From open data portals to speed cameras, practical digital tools are reshaping city services — and oversight needs to catch up.
- Despite its roots in corporate sales efforts, the lasting appeal of smart cities lies in their focus on efficiency, data-informed governance and better outcomes for residents, not flashy gadgets.
- As AI becomes embedded in government operations, experts emphasize the need for transparency to avoid reinforcing surveillance or inequality.
- True progress in smart cities depends less on acquiring new tools and more on coordination, long-term political commitment and ensuring residents experience tangible benefits from digital systems.
Smart cities started as marketing jargon to sell tech tools. Over the last 25 years, “smart city” has evolved into something quieter but more powerful.
Civil servants and their partners are using hardware and data science to improve everyday life, often in its physical form. Far from the vicious partisan battles inside the federal bureaucracy, some in state and local government continue pursuing efficiency in humdrum functions, from online permitting to red-light cameras to sensors monitoring infrastructure.
The term “smart city” has always reflected a mix of the snazziest software and hardware available at the time, such as websites and screens in the 1990s, big data and mobile devices in the 2000s and sensors and solar energy more recently.
Now, it’s all artificial intelligence. Microsoft released this week guidance on using AI for infrastructure planning, the same day Brazilian officials shared an air pollution tracking system.
“GenAI is becoming embedded across core government functions,” the trade group NASCIO put it this month. “The future is in citizen services.”
It’s a good time to remember that the entire smart cities concept proliferated as a sales tactic for government contractors.
The origins of smart cities
The phrase “smart cities” first surfaced in academic writing in 1999, evaluating how Singapore was investing in technology to improve citizen services. The same year, a consultant introduced the term “internet of things” to describe how declining costs in cheap tools (like RFID chips) could interact with digital tools and online systems to make smart decisions.
The two terms — “smart cities” and “internet of things” — evolved together, commonly championed by consultants and contractors selling stuff. Sometimes addressing real problems too. Around the same time, experiments in “digital cities” — like Amsterdam’s pioneering project in 1994 — hinted at what was coming. By the late 2000s, corporate campaigns such as IBM’s Smarter Planet and Cisco’s Smart+Connected Communities were selling mayors a vision of high-tech dashboards and sensor-laden streets. It was, in many ways, a marketing push to sell governments new infrastructure.
As urban theorist Michael Batty and colleagues argued in 2012, the original smart city vision that excited civic doers was less about gadgets and selling than about complex systems working in concert, such as transport, utilities and governance linked by digital feedback loops.
This balance of marketing and solutions has stuck, because underneath the hype was a practical truth. Cities run on systems, and software, data standards and digital tools can help those systems work better.
What does the term ‘smart cities’ mean today?
Though internet-enabled software was never far, “smart cities” have always implied a certain physicality: wiring up the streets, sidewalks and other stuff that make up a place.
Along the way, marketers found lots of places to sell government stuff — according to one popular theory, a major contributor to the bloated budgets of American infrastructure projects is reliance on consultants.
Anthony Townsend’s 2013 book Smart Cities argued these systems require good people as much as good technology. “Civic technology” advocates have worked to center resident outcomes.
Examples include: Boston’s 2015 CityScore, which aggregated dozens of performance metrics into one public number; Los Angeles pioneering the open-source Mobility Data Specification in 2018 that lets cities regulate scooters, bikes and potentially driverless vehicles in real time; and Seattle’s current alliance with the Open Mobility Foundation to pilot a system to link 911 dispatch data directly to robotaxis so they reroute around emergencies instead of blocking first responders.
Even the Pittsburgh city government is using design thinking strategies to solve a flaw in garbage collection, a kind of example, as data crunching was involved.
Way back in 2011, Technical.ly collaborated with city leaders to release OpenDataPhilly, an early platform of data releases — which earned us plenty of criticism for crossing journalistic lines, but was part of a national movement. City governments brimmed with eager civic ambassadors working to better collect, analyze and implement the insights from data.
Most recently, the City of Philadelphia has expanded automated speed enforcement with cameras — which challenges my personal opinions on security but certainly is data-backed. A years-long pilot on one major thoroughfare slashed speeding by more than 90% and cut serious crashes.
These are high-quality examples, but there are low-quality alternatives, too. Rob Kitchin warned a decade ago that “real-time cities” risked overwhelming policymakers with too much raw data unless paired with clear strategies for governance and accountability.
As I told a class of Ivy League urban design undergraduates recently: A smart city isn’t about whizzy technology. It’s about efficient processes that get better outcomes for constituents.
AI and automation could make these systems more powerful — or more dangerous — depending on how they’re deployed.
Smart city standards take hold
International groups like the OECD now describe AI in cities as a test case for balancing innovation with trust, urging governments to pair experimentation with transparency and public oversight. Researchers caution that the same tools for access (everybody gets a chatbot!) can also deepen inequities or enable surveillance if left unchecked.
As with past waves of “smart” innovation, the opportunity isn’t the technology itself — it’s how public servants and their partners choose to use it.
It’s no coincidence that “smart city” conversations have mostly lived at the state and local level. That’s where most service delivery actually happens — and where small but meaningful experiments can scale.
The point is simple: Many cities already have the technology they need. The real work is coordination, sustained political support and ensuring residents see the difference.
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Autor(en)/Author(s): Christopher Wink & Katie Malone
Dieser Artikel ist neu veröffentlicht von / This article is republished from: Technical.ly, 31.10.2025
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