As the prototype had to be made in a very short timeframe we quickly discussed the user goals and turned them into a low fidelity interface.

As a user, I would like to train how the AI works so that I can ensure it understands my listening habits.

Ken’s primary benefits come from working in conjunction with the smart headphones and wristband, however, it was still important to develop a product that people can use without having to rely on them.

In addition to the smart playlists Ken creates, users can make their own ones based on specific song titles, genres of music as well as filters that can grow your playlist over time.

Users are able to see exactly what data Ken collects about them over time. By digging deeper, they can see in-depth information on their listening habits such as the location, time, data and emotions felt while listening to a particular song.

While listening to a song users can adapt the bass to match your environments background noise. In addition, they can manually train Ken to recognize their listening habits, this helps Ken create smarter playlists.

Using the headphone’s built-in accelerometer Ken measures your posture while you sit and gives feedback to help you improve over time.