Aug 2026· Journal of The American Geriatrics Society· 0 citations· 18 references
Medicine
TL;DR
This commentary offers a framework organized around three fundamental domains of clinical care-information collection, data analysis, and treatment delivery-and describes how the physician's role within each is shifting rather than disappearing.
Abstract
The integration of artificial intelligence and robotics into clinical medicine is no longer a question of whether but of how, and physicians currently caring for older adults with complex multimorbidity need practical guidance for the transformation ahead. This commentary offers a framework organized around three fundamental domains of clinical care-information collection, data analysis, and treatment delivery-and describes how the physician's role within each is shifting rather than disappearing. In information collection, the clinician moves from direct performer to supervisor, deciding which data streams and alerts warrant attention and eliciting the contextual, values-based history no algorithm can capture. In data analysis, where AI will prove most transformative, the physician becomes a critical appraiser and ethical arbiter of machine-generated options, a role demanding vigilance against documented hazards: training-data bias, digital ageism, large language model confabulation, and automation bias. In treatment delivery, the physician becomes an orchestrator, matching the level of intervention to the patient's goals across a spectrum from robotic nursing support to autonomous self-management. Throughout, the organizing principle is augmented intelligence-AI as an amplifier of expert physician judgment rather than a replacement for it-operationalized as an architectural safeguard in which AI outputs remain interrogable, sourced, and subordinate to the responsible clinician. A specialty-endorsed certification of clinical AI tools, modeled on the American Geriatrics Society Beers Criteria, is proposed. Geriatric medicine's emphasis on multimorbidity, goals-of-care conversations, and interdisciplinary coordination, exemplified by the PACE model, positions geriatricians to lead this transition and to prepare, beginning today.
Bedside use of artificial intelligence (AI) platforms is increasingly common. Busy clinicians may welcome these generative AI (Gen AI) tools, which have the potential to streamline many time-consuming tasks and aid in patient care. Trainees may find them useful to quickly evaluate complex medical information. Acceptanc...
K. MacDuffie, Douglas S. Diekema, J. Kett et al.· Pediatrics· 0 citations
It is argued that the convergence of pressing healthcare demands, technological advancements, and cultural readiness signals a tipping point for PAI in medicine.
Yonatan Prat, R. Francos, M. Shoham et al.· Frontiers in Digital Health· 0 citations
The operating room is evolving into an information-rich environment where surgical care is increasingly shaped by integrated digital architectures. The proliferation of minimally invasive and robotic platforms has generated a massive influx of high-resolution video, shifting the field toward real-time computational ana...
B. Sengun, Y. Iscan· Turkish Journal of Surgery· 0 citations
BackgroundThe rapid integration of Artificial Intelligence (AI) into healthcare and industry is often framed as a threat to human roles. Within rehabilitation and occupational health, this polarized discourse risks obscuring more nuanced possibilities for human-AI collaboration.ObjectiveThis article challenges the domi...
Agentic artificial intelligence (AI), comprising autonomous, goal-oriented systems capable of reasoning, planning, and coordinating multi-step clinical workflows under clinician oversight, is emerging as a transformative paradigm in modern healthcare. This study presents a systematic review of its conceptual foundation...
The focus of artificial intelligence (AI) research is rapidly moving beyond screen-based generative models toward physical AI, an umbrella paradigm for computational systems with physical embodiments that can perceive, reason, and act directly in the real world. In robotics, physical AI is increasingly being implemente...
Eui-Suk Sung· Kosin Medical Journal· 0 citations
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