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Short abstract:

We present our ethnography of information technologists and healthcare providers as they implement a generative AI system for responding to patient messages. We will share how learning health science shapes our work and the challenges we have faced studying generative AI in the clinical space.

Long abstract:

Since the public release of the generative AI chatbot - ChatGPT, healthcare systems and electronic health record (EHR) vendors have jumped at the opportunity to integrate generative AI into clinical practice. At a large academic health center in the Midwestern United States, an interdisciplinary team of information technology (IT) professionals is working to roll out a system using ChatGPT to create AI-generated draft responses to patient inbox messages. The use of generative AI for assistance in administrative documentation tasks such as this is novel and rapidly evolving.

In this panel, we will present our current ethnography, exploring the emergent behaviors, interactions, and perceptions of the IT experts and healthcare providers who use, implement, and evaluate this new technology. We will discuss how the implementation, use, and evaluation of generative AI technologies are entangled processes that cannot be studied in isolation and how ethnography can help us understand the social phenomena that influence these processes. Our ethnographic methods are complemented by exploratory data analysis techniques using natural language processing. We will share how adding these techniques can support the findings of traditional ethnographic approaches when studying medical AI.

We frame our discussion and interpretative lens through the perspective of learning health sciences. Our presentation will explore how this perspective influences our current work and its contribution to STS scholarships on medical AI. Additionally, we will present the challenges we have encountered in the field as we try to negotiate our role as ethnographers with the expectations of IT professionals and providers.