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Paper short abstract

Self-tracking entails ongoing anticipatory waiting. Data are encoded through sensors and algorithms, while meaning is deferred to future insight. Based on a qualitative study of wellness users of continuous glucose monitors, this paper shows how tracking sustains perpetual waiting for better health.

Paper long abstract

Everyday AI systems for self-tracking often involve different degrees of anticipatory waiting, either to ensure something potentially negative has been prevented, or to be able to ‘diagnose’ when something negative is happening. Yet for many self-trackers, waiting has no clear endpoint and through their tracking practices, they are offered more data, more observations, and more suggestions from these systems such that waiting becomes a permanent way of life. Drawing on encoding/decoding theory, this paper argues that self-tracking is organised around temporal delays and waiting between data production and meaning-making. On the encoding side, bodily signals are continuously encoded through sensors, algorithms, data visualisations and nudges. Decoding, however, is deferred and repeatedly postponed, such that meaning comes to be positioned as a future achievement that will eventually emerge over time if the individual is patient enough, attentive enough, and generally engaged in tracking themselves. In this way, self-tracking technologies create the illusion that such a comprehensive understanding of oneself and one’s health is possible. Empirically, the paper is based on a qualitative study that combines online observation, interviews and data walkthroughs with people who use continuous glucose monitors (CGM) for wellness purposes. The analysis shows how self-tracking situates people in a temporal structure of anticipatory waiting for an ever-improving future state of health, sustained through practices to maintain oneself as a trackable human being who is constantly in the wait for new interpretation and meaning, often with the help of peers in decoding and interpreting their data.