Related papers: A quality of mercy is not trained: the imagined vs. the practiced in healthcare process-specialized AI development

A quality of mercy is not trained: the imagined vs. the practiced in healthcare process-specialized AI development

URL: http://arxiv.org/abs/2510.21843v1
Date: Wed, 22 Oct 2025 14:48:35 GMT
Title: A quality of mercy is not trained: the imagined vs. the practiced in healthcare process-specialized AI development
Authors: Anand Bhardwaj, Samer Faraj,
Abstract summary: We show how early representational decisions narrowed what the AI could support, resulting in the premature exclusion of key ethical dimensions from system design.<n>Our findings surface the moral consequences of abstraction and call for a more situated approach to designing healthcare process-specialized artificial intelligence systems.
Score: 0.0
License: http://creativecommons.org/licenses/by/4.0/
Abstract: In high stakes organizational contexts like healthcare, artificial intelligence (AI) systems are increasingly being designed to augment complex coordination tasks. This paper investigates how the ethical stakes of such systems are shaped by their epistemic framings: what aspects of work they represent, and what they exclude. Drawing on an embedded study of AI development for operating room (OR) scheduling at a Canadian hospital, we compare scheduling-as-imagined in the AI design process: rule-bound, predictable, and surgeon-centric, with scheduling-as-practiced as a fluid, patient-facing coordination process involving ethical discretion. We show how early representational decisions narrowed what the AI could support, resulting in epistemic foreclosure: the premature exclusion of key ethical dimensions from system design. Our findings surface the moral consequences of abstraction and call for a more situated approach to designing healthcare process-specialized artificial intelligence systems.

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