The First Generative AI Prompt-A-Thon in Healthcare: A Novel Approach to Workforce Engagement with a Private Instance of ChatGPT
William R. Small, Kiran Malhotra, Vincent J. Major, Batia Wiesenfeld, Marisa Lewis, Himanshu Grover, Huming Tang, Arnab Banerjee, Michael J. Jabbour, Yindalon Aphinyanaphongs, Paul Testa, Jonathan S. Austrian
Abstract
Healthcare crowdsourcing events (e.g. hackathons) facilitate interdisciplinary collaboration and encourage innovation. Peer-reviewed research has not yet considered a healthcare crowdsourcing event focusing on generative artificial intelligence (GenAI).
Introduction
Generative artificial intelligence (GenAI) use exploded with ChatGPT’s release to the public in late 2022. Large language models (LLMs), which learn from vast amounts of text data to "understand” the context in which words appear and ultimately, their meaning, belong to a class of artificial intelligence (AI) called GenAI.
Material and Methods
To fulfill our objectives, we assembled a large team of clinical leaders, researchers, information technology experts, product managers, and event planners to organize and execute this event (Fig 1).
Result
There were 412 applicants for our event, and the committee selected 90 participants. There were 70 attendees and 56 staff members on the day of the event, and an additional 375 virtual attendees of the didactic sessions.
Discussion
The NYULH Prompt-a-thon aimed to augment the understanding and utilization of GenAI within our workforce, with the broader goal of democratizing the technology throughout our health system.
Conclusion
In conclusion, the Prompt-a-thon successfully brought together diverse healthcare professionals to explore and engage with GenAI, demonstrating its transformative potential and accessibility.
Citation: Small WR, Malhotra K, Major VJ, Wiesenfeld B, Lewis M, Grover H, et al. (2024) The First Generative AI Prompt-A-Thon in Healthcare: A Novel Approach to Workforce Engagement with a Private Instance of ChatGPT. PLOS Digit Health 3(7): e0000394. https://doi.org/10.1371/journal.pdig.0000394
Editor: Janna Hastings, University of Zurich Faculty of Medicine: Universitat Zurich Medizinische Fakultat, SWITZERLAND
Received: October 26, 2023; Accepted: June 10, 2024; Published: July 23, 2024
Copyright: © 2024 Small et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: All relevant data are within the manuscript and its Supporting Information file.
Funding: The author(s) received no specific funding for this work.
Competing interests: The authors have declared that no competing interests exist.
Source: https://journals.plos.org/digitalhealth/article?id=10.1371/journal.pdig.0000394#abstract0
