The robotic PIANO: a critical narrative review of surgeon-controlled operative polyphony, human factors, and robotic training

Abstract Robotic surgery can concentrate control of several technical functions at the console, but such concentration does not itself confer clinical independence, reduce dependence on the perioperative team, or improve patient outcomes. We define surgeon-controlled operative polyphony as the phase-bounded coordination of multiple partially independent technical control streams by one console operator within a distributed perioperative system. This critical narrative review and conceptual synthesis asks which technical functions can be concentrated coherently, where human-factors and team dependencies set limits, and how evaluation, training, and governance should respond. The piano is used as a question-generating model, not as evidence of clinical benefit. PubMed/MEDLINE was searched from inception through 18 August 2026; targeted engineering, educational, neuroscientific, human-factors, and musicological searches and backward citation tracking supplemented retrieval. To analyze this control configuration, we propose the PIANO framework: Phase-specific control, Interface fidelity, Agency allocation, Neuromotor integration, and Orchestrated teamwork. Its scientific novelty lies in linking this control architecture to the PIANO framework: Phase-specific control, Interface fidelity, Agency allocation, Neuromotor integration, and Orchestrated teamwork. PIANO is an analytic and hypothesis-generating framework, not a score or credentialing standard. Concentrated control may shorten selected action loops, but any benefit depends on feedback, workload, shared situation awareness, explicit authority, and rescue capacity. The Competency-Based Assessment of Robotic Surgery Skills (CARS) curriculum provides initial validation evidence for domain-specific assessment of performer competence; repeated cases and use-specific evidence remain necessary for high-stakes decisions. Artificial intelligence (AI) may support phase recognition, feedback, assessment, and personalised training within a human-in-the-loop system. One surgeon may coordinate many operative voices; safe surgery remains a collective, patient-centered performance.