Together with Space10 we investigated the treatment of sensitive personal information in AR applications, designing and building a feature which allows users to mask this information by choosing different levels of abstraction.
Within this context our goal was to design and built a feature which allows users to anonymize this information, visually and technically. This feature was only one part of a broader research and design project, aiming at creating a trustful relationship between users and companies, across digital products.
Using common computer vision techniques allows users to select and adjust the abstraction of books, documents, faces, people, windows and doors, before any data leaves their phones. This process is deliberately integrated into the main interface, elevating privacy controls from sub-menus to being an accessible main interaction. The aesthetical integration alongside a short feedback loops are key to making these controls as frictionless as possible.
Besides working on the technical implementation, my main focus was on designing the visual language which:
- • aligns with IKEA’s overall domestic visual expression
- • keeps abstracted areas in visual harmony with surroundings
- • abstracts information sufficiently
- • is resource efficient to be run alongside detection on mobiles
- • fast to render on a variety of devices
Especially in AR people rarely think of themselves in the picture, yet they always are. To get a better understanding of how people would ultimately accept such a feature, I prototyped a system that allowed people to see their abstracted selves and react to it. This process ultimately shaped the final visual treatment.
Private Collection shows that treating people's data with respect does not exclude the use of intelligent AR applications in the home. By outlining the appropriate technical infrastructure we demonstrated an approach to foster more trustful relationships between people and service providers through digital interfaces.