How might we...
...create a simple and intuitive way for people to control their personal information that also helps educate them on why they are shown certain content?
People need to be able to adjust their interests and preferences gradually on personalised services, understanding how algorithms are used by showing its effect. How can services rethink personal data control by shifting towards progressive disclosure?
Loco is a fun image-sharing mobile application that allows people to share images, videos and AR masks directly to friends via messages or to an ephemeral feed made up of people near them and selected brands. Part of loco’s popularity is the uncanny ability to suggest content to people that they are likely to enjoy. Loco takes account of a great many complex signals for delivering a “magical” experience while also seeking to provide transparency and control.
In order to provide the service, Loco is powered by some of the following data:
People say that they expect to be well informed and have access to intuitive controls. However, the reality is that there may be expectation but actual interest in taking control of personal data is much lower.
How might we...
...create a simple and intuitive way for people to control their personal information that also helps educate them on why they are shown certain content?
Giving control, without having to leave the context of the feed, allows people to take control and customize their data experience with little effort. When browsing through their interests, they can navigate to a data dashboard or settings area for more advanced controls if they wish.
In the data settings area, people can interrogate the genesis of the data by interest. They can see how the app created the ranking and control the data that will be used in the future.
Loco is transparent about settings and actively asks people to decide whether they would accept Loco using the data for other interests.
How might we build on Loco’s ideas to…