Supervisor:
Enrique Encinas
Music services are leveraging artificial intelligence to enhance personalization, promising users a more tailored listening experience. However, this integration of AI presents a dilemma: users struggle to express their own needs within the framework constructed by AI
algorithms.
Music Bubble and Black Box are main threads I have defined to be the breakthrough of reimaging AI’s role in our music experiences and how future interactions with AI could be. Utilizing a collection of visions and aspirations, I weave the concept with interesting feature extracted and combined from the research, which can be categorized into three motifs: Explore, Extend, Engage.
Exploration stems from a strong desire to learn more about oneself. Concept Vignette is a small-scale representation of a user’s personal music journey through the streaming platform. It illustrates how users utilize music bubbles to discover aspects of themselves, whether driven by curiosity, a desire to share, or simply for fun.
Music, context, and mood interact and influence each other. Expand focuses on pushing off bubble boundaries with real world inputs in many scenarios. Users can select palettes based on their listening habits and music preferences to paint their day with music.
The essence of the palettes are instructions given to AI algorithms, which correct the bias in recommendation results by integrating AI’s understanding of users with their intended goals.
Music carries a wealth of information and is a channel for emotional transmission, which has cultivated many interesting ideas. In the third motif Engage, the scenarios are divided into two types: weak tie and strong tie to showcase potential new games between different relationships brought by music bubbles.
Together, the three motifs create a space for opening up discussion and fostering imagination about highly personalized music experiences and communicative AI services in the future.
Contact
Tianyi Shi / tianyi.shi@stud.aho.no