• Nursing Informatics
• Artificial Intelligence in Medicine

Background:

• The increasing use of AI in clinical decision-making introduces complexities in professional accountability, especially when patient care leads to adverse outcomes.
• Nurses are primary users of AI clinical decision support systems (AI-CDSS), navigating a landscape where professional responsibility clashes with algorithmic opacity and shared decision-making.
• Evolving legal and ethical frameworks further complicate accountability in AI-assisted healthcare.

Purpose of the Study:

• To examine the specific accountability challenges faced by nurses operating in AI-enabled healthcare environments.
• To explore the ethical dilemmas nurses encounter when balancing AI-CDSS recommendations with their independent clinical judgment.
• To highlight the urgent need for structured solutions to ensure accountability in AI-integrated healthcare.

Main Methods:

• This commentary analyzes the intersection of AI, clinical judgment, and professional accountability.
• It reviews ethical considerations and legal implications for nurses using AI-CDSS.
• The study synthesizes current challenges and proposes areas for future development in accountability frameworks.

Main Results:

• Nurses face significant ambiguity in accountability due to the opaque nature of AI algorithms and shared decision-making models.
• Ethical tensions arise from the conflict between adhering to AI recommendations and exercising professional nursing judgment.
• Existing accountability structures are insufficient for AI-integrated healthcare settings.

Conclusions:

• Clear frameworks for attributing responsibility in AI-assisted care are essential.
• Robust institutional policies and strengthened professional guidance are required to support nurses and safeguard patients.
• Proactive measures are necessary to manage accountability challenges as AI becomes more prevalent in healthcare delivery.