Between Lines: Critically Speculating Futures with Location-Based Recommendation Systems
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Abstract
Location-based recommendation systems are becoming increasingly ubiquitous in the march toward fully tailored user experiences. Applications like Google Maps, Strava, Uber, Hinge, and many others utilize location data as key material for providing contextual recommendations. Rising concerns about usage and misuse of location data have arisen in recent years. I situate this thesis within design’s future-oriented nature, critically speculating possible futures with location-based recommenders. I propose a refinement of current approaches and speculative design for engaging domain experts in co-speculation through the use of tailored, high-fidelity, critical design fiction videos. In this case study, I lay preliminary insights, including a widespread sense of fatalism, self-described lack of agency, and underlying individualist ideologies driving development and deployment of these systems. I also reflect on the process of creating four critical design fiction videos, their use in 11 guided co-speculation sessions, and implications for their use in gathering rich qualitative data, creating space for reflection, prompting stories and personal connection, and unpacking experts' views on complex, wicked problems.
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Thesis (Master's)--University of Washington, 2024
