How to Design with Ambiguity: Insights from Self-tracking Wearables

Research Background and Problem

• Identified Issues or Challenges by the Authors: Current self-tracking devices (e.g., fitness bands and activity trackers), while providing individuals with quantifiable data and behavioral insights, often emphasize clarity and standardization in data representation, obscuring the inherent ambiguity in device design and tracking phenomena. This excessive standardization may lead users to overtrust the data and overlook the complex and subjective meanings behind it.

• Why This Issue is Important: Wearable devices influence users' life decisions by monitoring health and behavior, reinforcing the objectivity of data. However, data is not neutral and may contain technical limitations and social constructs. Ignoring data ambiguity in design may cause user stress, anxiety, or misunderstanding. Self-tracking technologies require more flexible design approaches to accommodate the diversity of user needs.

• Research Motivation and Related Work: Twenty years ago, Gaver et al. proposed "using ambiguity as a design resource," aiming to introduce everyday uncertainties into interactive system design to encourage users to interpret based on their own contexts. However, in the field of wearable self-tracking devices, the application of ambiguity design strategies is rare, and research on implementing these strategies as design guidelines is lacking. This study aims to fill this gap by providing mid-level knowledge and concrete cases for design practice.

Solution

• Proposed Method or Solution by the Authors: The authors tested the practical application of ambiguity design strategies through a two-week design workshop. The workshop involved 60 designers tasked with developing self-tracking device designs that inspire data interpretation and self-reflection while addressing identified design issues using ambiguity strategies.

• Innovative Aspects of the Solution: Building on Gaver et al.'s original ambiguity strategies, the authors developed eight new ambiguity strategies tailored to the specific needs and contexts of the self-tracking domain. These strategies not only help designers implement ambiguity in a more specific and actionable way but also expose the issues of over-standardization in device design, reintroducing ambiguity into data representation and device interaction design.

• Implementation Steps and Key Techniques:

  1. Phased Workshop Design Process:
     • Phase 1: Analyze existing devices to identify the absence of ambiguity and related tensions in self-tracking.
     • Phase 2: Review initial ambiguity strategies, select appropriate strategies based on identified tensions, and translate them into design task briefs.
     • Phase 3: Design data representations and explore strategy implementation through low-fidelity and experiential prototypes.
  2. Strategy Development and Induction:
     • Analyze design outcomes (11 concepts) and participants' design processes and reflections.
     • Derive eight domain-specific ambiguity strategies, organized into three main categories: description, omission, and extrapolation.

Research Outcomes

• Specific Outcomes: The authors proposed eight ambiguity strategies applicable to the self-tracking domain:

  • Description strategies: e.g., "Transform uncertain data into sensory aesthetic experiences."
  • Omission strategies: e.g., "Conceal data input-output mappings."
  • Extrapolation strategies: e.g., "Exaggerate system capabilities to reveal its limitations." Additionally, these strategies were organized into three categories (description, omission, extrapolation) as flexible and actionable design guidance resources.

• Advantages Over Existing Solutions:

  • Introducing ambiguity helps address the over-standardization issue in current device designs, making data representation more flexible and meaningful, encouraging personalized interpretation and self-reflection by users.
  • Provides a clear strategy framework for design practice, facilitating the transition from theoretical abstraction to practical examples with greater utility.

• Experimental or Evaluation Results: The 11 conceptual designs from the workshop and participant interviews demonstrated that ambiguity strategies effectively address tensions in self-tracking design, fostering more creative and exploratory device designs. However, designers faced challenges in understanding and implementing ambiguity, particularly in balancing ambiguity with clarity and avoiding excessive guidance on user experience.

• Limitations and Future Directions: Limitations:

  • The study was conducted in an academic setting, where participants' design motivations might have been influenced by course grading.
  • The study did not involve real user testing, so the results have not been validated in practical use.
  • Participants lacked experience in wearable device design.

  Future Directions:

  • Further research on the long-term impact of ambiguity strategies on users, especially how users cope with the difficulty of interpreting ambiguous data.
  • Explore evaluation methods for ambiguity design, moving beyond traditional metrics of usability and efficiency to focus on multi-stability and unintended aspects of user experience.
  • Extend the study to professional designers in industry settings to validate the applicability of the strategies in commercial devices.

Overall, this study provides significant theoretical and practical foundations for applying ambiguity in self-tracking design, showcasing the potential of non-standardized design while calling on the design community to pay greater attention to the openness and complexity of user experiences.