Unboxing the Algorithm: Designing an Understandable Algorithmic Experience in Music Recommender Systems.
Year: 2021
Type: conference-paper
Abstract: After decades of the existence of algorithms in everyday use technologies, users have developed an algorithmic awareness, but they still lack the confidence to grasp them. This study explores how understandability as a principle drawn from sociology, design, and computing can enhance the algorithmic experience in music recommendation systems. The preliminary results of this Research-Through-Design showed that users had limited mental models so far but had a curiosity to learn. Further, it confirmed that explanations as a dialogue could improve the algorithmic experience in music recommendation systems. Users could comprehend recommendations the best when they were easy to access and understand, directly related to user behavior, and when they allowed the user to correct the algorithm. To conclude, our study reconfirms that designing experiences that help users to understand the algorithmic workings will make authentic recommendations from intelligent systems more applicable in the long run.
Authors: Anna Marie Schröder, Maliheh Ghajargar
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W3203087752