Ayobi, A;
Marshall, P;
Cox, A;
(2017)
Self-Experimentation and the Value of Uncertainty.
In:
CHI EA '17: Proceedings of the 2017 CHI Conference Extended Abstracts on Human Factors in Computing Systems.
ACM: CHI'17 workshop: Digital Health and Self-Experimentation: Design Challenges and Provocations, Denver, CO.
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Abstract
Self-tracking technologies have a great potential to transform the ways people understand and manage their personal health and wellbeing. However, studies on self-tracking suggest that people face challenges in gaining self-knowledge because of a lack of scientifically robust self-experimentation systems. In this position paper we focus attention on the value of uncertainty in self-experimentation by drawing on diagnostic tracking practices in multiple sclerosis (MS). In doing so, we illustrate the role of uncertainty and scientific thinking in self-tracking and managing the complex and unpredictable nature of the disease. Based on this understanding, we propose a set of design considerations to motivate discussion of the ways in which the design of future self-experimentation tools could spark scientific thinking and acknowledge uncertainty in everyday life.
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