Short abstract

Based on a sensory ethnography with a diabetes community developing a DIY automated insulin delivery system, this paper traces how sex steroid hormones are algorithmically scripted and re-coded as vital molecular signals that shape metabolic futures of people living with diabetes who menstruate.

Long abstract

In automated insulin delivery (AID) systems molecular life is continuously sensed and algorithmically predicted. Blood glucose levels are tracked in real time and translated into algorithmic adjustments of insulin dosing, producing predictive models that attempt to stabilize anticipated metabolic futures. However, sex steroid hormones secretions during menstrual cycle or menopause, modulate insulin sensitivity, reshaping metabolic responsiveness in ways that exceed standardized computational models.

Building on scholarship that reframes hormones as signaling cascades rather than messengers of sex (Ford et al., 2024), and developing Preciado’s notion of techno-biopolitical scripting (2013), I explore hormonal regulation in diabetes care as a molecular techno-bio-code: a script that materializes in tissues, devices, and data infrastructures, stabilizing particular endocrine norms. When algorithms fail to anticipate hormonal variability, deviations are not merely transient errors; recurrent hypo- or hyperglycemic episodes can sediment into metabolic memory, producing cumulative risk that shapes the long-term metabolic futures of people living with diabetes who menstruate. Toxicity thus emerges not only from excess or deficiency of a substance, but from misalignment between distinct molecular cocktails and the standardized codes designed to govern them.

Based on ethnographic fieldwork with users and developers of DIY AID systems, I show how such scripts can be re-coded. Through hormonal mind mapping, a collaborative sensory drawing practice, research partners trace how hormonal rhythms intra-act with algorithms, identifying which fluctuations can be encoded and which remain technically untranslatable. Hormones thus appear simultaneously as a source of metabolic risk and as a vital signal through which users recalibrate algorithmic care.