The study does not examine Flock cameras directly. Instead, it draws its evidence from two other contested urban technologies: facial recognition systems in Portland, Oregon, and autonomous vehicles in Tempe, Arizona. By tracing how those communities confronted the promised benefits of new tools against risks to privacy, equity, transparency and civil liberties, the researchers built a framework that applies directly to the current Flock controversy. The choice of cases was deliberate. Both technologies arrived in cities amid claims of improved safety and efficiency, and both raised documented concerns about bias, accuracy and the control of sensitive data. The paper, co-authored by Farah Najar Arevalo of Arizona State University and Devon McAslan of Chalmers University of Technology in Sweden, was published on 18 August 2026 under the title Public value mapping in the smart city: Assessing emerging urban technologies.

Timing matters in this research. Miller notes that the technologies investigated in the study were emerging slowly when the work began, before and during the COVID-19 pandemic. Since then, the pace of adoption has accelerated dramatically. These technologies, like facial recognition and Flock, were emerging in baby steps then, and the pace has only ramped up, Miller observes. That acceleration places municipal governments in a difficult position. Cities and towns face pressure from technology companies and law enforcement agencies to adopt systems that promise gains in public safety or operational efficiency, often without the staff or technical expertise needed to understand the full range of trade-offs involved.

That capacity gap is central to the problem the study identifies. Many local governments do not have the capacity or sometimes the expertise to think through how emerging technologies might affect a whole set of values that the community may have, Miller explains. A city might adopt a surveillance system to fight crime, for example, without fully considering its implications for privacy, freedom of expression, racial equity, or how the information it gathers could be shared beyond the agency that collected it. In practice, procurement decisions are frequently made department by department, with police or public works offices evaluating a tool narrowly on its stated function while the broader civic consequences go unexamined until a controversy erupts.

The Portland case illustrates those tensions in concrete detail. Researchers found that facial recognition cameras could offer public-safety benefits, but there was significant uncertainty about the extent of those benefits in an urban environment. At the same time, there were documented concerns about racial and gender bias in the technology, questions about its accuracy, and a lack of transparency about how data would be collected, managed and shared. The uncertainty cut both ways: the promised gains could not be verified, while the potential harms were grounded in documented evidence about how facial recognition performs across demographic groups. That asymmetry proved decisive in how the community weighed its options.

Ultimately, Portland’s response was to ban facial recognition technology in public spaces. The outcome carries a broader lesson for cities confronting Flock cameras and similar systems: technologies marketed as inevitable can be constrained when the community evaluates them through the lens of public values. The ban did not emerge from a single moment of opposition but from a process in which residents and officials examined what the technology was designed to do and what else it might change. That distinction, between a tool’s intended purpose and its full range of effects, is the analytical core of public value mapping and the reason the researchers believe it generalizes across technologies and jurisdictions.

Miller is careful to caution that public value mapping is not a scorecard that automatically tells a community whether to approve or reject a technology. Instead, it is intended to bring government officials and residents together to identify what they value, examine potential benefits and harms, and consider what policies could produce a better outcome. The method treats values such as privacy, equity, transparency and civil liberties not as obstacles to innovation but as legitimate design criteria that a technology deployment either respects or violates. In that sense, it resembles a structured civic deliberation more than a technical audit, and it deliberately shifts the conversation from the artifact itself to the governance choices surrounding it.

Applied to the Flock debate, the framework suggests asking a series of questions before debating the pros and cons of the cameras themselves. What public safety problems actually exist in the community? What privacy sacrifices are people willing to accept? Who controls the data the cameras generate? How long is it retained? Who can access it? And, crucially, do the answers align with the community’s stated values? These questions expose the fault lines that often remain hidden in polarized debates, where opponents and supporters talk past each other about the device rather than about the data governance regime built around it. The study asserts that those conversations should take place across government silos and with the public before a controversy erupts, not after.

The stakes of getting this process right are considerable. License plate reader networks create searchable databases of vehicle movements, and controversies over data-sharing agreements between municipalities, private companies and out-of-state law enforcement agencies have made Flock cameras a national flashpoint over privacy, surveillance and policing. A framework that forces explicit answers to questions of retention, access and control could change how such contracts are negotiated, disclosed and audited. It could also reshape the market itself, since vendors respond to the procurement standards that cities set. If communities demand transparency about data flows as a condition of adoption, the terms of deployment shift from a take-it-or-leave-it pitch to a negotiated public arrangement.

Miller says the goal is not to reject innovation but to approach it deliberately, ensuring that technological advancements do not come at the expense of values a community is trying to protect. Technology, he argues, is not destiny: communities can have a say in how it is adopted, regulated and used. We shape technologies every day in all sorts of ways, Miller adds. The question is, can we do so with more intention? For hundreds of cities now weighing Flock cameras, facial recognition and the next wave of smart-city tools, that question may define whether emerging surveillance infrastructure is governed by default settings written elsewhere or by the deliberate choices of the people it watches.

Subject of Research: Public value mapping for assessing emerging urban surveillance and smart city technologies

Article Title: Flock cameras put cities at a crossroads. New research offers a roadmap

Article References: Flock cameras put cities at a crossroads. New research offers a roadmap. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: Flock cameras, public value mapping, surveillance, facial recognition, automated license plate readers, urban technology governance, privacy, civil liberties, smart cities, Portland, Tempe, technology policy