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PhD Series No. 37.2015
The proliferation of technological enhancements has fundamentally changed the relationship between the individual and technology. One particular change is the increased dispersion of technology in everyday experiences through personalized information technology (IT), such as smartphones, laptops, tablets and wearable technology. This development has brought about the rise of experiential computing, which refers to the “mediation of embodied experiences in every day activities through everyday artifacts that have embedded computing capabilities” (Yoo, 2010, p.213; Jain, 2003). The emphasis is thus placed on the relationship that occurs between the user and technology as the lived experience is mediated to the user through data dashboard. This potentially transformative relationship is both intimate and complex and spurs the research interest, which asks how the user is influenced by the exposure to personal data captured by experiential computing devices and how it alters the perception of personal performance. One type of activity stemming from the dispersion of experiential computing is self-tracking. Self-tracking is a way for the user to capture and measure intimate details of the self, by using IT to collect, index and analyze personal data on life experiences. For example, the user might use an activity tracker, like the Jawbone UP, to gather numerical data on daily step and sleep activity. The exposure to this data may transform or distort the way the user initially perceived the activity by getting a new visual expression of what has occurred. To better understand the user’s reaction and counter-reactions to using experiential tools, this research suggests placing the focus on the user and analyzing it through a behavioral economics perspective. This is done by conducting empirical studies with a mixed method approach. The first study is a field study that investigates the influence on performance and perception by wearing a self-tracking device. The second study is an in-depth interview study that studies experienced self-trackers by exploring further into the perceptions of the user. This dissertation contributes to a deeper understanding of how the self-tracking user is affected by the use of experiential computing devices and the subsequent exposure to personal data. The findings suggest that the user’s analysis steps and sleep performance goes through a complex reflective process after the exposure to data that influences the perception of the initial experience. When this process involves unsatisfactory data, the user will reject the data and adopts coping tactics. The coping tactics are dismissal, procrastination, selective attention and intentional neglect.
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