The brief of this project challenged us to conduct research into the current state and direction of privacy technology, data collection methods and customer attitudes to data collection, in order to predict a future data privacy scenario (specifically set in 2040). This design method encourages sustainable and long-term design solutions that tackle up-coming issues before the negative impacts have affected society. Having read a number of papers on PETs (privacy enhancing technologies) and the psychology of data protection, we developed a plausible future scenario for the state of data collection in 2040. We talked to a member of the Information Commissioners Office (ICO - the U.K.’s independent body to uphold information rights), who validated our future scenario as a likely outcome of the current direction. We finally developed 3 goals to lead our project system solution and confront the issues present in our future scenario, outlined below.
1. Understand
The system should help the user understand the current state of their data privacy, by showing them how much of their data is leaking from the home, and which devices or services are responsible.
2. Control
The system should allow control of what data can and cannot leave the home - controlling each of the user's individual devices privacy settings with a single action, based on their current activities.
3. Minimise
The system should minimise the quantity and richness of data leaving the home. It should complete requests locally wherever possible - allowing for some of the home’s utility to be maintained during a detox.
We created a PET system that allows the user to block categories of data from leaving their home by activating a number of 'Privacy Modes' which range from 'All on' (all data can enter and leave the house) to 'Local Only' (only local devices within the home can send and receive data). The user can change between modes using a VUI (Voice User Interface) and the physical IoT touchpoint called the Opaque Dial. The dial lets the user know what devices and utility have been sacrificed in order to block the data. Users can visually understand their data privacy through the 'Privacy Metric' - a number that corresponds to the volume and importance of the data that is being transfered in and out of the home. The 'Data Bubble' visualisation tool supports the Privacy Metric, allowing users to see at a glance what category of data is most jeopardising to their privacy. In this way, the user can understand, control and minimise their data exposure, whilst seeing how it affects their home utility. All team members were influential across the project, but my specific focus was centred on the development of the visualisation tool and Privacy Metric.
A number of supporting elements create the Opaque system: a flow chart was created to demonstrate how incoming data moves through our solution, a system diagram outlines how Opaque fits into the data process that devices use to provide utility and an online demo illustrates how the system works in the context of an example 2040 house (linked below). These aspects are briefly outlined below, and can be viewed in more detail in the PDF above.
