Jordan Wirfs-Brock
University of Colorado, Boulder, Boulder, CO, USA
Music streaming services collect listener data to support personalization and discovery of their extensive catalogs. Yet this data is typically used in ways that are not immediately apparent to listeners. We conducted design workshops with ten Spotify listeners to imagine future voice assistant (VA) interactions leveraging logged music data. We provided participants with detailed personal music listening data, such as play-counts and temporal patterns, which grounded their design ideas in their current behaviors. In the interactions participants designed, VAs did not simply speak their data out loud; instead, participants envisioned how data could implicitly support introspection, behavior change, and exploration. We present reflections on how VAs could evolve from voice-activated remote controls to intelligent music coaches and how personal data can be leveraged as a design resource.
https://doi.org/10.1145/3313831.3376493
The ACM CHI Conference on Human Factors in Computing Systems (https://chi2020.acm.org/)