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Short abstract:

We propose a three-stage methodology to research the emerging arrangements for implementing medical AI. We examine this in an investigation of different strategies for developing, implementing and validating AI diagnostic tools.

Long abstract:

STS research into medical AI requires strategies to keep up with the rapid deployment of AI tools in an evolving landscape. Traditional methods, like ethnographies of developer or user organisations, struggle to capture the emergence of new actors, their strategic transformation and constantly changing relationships. To address this, we propose an adaptive evolutionary methodology involving three phases: Landscape, Vignettes, and In-depth study. We developed and refined this methodology in an investigation of different strategies for developing, implementing and validating AI diagnostic tools. This methodology seeks to balance the insights from detailed local ethnography with the need to track emerging institutional and technical arrangements through interaction between diverse players over an extended period and across multiple locales.

Landscape: initial interviews with stakeholders offer insights into their perspectives, aids in understanding the challenges and solutions in adopting medical AI, and helps identify dilemmas and emerging trends that guide further detailed studies.

Vignettes: cases selected from the Landscape to compare strategies across settings. Our medical AI study analyses two cancer detection tools to understand the interplay between AI developers, health providers and their contingent innovation ecosystems.

In-depth study charts the long-term change process in a single case to capture the complex dynamics surrounding the emergence of a key player.

The methodology draws upon the Biography of Artefacts and Practice perspective. More specific STS concepts that engage these evolving developments — including theories of information infrastructure, domestication/social learning — will inform the interpretation of empirical findings and their implications for policy and practice.