Brutus is an artificial intelligence bouncer that compares the appearance and behaviour of a club guest to a set of preferences, enabling the owner to curate events in an efficient way. Deviations of a guest’s appearance and behaviour are accumulated in the entry bill, making it obvious how well they are a fit for today’s event and allowing them to compensate for any discrepancy.

Our goal is to imagine and discuss how the profession of a doorman might be altered through AI within the next 20 years. To have an effective means of discussion to illustrate the scenario further we designed a product prototype for people to experience.

Guest Experience

In 2038 Brutus will be at an accessible place in front of clubs, where guests can receive their entry tickets after they are being evaluated by Brutus.

Step 1
Capture Guest

Before entering the club guests will have to walk up to Brutus and press the large button on the front side, Brutus will capture the person visually as well as the behaviour of the person towards Brutus.

Step 2
Analysing Face

Brutus will assess the guest’s behaviour, looks, gender, values and determine how well a person meets the configured settings of the club owner and the current crowd inside the club.

Step 3
Printing Ticket

Each guest will receive a ticket with a picture on it containing all compensation fees as well as the base entry fee.

Owner Experience

The owner of a club has complete control over the appearance of the guest’s who can enter the club as well as their attitude and mood. With additional training, Brutus constantly improves in selecting the perfect crowd to enable the vision of the club owner.


We got reactions to our prototype from a large number of people at the Copenhagen Maker Festival. People reacted a bit disturbed at first by being assessed by an artificial intelligence. But on second thought it raised some interesting and relevant questions in our participants. What are the criteria? How do the criteria differ from the criteria a human bouncer has? Which is better a human or a machine? How much does the machine know about me? How might the criteria evolve in the future with more data?

The ticket listing all the fees soon started a competition on who would get the better results from the machine amongst the guests of the maker festival.
I don’t think this job can be done by AI anytime soon, it’s so much about assessing people not just on a visual level and to ensure you let the right people in order to have a good night for all guest’s. Bouncer at the Hive


We got the brief to choose a profession and develop a speculative scenario to show how this profession might change within the next 25 years. After choosing the profession bouncer as a profession, we quickly develop some ruff senarios and went out at night to talk to actual professionals about how their work, what skills are needed and how they think their profession will change in the future.

Research at Hive
Developing Scenarios
I can not tell from a static image if I would let someone in or not it’s not the dress code which is most important. Bouncer at the Hive
I try to assess if someone’s behaviour is right for the event and also to make sure the person is not looking for trouble. Bouncer at the Hive
Sometimes I sent someone away just to see the reaction if the person is cool with being sent away I let them in. Bouncer at the Hive


From our initial research, we started to build prototypes with paper and cardboard and gradually increased the fidelity.

Our final prototype consists of an acrylic case, with a Raspberry Pi, Arduino, camera, thermal printer, several leds, a button and an iPhone as a screen. When the button is pressed we use the Microsoft Cognitive Service API to recognise facial features, age, makeup and mood. The response from the API is used to calculate the fees accordingly and finally and print a ticket.