smart city concept
illustration: Oliver raw

CONTRIBUTOR: Ryan Falconer is not convinced that enough urban tech is sufficiently citizen-driven. He’s got three key concerns that government needs to address.

It’s a brave, new data-driven world. Together, data and data processing potential offer unprecedented insights into all manner of human and environmental conditions and activities. 

They help predict, manage and respond to climate change, healthcare needs and risks, electricity supply and demand, and mobility challenges, among many more issues.

In the mobility sector, there are now so many potential sources of data regarding how, why, when and where passengers and freight are moved, and sophisticated processing tools, we’d be forgiven for wondering why things like congestion remain problems.

We have technology and entrepreneurship to thank for these marvellous means. But the means are not foolproof (despite what we might be able to convince ourselves regarding our technological reach), nor are they available universally. 

They’re also not applied purely for the public good. The tension between what data might tell us, and how it’s really collected and applied, is therefore of great significance in cities in the late 2010s. 

In today’s cities, we can neither be sure what information we cede nor how it’s employed

This article explores concepts of data value, and how means to collate, process and apply data in our urban environments is redefining our civic experiences, for the positive, negative and in the murky middle. 

These issues are important for all users of urban space, because in today’s cities we can neither be sure what information we cede nor how it’s employed.    

In 2008, a Wired magazine article proposed that “big data” was replacing the need to theorise: there’d be no longer any need to ponder causal links, model alternative scenarios, or worry too much about trivialities like probability. AI-boosted processing potential, as well as the weight of data being aggregated, would take the guesswork out of much of daily life.

According to Google’s Smarter Digital City 2.0 paper for Hong Kong prepared by Ipsos, AXA has used machine-learning to predict the likelihood of a driver causing a significant traffic accident with 78 per cent accuracy. 

The closer that statistic tracks towards 100 per cent this seems like a boon for the insurance industry  but maybe not so much for the driver who’s asked to pay an exorbitant premium or is refused coverage.

There are almost 50 billion Internet-of-Things devices in circulation

According to a 2018 article in The Press newspaper, by 2020 there will be more than 50 billion Internet-of-Things devices in circulation, globally including perhaps six billion smartphones. 

Many of us think very little about how much data we are generating, either through having a smartphone or by engaging in some way with these myriad other IoT devices, and how the data are then used. 

Data itself has no face value like traditional currency does. Rather, value depends on someone being willing to pay for the data and how much they’ll offer to outbid others.

Historically, value has been assigned to goods and services from works of art to oxen. More recently, bitcoin and other cryptocurrencies have shown us how markets can apply value to Os and 1s. 

Today, data are often by-products of many activities that we take for granted, including surfing the web and using search engines, making calls on our mobiles and using social media; even using our credit cards, calling an Uber or tapping our public transport smartcard to board a bus. 

A person’s daily digital footprint is generated in increasingly diverse and deep ways. By-products or not, these sorts of data can and do generate value.

We embrace most of the activities yielding a digital footprint because they seem to make our lives easier, satisfying our wishes for convenience, instantaneous gratification, customisation, information and consolidation (for instance, everything at the touch of a button). 

Also, we are bombarded with so many complicated sets of terms and conditions – which is when we have the opportunity to opt in or out – that it’s hard to really understand the consequences of opting in.

For these reasons, maybe we don’t mind giving up immense tracts of data about ourselves either for free or as condition of access, only for it to be used by commercial enterprises to target marketing back at us as part of our “customisation” experience. 

That’s if we really understand what we’re giving up.  

The new norm is that one must be wired to engage meaningfully in urban life – to be unwired is to risk civic irrelevancy as well as foregoing even basic forms of access to essential goods and services. 

This imposition on the public should precipitate much more civic engagement in decision-making relating to the wiring of the urban environment, and much more governmental oversight of how this wiring is used. 

These imperatives should temper the “sizzle” of smarter city (read data-driven and data-harvesting) infrastructure, despite it being in vogue for cities to brand themselves based on how digitally-enabled they are. 

“Smart” sensor and processing technologies can, without doubt, make civic life easier and enable government to deliver services more efficiently and effectively. 

