Feastopolis is a restaurant using users' diet behaviour to generate dishes. The goal is to advocate a data-informed lifestyle that empowers people to be healthier and conscious about their daily behaviour with a sense of exploration of food.
In 2019, Dentsu international published a report stating that 45% of the people around 22 countries are decreasing their digital footprint and 59% of the people don't trust businesses for protecting their data. In response to that, new regulations are happening around the world. Having more regulations means more fines. The regulations, however, are only there to protect, but fall short in empowering people with useful information about their life. There needs to be new services between people and data to shape healthy relationships.
The first hypothesis was drawn under the impression that the insecurity of how people's data circulates is the primary cause of the distrust about data. The prototype attempt is an app created especially for testing the user feedback from people. The result was not great as people were not engaged in the process. Something was missing. The second hypothesis is that, besides the points from the first hypothesis, a good experience and purpose could make data collection more successful. The second prototype is a Secret-Santa-ish Potluck. In this potluck, every participant will have to cook for another person in secret. In return, someone else will cook for the participant. The result is astonishing. People were very engaged in creating a dish that others may like. This information about the everyone's preferences and tastes flows within the group naturally.
The goal is to scale and digitise this environment. Essentially, the design will not simply be a service but also promote a lifestyle with people's daily life decisions influenced by good information. Promoting a lifestyle is complicated. The service will need to use a service/sales funnel to help integrate users into the service slowly. The start of the service funnel needs to be something manageable, something people do a bit differently every day, something that brings people joy with a sense of exploration. The design turns to the concept of food and diet because of this. The problem statement is thus "How might we promote a 'data-driven lifestyle' that is closely related to good information through food consumptions?" This is where Feastopolis sits—a restaurant using data to give a good dining experience—and in the process, introduce how a user-owned data model could benefit them.
Though there is no menu, it is not entirely menuless but instead a sheet to choose what people like and dislike. To order food, people can choose between the ingredients they like, something from the past that you had with Feastopolis or something completely random to enjoy the excitement of discovering new flavours. Flavour Palette, the visualised algorithm, will be accessible for users to see their diet journey in real-time. The palette will power the random dish suggestions. It is just like Tinder, but here people are dating the dish. When the user base starts to accommodate this data-driven diet style, the focus will be shifted from the restaurant towards activities made possible thanks to the Flavour Palette. The Flavour Palette becomes the main product of the service. The platform will open for other restaurants to join. The better the utilisation of the palette, the more powerful the service proposition will be.
When a strong user base emerges, Feastopolis will start allowing users to complete a self-monitoring diary while the outside collaborators will help us build ways to measure the impact of the data. With their tools, the meaning of the data becomes apparent, which will significantly help the platform thrive. In return, outside collaborators will have the anonymous data to help their organisation to improve. The Feastopolis restaurant is still very important. It is just like an Apple store now, which promotes the Flavour Palette. The core service is to have people see how data works and enjoy the benefit of good and transparent data ownership. The service promotes the idea of people-owned data. It tells its users why their data matters and the benefits of it. Compared to the more mature platforms such as Facebook or Google, people will learn how every piece of their information matters—building a healthier environment data-sharing platform.
