Seeing through Things: Exploring the Design Space of Privacy-Aware Data-Enabled Objects

TL;DR

This paper investigates how to incorporate privacy considerations into the design of data-enabled objects, specifically sensor-augmented home research cameras, by exploring design spaces through student re-designs supported by a specialized toolkit.

Contribution

It introduces the Connected Peekaboo Toolkit to facilitate privacy-aware design and demonstrates that privacy can be a creative driver rather than just an obstacle in data-enabled objects.

Findings

Privacy can be a design driver for data-enabled objects.

Design spaces for privacy-aware data-enabled objects can be systematically explored.

Student re-designs reveal diverse privacy-preserving approaches.

Abstract

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.