Assessing Clinicians' Legal Concerns and the Need for a Regulatory Framework for AI in Healthcare: A Mixed-Methods...

Area of Science:

• Healthcare Law
• Medical Ethics
• Artificial Intelligence in Medicine

Background:

• Rapid AI integration in healthcare creates legal and ethical challenges.
• Limited legal awareness in Saudi Arabia may impede safe AI tool implementation.
• Existing healthcare systems face evolving regulatory landscapes due to AI.

Purpose of the Study:

• To assess legal awareness among Saudi clinicians regarding AI in healthcare.
• To identify legal barriers and regulatory needs for AI adoption in Saudi healthcare.
• To evaluate clinician confidence in AI's compliance with data protection laws.

Main Methods:

• Sequential explanatory mixed-methods design.
• Phase One: Electronic survey of 357 clinicians on AI legal awareness, liability, data privacy, and trust.
• Phase Two: Qualitative expert panel to interpret findings and define regulatory needs.

Main Results:

• Only 7% of clinicians reported high familiarity with AI legal implications; 89% lacked formal legal training.
• Low clinician confidence (1.40/3) in AI compliance with data laws.
• Key legal barriers include lack of training, unclear liability, and regulatory gaps (e.g., PDPL alignment).

Conclusions:

• Significant legal readiness gap exists among Saudi clinicians, impacting patient safety, liability, and trust in AI.
• Unclear regulations are a major barrier to safe AI adoption, despite clinician openness.
• Experts recommend national legal standards, mandatory training, and informed consent protocols for ethical AI use.