Discursive Ethics as a Normative Foundation for Integrating Ethics into AI Clinical Decision Support Systems

Area of Science:

• Bioethics
• Computer Science
• Philosophy

Background:

• Artificial Intelligence (AI) integration in healthcare raises concerns about human autonomy and opaque decision-making.
• Ethical integration of AI into Clinical Decision Support Systems (CDSS) requires robust normative foundations.
• Understanding human moral judgment models is crucial for AI ethics.

Purpose of the Study:

• To examine the normative foundations for responsible AI integration in healthcare.
• To propose a discursive ethics framework for AI-based CDSS.
• To ensure AI enhances human agency and trust in clinical practice.

Main Methods:

• Review of descriptive models of human moral judgment (rationalist, intuitionist, integrative), focusing on the Actor-Deed-Consequences (ADC) model.
• Proposal of a discursive ethics framework based on communicative rationality, stakeholder involvement, transparency, and accountability.
• Analysis of ethical requirements for AI deployment in healthcare.

Main Results:

• Descriptive models alone are insufficient for the legitimacy of AI-assisted clinical decisions.
• A discursive ethics framework provides essential conditions for ethically acceptable AI deployment.
• AI-based CDSS should function as dialogical tools supporting human judgment.

Conclusions:

• Embedding discursive ethical procedures in AI architectures is a normative pathway for responsible innovation.
• Ethical AI in healthcare must enhance human agency, safeguard dignity, and strengthen trust.
• AI-based CDSS require development as process-oriented tools that support, rather than replace, human decision-making.