Abstract
This article analyzes local algorithmic practices resulting from the increased use of time-lapse (TL) imaging in fertility treatment. The data produced by TL technologies are expected to help professionals pick the best embryo for implantation. The emergence of TL has been characterized by promissory discourses of deeper embryo knowledge and expanded selection standardization, despite professionals having no conclusive evidence that TL improves pregnancy rates. Our research explores the use of TL tools in embryology labs. We pay special attention to standardization efforts and knowledge-creation facilitated through TL and its incorporated algorithms. Using ethnographic data from five UK clinical sites, we argue that knowledge generated through TL is contingent upon complex human-machine interactions that produce local uncertainties. Thus, algorithms do not simply add medical knowledge. Rather, they rearrange professional practice and expertise. Firstly, we show how TL changes lab routines and training needs. Secondly, we show that the human input TL requires renders the algorithm itself an uncertain and situated practice. This, in turn, raises professional questions about the algorithm's authority in embryo selection. The article demonstrates the embedded nature of algorithmic knowledge production, thus pointing to the need for STS scholarship to further explore the locality of algorithms and AI.
Highlights
Embryo Assessment, Algorithms, and Knowledge StandardizationTime-lapse (TL) imaging technologies were developed in the midst of a research-intensive period in the field of assisted reproductive technologies (ART)
As STS scholars grapple with the social implications of algorithms (Crawford 2016; Lee and Helgesson 2020), we offer a view of algorithmic lab technologies as situated and disruptive, suggesting that knowledge-creation through algorithms is a local process-in-the-making rather than a straightforward achievement through the introduction of a technology alone
TL algorithm scores are meant to improve embryo selection, we found that this new knowledge dimension was not always easy to integrate within established professional practices
Summary
Embryo Assessment, Algorithms, and Knowledge StandardizationTime-lapse (TL) imaging technologies were developed in the midst of a research-intensive period in the field of assisted reproductive technologies (ART). The technology has required professionals to rearrange lab routines, while navigating the demands of the algorithmic embryo selection process. We paid close attention to the use of TL in the lab, the annotation and selection process, and professional engagement with selection algorithms and information generated through TL technologies.
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