The algorithmic covenant: why AI-driven consent must not replace clinician responsibility

Area of Science:

• Medical Ethics
• Health Informatics
• Sociotechnical Systems

Background:

• Healthcare systems increasingly use artificial intelligence (AI) for tasks like procedural disclosure and documentation.
• AI tools in patient consent workflows may improve efficiency but risk substituting algorithmic disclosure for essential clinician-patient dialogue.
• Existing consent processes are often deficient, making the ethical implications of AI integration critical.

Purpose of the Study:

• To perform a conceptual analysis of the "algorithmic covenant" in healthcare AI.
• To examine the risks of AI in informed consent, particularly regarding responsibility and ethical commitments.
• To propose guidelines for governing AI to preserve the integrity of informed consent.

Main Methods:

• Conceptual analysis drawing on legal standards of material risk.
• Sociotechnical scholarship on "moral crumple zones" and ethical tensions.
• Analysis of current AI deployment risks, including "responsibility laundering."

Main Results:

• Current AI deployments risk "responsibility laundering," where institutions prioritize efficiency, standardizing disclosure via AI.
• This creates a misaligned responsibility structure, leaving clinicians to absorb blame and legal risk for AI-generated consent artifacts.
• AI-driven consent may degrade into a digitized "tick-box" exercise, diminishing genuine patient understanding.

Conclusions:

• AI in healthcare consent must be strictly governed as an assistive technology, not a replacement for dialogue.
• Policy and workflow design must explicitly assign clinicians the responsibility for verifying patient understanding.
• Automation should support, not displace, the clinician's non-delegable ethical duty for informed consent.