Harvey Castro, MD, MBA

Patients are hearing more about artificial intelligence (AI) in medicine. Some are excited. Some are worried. Many are unsure what it means when a clinician, hospital, insurer, or digital health company says AI is being used in their care. That uncertainty matters.

Trust is not created by telling patients that a tool is advanced. Trust is created when patients understand what is happening, why it is happening, who is responsible, and …

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Artificial intelligence is no longer a future issue for hospital boards. It is already affecting clinical documentation, patient communication, revenue cycle operations, imaging, scheduling, research, cybersecurity, and physician workflow. In many organizations, AI is entering through the side door before leadership has created a clear strategy. That is risky.

A hospital does not need an AI strategy because AI is fashionable. It needs one because unmanaged AI creates clinical, operational, …

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Artificial intelligence (AI) is entering medicine faster than many physicians expected. It is already helping draft notes, summarize records, answer patient questions, support imaging workflows, and organize clinical data. Some tools are useful. Some are premature. Many are somewhere in between.

The question for physicians is no longer whether AI will appear in clinical care. It already has. The real question is how to use it without giving away the judgment …

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Every few months, the news runs with a headline about artificial intelligence replacing doctors. A model passes an exam. A chatbot answers a patient question. A system summarizes a chart or reads an image. The debate starts again.

Will AI replace physicians? I think that is the wrong question. The better question is: Which parts of modern medical work should never have been placed on physicians in the first place?

Doctors are …

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The attending scrolls through the chart before morning rounds. The progress note is polished. The assessment is structured. The differential is surprisingly thorough. A predictive model flags the patient as high risk for deterioration within 24 hours. He did not write most of it.

An AI assistant drafted the note. A risk algorithm generated the alert. A decision-support tool suggested broadening the workup. He reviewed it. He agreed with most of …

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Medicine has always loved the story of the hero.

The physician who pushes through exhaustion. The one who catches the rare diagnosis at the last second. The colleague who seems to carry an impossible load without ever dropping the ball.

But after years of watching which physicians actually thrive, not just survive, I have come to believe we have been telling the wrong story.

The doctors who perform at the highest level over …

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Artificial intelligence (AI) is rapidly entering clinical spaces, and ChatGPT is among the tools drawing increasing interest. Hospitals recognize their potential to reduce administrative burden, improve communication, and support clinical decision-making.

But with this potential comes responsibility. Deploying large language models (LLMs) in health care without proper oversight can lead to misinformation, privacy breaches, and erosion of patient trust. Before implementation, hospitals must establish a framework grounded in safety, ethics, and …

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“The danger isn’t that AI is too powerful; it’s that we stop questioning it.”

Artificial intelligence in medicine is often described as revolutionary, capable of diagnosing disease, predicting deterioration, and automating once-human decisions. But I want to suggest a different lens, one drawn not from technology, but from history.

Let’s go back to ancient Greece.

There, leaders turned to the Oracle of Delphi not for …

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At this point, numerous individuals have become engaged with ChatGPT. We’ve asked it to summarize a complex patient history and draft a discharge summary or explanation of a rare clinical concept. At first, it feels like magic. However, after several weeks, that same old feeling of frustration returns. Why does this still feel like more work?

The problem is not that technology is lacking. The problem is that ChatGPT was never …

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When ChatGPT burst onto the scene in late 2022, many clinicians glimpsed the future then ran smack into a wall of red tape labeled “HIPAA.” Since then, large-language models (LLMs) have matured from clever chatbots into workhorse tools that summarize admission notes, draft prior-authorization letters, and even suggest antibiotic dosing. Yet most models still sit outside the guarded perimeter of protected health information.

Grok 4, the next-generation model from xAI, could …

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Why doctors should care

• Generative AI has moved from hype to bedside utility.
• Ambient “copilot” apps draft encounter notes.
• Large language models (LLMs) summarise new studies in seconds.
• Early adopters save hours each week and report less burnout.

Five core concepts, clinical parallels

• Neural networks → Repeated pattern-finding, like residents running endless simulations.
  Example: Abridge and Nuance DAX learn note structure from thousands of visits.
• Prompt engineering → Give precise orders, just

…

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As artificial intelligence gains ground in every aspect of health care, from diagnostics to documentation, an urgent question arises: Are we gaining efficiency at the cost of empathy?

Drawing inspiration from Simon Sinek’s perspective on AI and humanity, this piece explores how health care can embrace innovation without compromising the very heart of medicine.

1. Humanity first, technology second

“I’m not in the AI business. I’m in the humanity business.” – Simon Sinek

AI …

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A comprehensive 2025 framework on medical education reform has laid bare a critical challenge: The traditional path to becoming a doctor is failing to meet the demands of modern health care. The consequences are stark: 70 percent of medical students report frequent feelings of burnout, persistent health disparities remain entrenched, and a median debt of $200,000 is pushing graduates away from essential careers in primary and public service care.

This new …

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