ArticleSocial studies of science2023
Eye for an AI: More-than-seeing, fauxtomation, and the enactment of uncertain data in digital pathology.
Article in Social studies of science, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed, 23 citations in OpenAlex.
- 'I Put a Lot of Emotion in My Work, I Use It, It's My Tool': An Ethnographic Account of Algorithmic Homecare Assistance in the Netherlands.Sociology of health & illness · 2026Article
- Implementing AI in Radiotherapy: Insights From the Healthcare Professions.Sociology of health & illness · 2026Article
- Artificial intelligence and gender equity: An integrated approach for health professional education.Medical education · 2025Article
- Streamlining a Patchwork - Exploring the Challenges of Digital Transformation in Pathology: Ethnographic Study.Journal of medical Internet research · 2025Article
- And say the AI responded? Dancing around 'autonomy' in AI/human encounters.Social studies of science · 2024Article
- Enabling 'AI'? The situated production of commensurabilities.Social studies of science · 2023Article
- Groundwork for AI: Enforcing a benchmark for neoantigen prediction in personalized cancer immunotherapy.Social studies of science · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial Intelligence (AI) tools are being developed to assist with increasingly complex diagnostic tasks in medicine. This produces epistemic disruption in diagnostic processes, even in the absence of AI itself, through the datafication and digitalization encouraged by the promissory discourses around AI. In this study of the digitization of an academic pathology department, we mobilize Barad's agential realist framework to examine these epistemic disruptions. Narratives and expectations around AI-assisted diagnostics-which are inextricable from material changes-enact specific types of organizational change, and produce epistemic objects that facilitate to the emergence of some epistemic practices and subjects, but hinder others. Agential realism allows us to simultaneously study epistemic, ethical, and ontological changes enacted through digitization efforts, while keeping a close eye on the attendant organizational changes. Based on ethnographic analysis of pathologists' changing work processes, we identify three different types of uncertainty produced by digitization:
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.