ChatGPT 'Health' Enters Healthcare: Is Protocol-Based Medicine Ending?
A trial in Utah demonstrated that artificial intelligence can renew medical prescriptions with 99.2% accuracy compared to human doctors. The news has chilled the sector, where anxiety grows since OpenAI released its 'Health' module. Are we witnessing the beginning of the end for traditional medicine?
AI Diagnosis is Now a Reality
The data leaves no doubt: in 99.2% of cases, the AI did exactly what a real doctor did in the Utah trial. This is not an isolated case. In radiology, machines already filter thousands of normal images so radiologists can focus on suspicious ones. According to a study shared in the debate, AI-driven drug discovery is 10 times faster and cheaper. The question is no longer if AI can diagnose, but what remains for humans.
Protocols vs. Clinical Judgment
One sharp line of analysis points out that modern medicine has abandoned clinical judgment in favor of standardized protocols, often dictated by the pharmaceutical industry. If doctors have become algorithm appliers, AI will do it better, faster, and without fatigue errors. Some argue that many doctors already check their phones during consultations, making AI just a logical next step. Others, however, warn of the risk of overdiagnosis and note that most people are unable to use these tools correctly, as happens with Google.
Robotic Surgery and Knowledge Privatization?
Elon Musk stated in a January 2026 interview that within 3 to 5 years, robots could perform surgeries at the level of the world's best surgeons. Moreover, the debate raised a darker scenario: the privatization of knowledge. If only machines know how to diagnose certain diseases, access to that knowledge will be limited to those who can pay, leaving the population dependent on closed systems. "Just as they took your chickens, they will take your knowledge," one analysis summarizes.
The positions are clear: those who believe AI is a tool that will free doctors to focus on human care, and those who think it is the Trojan horse of soulless medicine, where patients are just numbers. Time will tell, but the data is already on the table.
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