Close Encounters: Gauging Residents’ Comfort and Trust Levels with Smart Technologies During “Data Walks”

For this study, I led thirty-two study participants on a 1.5-mile community “data walk” in Long Beach, California, to gain insights into the trust and comfort levels residents experience when encountering smart technologies that track their movements and capture their image. During the walk, study particip­­ants used a custom mobile app to map and photograph each smart technology observed. Participants then responded to prompts intended to gauge their perceptions of various smart technologies including surveillance cameras, public Wi-Fi routers, and license plate readers. The analysis—which relied on theoretical frameworks grounded in cultures of trust, surveillance studies, and contextual integrity—found that study participants are generally unaware of the ubiquitous nature of surveillance technologies deployed by both public and private entities, and they can only speculate on how personal information collected is stored, shared, and analyzed. Volunteers also expressed concern about the discriminatory impacts of smart technologies, particularly those used by law enforcement. The findings advocate for structural change, shifting the burden of personal data protection off users themselves.

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Publication Details

Journal
Surveillance & Society
Published
2025-06-05
DOI
https://doi.org/10.24908/ss.v23i2.16560
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
0.00

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article

Close Encounters: Gauging Residents’ Comfort and Trust Levels with Smart Technologies During “Data Walks”

Gwen Shaffer
Surveillance & Society
Big Data and Business Intelligence
article

Close Encounters: Gauging Residents’ Comfort and Trust Levels with Smart Technologies During “Data Walks”

Gwen Shaffer
article en

Abstract

For this study, I led thirty-two study participants on a 1.5-mile community “data walk” in Long Beach, California, to gain insights into the trust and comfort levels residents experience when encountering smart technologies that track their movements and capture their image. During the walk, study particip­­ants used a custom mobile app to map and photograph each smart technology observed. Participants then responded to prompts intended to gauge their perceptions of various smart technologies including surveillance cameras, public Wi-Fi routers, and license plate readers. The analysis—which relied on theoretical frameworks grounded in cultures of trust, surveillance studies, and contextual integrity—found that study participants are generally unaware of the ubiquitous nature of surveillance technologies deployed by both public and private entities, and they can only speculate on how personal information collected is stored, shared, and analyzed. Volunteers also expressed concern about the discriminatory impacts of smart technologies, particularly those used by law enforcement. The findings advocate for structural change, shifting the burden of personal data protection off users themselves.

Surveillance & SocietyVol. 23(2)
California State University, Long Beach (US)
California State University Long Beach
Openalex Percentile: Top 63%
Big Data and Business Intelligence
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Close Encounters: Gauging Residents’ Comfort and Trust Levels with Smart Technologies During “Data Walks” — Gwen Shaffer · Surveillance & Society (2025) | TGRS Research Map | TGRS