Artificial intelligence in healthcare research: Research ethics perspective

Area of Science:

• Healthcare Ethics
• Artificial Intelligence Research
• Biotechnology Governance

Background:

• Current policies struggle to keep pace with rapid artificial intelligence (AI) development in healthcare.
• AI applications introduce novel ethical and legal dilemmas beyond traditional bioethics and legislation.
• Establishing definitive professional guidelines and regulations for AI in healthcare is a slow process.

Purpose of the Study:

• To examine the ethical challenges at the intersection of AI and healthcare research.
• To identify key ethical principles for responsible AI implementation in healthcare.
• To discuss ethical considerations throughout the AI development lifecycle.

Main Methods:

• Literature review of AI in healthcare ethics.
• Analysis of ethical principles relevant to AI.
• Examination of AI development lifecycle stages for ethical implications.

Main Results:

• Key ethical principles include justice, data stewardship, explainability, accountability, and sustainability.
• Ethical considerations span from AI problem identification to post-deployment evaluation.
• The dynamic nature of AI necessitates adaptive ethical frameworks.

Conclusions:

• Responsible AI in healthcare requires a proactive approach to ethical challenges.
• Adherence to core ethical principles is crucial for trustworthy AI systems.
• Ongoing dialogue and adaptive governance are essential for navigating AI's ethical landscape in healthcare.