New research published in AI & Society and co-authored by DSPI MSc student Samuel Johnson examines how people understand and respond to Quantified Self (QS) technologies such as fitness trackers, smartwatches, and mood-tracking apps. Alongside Dr Glen Billesbach from the University of Florida, he analyses critical perspectives on self-tracking technologies and proposes a new approach to engaging with them.
QS technologies collect data about the body or everyday behaviours and are widely credited as helping users to improve mental, physical, and emotional health. However, these technologies often come with assumptions. For example, smartwatches analysing sleep cycles rely on default ideas of what constitutes a ‘good sleep’, setting goals and determining what improved sleep looks like. Although this data can be useful, users often accept this data passively instead of actively exploring the reasoning behind the scores.
By prioritising self-interpretative freedom, individuals can make sense of the data on their own terms, enabling them to gain insights and make informed decisions rather than simply accepting information without any engagement.
Research findings
Self-tracking methods vary in technological advancement. However, the researchers emphasise that users of QS technologies should actively exercise self-interpretive freedom to ensure that these technologies support, rather than replace, their ability to make choices, act intentionally, and shape their own lives.
The authors stress that users play a key role in making sense of their own experiences. This could be through talking with their peers and considering their surroundings and emotions. While scores can be useful, they can also take away some of the user’s ability to understand themselves in relation to their data.
“Our research shows that the main challenge facing society is how to effectively embrace technological advancements while sustaining our interpretive faculties,” commented Samuel Johnson. “QS practitioners need neither blindly surrender to self-tracking technology nor lose their humanity when deploying it.”
Research recommendations
The study suggests that the idea of self-interpretative freedom should guide both the design and the use of QS technologies. Users are encouraged to remain mindful of their own interpretations when engaging with the data, while designers should incorporate this principle into future technological development.
The researchers identified opportunities for future work, including exploring the policy implications of QS technologies and conducting in-person discussions to better understand people’s lived experiences with self-tracking tools.
Mr Johnson is currently completing an MSc in Comparative Social Policy at DSPI, with his thesis examining the compliance of street-level bureaucrats. His supervisor, Dr Dirk Witteveen, commented: "It’s remarkable to see a student publish research so early in their career, and equally impressive that it grew out of a side project."
Read the research in full in AI & Society
