Munjal Shah Bets on Health Care LLMs for ‘Super Staffing’

Serial entrepreneur Munjal Shah sees tremendous potential in using large language models (LLMs) to help alleviate global healthcare staffing shortages. However, he believes success lies not in aspiring to fully automate doctors’ diagnostic work but in applying LLMs’ communication strengths to non-diagnostic chronic care support.

Shah sharply distinguishes between LLMs’ creative language generation capabilities versus most AI’s classification and categorization strengths. While the latter excels at analyzing data to make judgments, Shah notes LLMs’ exceptional ability to produce original, human-like content after training on diverse texts. He argues LLMs can provide knowledgeable, empathetic patient interactions akin to human health workers.

Consequently, Shah’s new startup, Hippocratic AI, focuses narrowly on leveraging LLMs to deliver supportive chronic care services like nursing check-ins, diet planning, transportation coordination, and social assistance referrals. Shah stresses that bypassing diagnosis, where lives are directly at stake, is essential for responsible LLM adoption, given AI’s propensity to occasionally “hallucinate” false information. However, he sees massive unmet needs in non-diagnostic care, which has profound health impacts but needs more staffing due to a global shortage of over 15 million health workers.

Shah envisions LLMs filling gaps by providing round-the-clock supportive care at scale. With infinite time and no burnout, they could support far more patients than humanly possible. Hippocratic AI’s LLMs are specifically trained based on how real-world health workers communicate to encourage patient engagement. With ongoing reinforcement learning from professional feedback, Shah aims to create “fully autonomous agents” providing comprehensive chronic care to help resolve care access issues globally.

Rather than inflating expectations, Shah argues LLMs may still be “underhyped” given their unprecedented creative potential. He believes thoughtfully targeted applications like Hippocratic AI’s “super staffing” concept highlight how this new AI breakthrough could positively impact industries like health care. With LLMs still in their infancy, Shah sees a long runway for finding responsible, ethical uses that provide societal value.

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