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Paper short abstract

Presenting results of a year and a half of video ethnographic study, the communication will address some effects of using AI-based support-decision devices in radiology (mammography), showing that tensions arise in practice regarding epistemic distribution problems related to AI.

Paper long abstract

Our video-based ethnography of radiologists’ use of AI decision-support devices in breast cancer detection, sheds light on several integration issues arising in practice. We highlight three distinct types of use that illustrate different positions and tensions regarding these devices. These forms of use correspond to different epistemic distributions:

1. AI is “separated”, queued, and epistemically subordinated to the radiologist’s authority. Radiologists maintain the lead throughout the entire reading process, enabling AI advice within a confirmation/invalidation framework (thus eluding most of the potential ambiguity it may introduce).

2. AI is “intertwined” with radiologists’ reading through the enactment of two independent channels of interpretation. Radiologists temporarily eclipse their own authority and assess, at the end, the outcome of the confrontation between both readings.

3. AI is “merged” and closely incorporated into radiologists’ reading from the beginning of the process, the boundaries between the two authorities and reading modalities becoming blurred.

From these empirical observations, several effects of AI on radiological reading can be inferred. The practice becomes reframed and tensioned around what counts as its good and legitimate forms, thereby relocating the stakes and the object of radiologists’ authority:

• the assumption of the radiologist’s legitimate authority and ability to decide while avoiding doubt (1);

• the open interpretive deliberation as the core of the clinical process, which should unfold fully (2);

• the evaluation of AI advice as the central focus of the reading (3).