Facial Recognition: Understanding Privacy Concerns and Attitudes Across Increasingly
summary
Study uses an Android app to run a 10-day experience sampling with 123 participants, sending location-triggered prompts plus evening surveys, yielding ~3,800 text responses and 10 follow-up interviews. Researchers coded responses inductively (two coders resolving discrepancies) across 15 real-world scenarios in four categories. Key findings: 9% explicitly oppose demographic profiling, ~33% worry about misidentification, 110 participants report bias concerns, ~70% raise privacy risks (surveillance, unwanted identification, nonconsensual disclosure), and recommendations focus on transparency and user control.
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