TrustLAB Translates - Balancing Privacy and Trust: Why Citizens Welcome Smart City Cameras in Theory but Resist Them on Their Street
Smart city cameras are becoming part of the urban furniture. From traffic lights that read the flow of cars to sensors that nudge signals in response to congestion, video-based traffic sensors (VBTSs) are quietly reshaping how local authorities manage roads, air quality and public safety. Yet, unlike a smartphone app or a contactless card, citizens cannot opt out of these systems. They simply walk, cycle or drive past them. That uneasy fact sits at the heart of our recent paper, which asks a deceptively simple question: under what conditions are people willing to accept video-based surveillance in their cities?
Building on previous work on trust in government technologies and the privacy calculus that underpins it, our latest paper, published in Government Information Quarterly, looks at how privacy concerns and trust in government shape the social acceptance of VBTSs. The findings suggest that acceptance is not a single judgement but two related ones – a general view of the technology in cities and a local view about its use in one’s own neighbourhood – and that these two views can pull in surprisingly different directions.
Smart Cities, Passive Cameras and the Limits of Choice
Traditional models of technology adoption assume that people choose whether to use a tool, weighing up its usefulness and ease of use. That logic does not travel well to smart city cameras. VBTSs operate as fixed urban infrastructure. They run continuously, often without explicit consent, and most citizens are not in a position to negotiate where they are placed or how the data is used. The decision-makers are local authorities; the people affected are everyone who passes through the camera’s field of view.
Cases from across jurisdictions illustrate the resulting tensions. Lawsuits against automatic licence plate readers in the United States, the suspension of San Diego’s smart streetlight programme amid concerns about police surveillance, and a Virginia ruling that compared continuous camera coverage to a GPS tracking device all point to a gap between technical capability and public acceptance. In this kind of environment, asking whether people will adopt a camera is the wrong question. The more useful question is whether they will tolerate, support or resist its presence.
To make sense of that question, we draw on Privacy Calculus Theory. The theory proposes that individuals weigh the perceived benefits of disclosing or sharing information against the perceived risks. In smart city settings, that calculation is rarely conscious. People may not know a sensor is there, what it captures or how its data will be used. The trade-off becomes a tacit, after-the-fact judgement shaped by trust in the institutions deploying the technology and by the perceived appropriateness of the data flows involved.
What We Did
We tested these ideas with an online survey of 1,920 adults living in the United States. Participants reported their views on a set of validated constructs: their general propensity to trust technology, their perception of the need for government surveillance, their reading of the government’s motives, and how intrusive they felt VBTSs were. We then examined how these factors fed into trust in the government’s implementation of the technology, into privacy concerns, and into two distinct outcomes – general acceptance of VBTSs across cities and local acceptance in one’s own area.
Where Trust Comes From
Several findings stood out. Citizens who tend to trust technology in general were also more likely to trust the government’s use of VBTSs, although the effect was modest. The strongest drivers of trust were perceptions of why the technology is being used and whether surveillance is seen as necessary. When people felt that local authorities were motivated by genuine public benefits (e.g., reducing congestion, improving safety, supporting cleaner air) their trust in the implementation rose substantially. When they perceived the cameras as unnecessarily intrusive, trust fell.
This pattern is consistent with a broader idea about contextual integrity: privacy is not violated only when data is collected, but when it flows in ways that breach the reasonable expectations of the people affected. A motorway camera that counts vehicles to ease congestion sits comfortably within those expectations. A residential camera that quietly feeds data into law-enforcement systems does not.
Two Acceptance Pathways, Not One
The most striking result concerns the difference between general and local acceptance. Trust in the government’s implementation of VBTSs had a clear positive effect on general acceptance. People who trusted local authorities to use the technology responsibly were comfortable with the idea of cities adopting it. When we looked at acceptance in their own neighbourhood, however, the relationship reversed: higher trust did not translate into higher local acceptance.
Privacy concerns, by contrast, dampened acceptance at both levels, but their effect was much stronger locally than generally. In other words, abstract endorsement of smart city cameras coexists with localised resistance – a kind of “yes, but not on my street” pattern. Once a sensor moves from a city-wide idea to a fixture on a familiar road, citizens start to weigh the privacy implications more carefully and less generously.
We see two plausible reasons for this. First, local acceptance often takes shape only after a system is operating and its practical benefits are visible, but VBTSs are designed to be unobtrusive and may never become visible to residents at all. Second, local deployments frequently happen with limited consultation, which leaves citizens with little sense of agency over a technology that nevertheless watches them every day.
What This Means for Local Authorities
For practitioners, the findings underline that public confidence in smart city technologies cannot be assumed from headline approval ratings. Cities can have broad public support for VBTSs in principle and still face determined resistance to specific installations. Three implications follow.
First, motives matter, and they need to be communicated clearly and consistently. Vague references to “innovation” or “smart cities” do less work than concrete, locally relevant explanations of what a camera is for, what it captures, how long data is kept, and who can access it. Independent oversight reinforces these messages.
Second, the local pathway requires its own engagement strategy. Online dashboards, neighbourhood workshops, living-lab pilots and pre-deployment impact assessments help residents see how a system will operate before it appears on their street. Where possible, citizens should have meaningful input into the rules around data use, not just retrospective notification.
Third, privacy-enhancing design is not a constraint to be tolerated but a route to legitimacy. Edge processing, anonymisation, strict purpose limitation and clear retention policies reduce the perceived intrusion that drives resistance. Pairing these technical measures with citizen review boards and third-party audits gives residents reasons to believe that the system will stay within its stated remit.
A Wider Lesson About Trust in Public Technologies
Beyond the specifics of traffic cameras, our study points to a broader truth about how citizens relate to government technologies that watch them. Trust is not a single resource that can be banked and spent across every deployment. It is shaped by perceptions of motive, necessity and intrusion, and it operates differently when the technology feels distant than when it feels close. For local authorities investing in smart city infrastructure, the practical task is less about persuading people that the technology works and more about demonstrating that it is being used in ways that are proportionate, transparent and answerable to the communities living alongside it.
Read the full paper here: Guazzo, G. M., Rosati, P., Troisi, O., & Lynn, T. (2026). Balancing privacy and trust: Social acceptance of video-based traffic sensors in smart city initiatives. Government Information Quarterly, 43, 102099. https://doi.org/10.1016/j.giq.2025.102099
Authors: Dr Gianluca Maria Guazzo, Marie Curie Postdoctoral Fellow at the University of Galway, and Prof Pierangelo Rosati, Professor in Management at DCU Business School and Funded Investigator at Lero, the Science Foundation Ireland Research Centre for Software.
Photo by Siarhei Horbach on Unsplash