Invited Response to "Artificial Intelligence in Rhinoplasty: Precision or Over-Reliance?"

Overview

This is a reply to a commentary that raised concerns about the limits of artificial intelligence in operative planning, particularly where human judgment, healing and aesthetic discernment resist algorithmic modelling. The authors accept those limits but argue they clarify the appropriate role rather than justify rejection. Their position is that the value lies in augmentation, not replication.

Sections of note

• Article type: invited response to another commentary. Level of evidence V. No patient data are reported.
• The original commentary raised limits around human judgment, healing trajectories and aesthetic discernment.
• Stated position: those limits define where artificial intelligence belongs rather than grounds for rejecting it.
• Named potential benefits: reducing cognitive burden, streamlining repetitive tasks, and extending access to reliable patient centered information.
• Stated principle: the value is in augmentation, not replication.
• Named foundational requirements: accountability, representational fairness and data security, described as foundational rather than optional additions.
• Stated framing: the issue is integration rather than a choice between precision and over-reliance.

What it means for a patient

• The argument is that these tools should handle information and administrative work rather than predict what surgery will achieve.
• Representational fairness means the systems should not perform worse for patients whose features are underrepresented in training data.
• Data security matters because facial images and medical records are what these systems process.
• The abstract carries no findings. It is an exchange of positions with no data on either side.

Why this paper matters

How artificial intelligence enters surgical practice is being decided now, largely through commentary rather than trials, and published exchanges shape what practitioners consider acceptable. Framing the question as integration rather than replacement is the position gaining ground. Neither side supplies evidence about effects on patients.

Terms

• Artificial intelligence: software that performs tasks normally requiring human judgment.
• Augmentation: supporting human work rather than replacing it.
• Cognitive burden: the mental effort a task demands of a clinician.
• Representational fairness: whether a system performs equally well across different groups of people.
• Level of evidence V: the weakest evidence grade, covering expert opinion.