Seeing through Things:
Exploring the Design Space of Privacy-Aware Data-Enabled Objects
Increasing amounts of sensor-augmented research objects have been used in design research. We call these objects Data-Enabled Objects, which can be integrated into daily activities capturing data about people’s detailed whereabouts, behaviours and routines. These objects provide data perspectives on everyday life for contextual design research. However, data-enabled objects are still computational devices with limited privacy awareness and nuanced data sharing. To better design data-enabled objects, we explore privacy design spaces by inviting 18 teams of undergraduate design students to re-design the same type of sensor-enabled home research camera. We developed the Connected Peekaboo Toolkit (CPT) to support the design teams in designing, building, and directly deploying their prototypes in real home studies. We conducted Thematic Analysis to analyse their outcomes which led us to interpret that privacy is not just an obstacle but can be a driver by unfolding an exploration of possible design spaces for data-enabled objects.
Research through Design
Bottom-Up Design Space Exploration through Toolkit
Results & Contribution:
18 Connected Open Toolkits
18 Working Home Observational Camera Connected Systems
5 Design Aspects for Design Space of Privacy-Aware Data-Enabled Object: Form, Observational Perspectives, Interaction of Data Capturing, Notification of Data Capturing, and Data Processing and Mapping.
Identify Data-Enabled Object Concept and its Related Design Challenges: Engagement, Empowerment, and Enactment.
Introduce Controllable Intervention: Many insights and reflections would not have happened without exploring privacy in real life through a designerly practice. Even if co-design with participants can help researchers understand privacy requirements before implementing or deploying data-enabled objects, this understanding will always be approximate. The crucial point is that such an intervention must be controllable by the residents in the home in terms of its privacy impact. This means that, during the explorations, all home participants could reject data collection and redact personal data at any point in the studies and could do so based on informed privacy choices.
Identify Privacy as a Driver: Privacy design seems to be often interpreted as a design that ultimately constrains the experience of users (or participants). However, our explorations show that participants are not always in the opposite position and can become collaborators or data curators, capturing and sharing unexpected data to the data-enabled objects.
Collaborators & Acknowledgement:
Mathias Funk (supervisor, engineering), Rung-Huei Liang (supervisor), Lin-Lin Chen (supervisor), Yi-Tang Chiang (engineering), Yi-Ching (Janet) Huang (researcher).
Yu-Ting Cheng, Mathias Funk, Rung-Huei Liang, and Lin-Lin Chen. 2022. Seeing Through Things: Exploring the Design Space of Privacy-Aware Data-Enabled Objects. ACM Trans. Comput.-Hum. Interact. Just Accepted (December 2022). https://doi.org/10.1145/3577012
The following presents a brief introduction and research photos of the project. More details can be seen in my publication or contact me for further information.
Ubiquitous sensing and massive data collection allow smart products, such as Amazon Echo, Google Home, or Apple HomePod, to quantify human behaviour and thereby act intelligently by anticipating and responding to people’s needs at least, that is the promise.
Parallel to these commercial developments, researchers have also developed sensor-augmented research objects such as Connected Resources, Connected Baby Bottle, and Morse Things to capture aspects of everyday activities in minute detail, shedding a new light on design ethnography.
We call these sensor-augmented research objects, Data-Enabled Objects. Data-Enabled Objects because they capture data about people’s natural interactions in the environment and with the objects. The need to collect data stems from understanding the everyday life context before and during designing for that context. These sensor-augmented research objects are purposely-built instrumented objects with finished product quality to be integrated into people’s daily lives to capture, store and share data from the field.
MOTIVATION & CHALLENGES
Data-enabled objects are computational devices with on-board memory and processing capabilities. While they are capable of capturing long-term data consistently and remotely without fatigue, they can be insensitive to the context of that data and to changes taking place within that context. Unless explicitly programmed, they cannot adapt their data collection mechanisms to react to different situations. Data-enabled objects can act as a kind of black box that continuously and inconspicuously absorbs personal data, including bio-signals and other health-related data, detailed whereabouts, and personal preferences.
This project aims to explore design space of privacy-aware data-enabled objects concerning the balance between individual privacy and ethnographic purpose.