Med Health Care Philos. 2026 Apr 1. doi: 10.1007/s11019-026-10346-2. Online ahead of print.
ABSTRACT
Artificial intelligence is increasingly integrated into medical decision-making, often framed as a supportive tool that enhances accuracy while leaving final judgment to clinicians. This paper argues that such framing obscures a deeper structural shift: medical action may proceed without any judgment ever occurring. AI systems do not judge; they generate outputs through statistical transduction. Clinicians, under institutional and legal pressures, may relay these outputs without regenerating them as their own reasons. When neither AI nor clinician generates judgment, decisions are enacted without a judging subject. While judgment without a judging subject may be sustainable elsewhere, medicine renders this absence unsustainable. Medical practice is characterized by irreversibility, case-specificity, meaning-demand, and relational accountability-features that presuppose judgment as a human act. Even clinically correct outcomes do not guarantee that patients will recognize a decision as right for them. When judgment disappears, informed consent persists only as a procedural ritual, simulating understanding without grounding it. To make this absence explicit, the paper introduces Metaqualia Theory (MTQ), distinguishing patient experience (Q), technical transduction (T), and judgment as meaning-generating endorsement (M). This leads to a prior ethical question: Is there an M here? This question precedes concerns about explainability and helps clarify the conditions under which consent and responsibility remain meaningful. The analysis suggests that when AI outputs are not regenerated as human judgment, their role in medical practice raises structural limits that cannot be addressed by transparency alone.
PMID:41920434 | DOI:10.1007/s11019-026-10346-2
