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Hippocratic's generative AI for healthcare: supplement, not substitute, for nurses?

One announcement from Nvidia's recent AI developer conference caused an uproar: the company's partnership with Hippocratic AI, a startup providing virtual healthcare workers at an hourly rate. A widely shared article is titled "Nvidia Wants to Replace Nurses With AI for $9 an Hour," and many readers followed that clickbaity lead, expressing outrage on behalf of both patients and nurses.

Hippocratic isn't actually aiming to replace nurses at below-minimum wage (at least, not yet). What's on offer is a suite of virtual generative AI healthcare agents, each with their own specialty. Diane, for example, performs weekly check-ins for patients with chronic kidney disease, while Nancy runs pre-ops for colonoscopies, reviewing instructions, explaining the procedure and confirming that a patient has a ride to and from the hospital.

All interactions take place in a telehealth setting, using natural language and a conversational style. Agents can be programmed to follow a healthcare provider's specific policies and instructions; and yes, Hippocratic prices them at USD 9/hour or less.

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Around the world, healthcare systems are struggling to hire nurses. Hospitals blame massive shortages; nurses say the staffing crisis is caused by low pay and poor working conditions, often due to intentional, profit-driven understaffing. Whatever the cause, the result is overworked staff and less access to care for patients.

Hippocratic's agents offer a solution not by replacing nurses, but by taking on routine tasks like patient education and admin, freeing up human staff for more complex work. Besides shorter wait times and improved access — agents are on call 24/7 — patients could also benefit in other ways. Without worrying about taking up too much of a nurse's time, they can ask agents to repeat instructions or pose a question they might feel is 'dumb.' And Diane and Nancy never have a bad day or run out of patience.

Only time will tell if gen AI healthcare assistants prove viable and trustworthy. What's certain is that robust ethical guidelines and safety guardrails must be put in place: strict oversight and auditing processes, transparency around the AI's training data and potential biases, clear policies limiting AI involvement to low-risk tasks, and prioritizing human medical expertise for high-stakes decisions impacting patient health. When it comes to sensitive domains like healthcare and education, public trust hinges on meticulous execution.