Ethics of AI in Pathology: Current Paradigms and Emerging Issues

Area of Science:

• Pathology
• Artificial Intelligence
• Medical Ethics

Background:

• Deep learning has advanced artificial intelligence (AI) and algorithmic decision-making (ADM) in medicine, particularly pathology.
• Pathology's data-rich environment is attractive for AI development, promising increased healthcare efficiency.
• Unethical AI implementation risks exacerbating existing healthcare inequities.

Purpose of the Study:

• To explore key issues in artificial intelligence ethics within pathology.
• To discuss ethical design and potential risks of AI and ADM in pathology workflows.
• To emphasize the need for ethical AI implementation in pathology.

Main Methods:

• Review of ethical issues in AI and ADM in pathology.
• Discussion of ethical design principles for AI studies in pathology.
• Exploration of risks associated with AI implementation in pathology workflows.

Main Results:

• Identified ethical challenges in AI and ADM for pathology.
• Highlighted the importance of ethical design and risk assessment for AI in pathology.
• Emphasized the need for transparency, accountability, and governance in AI.

Conclusions:

• Future pathology practice must be guided by ethical AI principles: transparency, accountability, and governance.
• Pathologists must understand AI's potential benefits and ethical risks.
• Pathologists' involvement is essential for driving ethical AI implementation in pathology.