Locally, in Perth, the pioneering (for Australia) application of smartcard technology across the public transport network benefited customers, streamlined a lot of fare payment, and has yielded government with an incredibly powerful network utilisation dataset. 

Regionally, in its Smart Cities in Southeast Asia discussion paper, McKinsey’s Global Institute proposes that smart applications can help cities make moderate, if not significant progress towards satisfying perhaps 70 per cent of the UN’s Sustainable Development Goals. 

Data-driven command-and-control centre, Yinchuan, China.

Yet government needs to apply stringent oversight to the infiltration of privately-controlled devices into the public realm.

These devices may not be designed with malicious intent in mind, but they function typically to gather information on consumer habits and preferences, and, in turn, influence patterns of consumption. 

These objectives don’t align always with the public good. 

Knowing more about habits and preferences means that consumables can be pitched the right way and at the right time – think “push” notifications that pop up on your smartphone. 

This is a process heightened by increasingly sophisticated algorithms that can “learn” a lot about what motivates and resonates with us. 

When those customers include the public sector, and the sales pitch is that a city can’t do without the most sizzling new sensor array or analytics engine (after all, the city next door has them), things start getting tricky. 

So, I’m not convinced that enough urban tech is sufficiently citizen-driven. 

Three concerns relating to urban tech that government needs to address, in a coordinated and sustained way.

All three apply to how civic spaces are accessed, managed and experienced. 

1. Legacy systems

This refers to proprietary hardware and software that cities can deploy to supplement or fulfill civic functions. 

Sometimes these are offered for free or at a significant discount (e.g. like public wi-fi) to cities on the basis of a contract term and ongoing maintenance fee. 

Alternatively, they might be offered in exchange for access to consumer data that’s then used to market and sell consumables. 

The legacy comes from the contract term, or the sole-provider hardware or software that the city is then wedded to.

2. Third-party applications

This is when data is harvested by on party and passed on to another for added use. For example, Glaxo Smith Kline has a four-year, $300m investment deal with 23andMe to use genetic data to develop new drug regimes. 23andMe customers pay for feedback on the genetic materials they provide, which is then used, albeit in aggregate, for research for profit. 

In the civic arena, a parallel would be a wi-fi provider collecting data about a consumer’s locations, consumptive behaviour and other characteristics, and passing this on to suppliers of specialist goods and services. 

On the one hand, these actions might improve access to goods and services through targeted marketing; however, on the other, are consumers giving informed consent for their data to be used in this way, and at what point does marketing become unduly manipulative?  

3. The manipulation of data and/ or civic experience behind a corporate firewall. 

The more the tech sector and digital entrepreneurialism grow, the more frequent, grander-scale, pernicious or downright malicious activity seems to become. 

Some of the manipulation arises through third-party cybercrime: Think the hacks of 3 billion Yahoo subscriber accounts in 2013 and 2014, and 57 million Uber drivers and users in 2016. 

Other manipulation is the product of orchestrated corporate malfeasance, such as the Cambridge Analytica scandal involving unsanctioned use of Facebook user data and Volkswagen’s infamous “dieselgate”.

Cities are likely to continue to be the focal points for clashes between techno-corporate conduct and the public interest. 

As technology evolves, civic policy has to follow. Plainly, civic policy cannot afford to stifle entrepreneurialism and be technophobic.  

Three phases of evolution of smart city policy

Some commentators refer to “phases” of the evolution of smart city policy. Boyd Cohen, for example, refers to three phases: 

  1. technology-driven
  2. city-led and technology-enabled
  3. citizen-driven. 

In Cohen’s view, some cities are starting to demonstrate much more sophisticated and inclusive applications of technology in

Ryan Falcone

the urban environment, addressing citizen quality-of-life issues with fewer unwanted (and unforeseen) trade-offs. 

As Ben Green puts it in his book, Smart Enough City, government needs to focus on human-centric outcomes and use technology as an enabler. 

In so doing, benefits must be measurable against costs and trade-offs, and citizens must be part of the conversation regarding what they must cede to use public space. 

Significantly, more effort is required to define, apply and enforce data access, management and application standards particularly when these apply to activities within the public realm. 

Ryan Falconer holds a PhD in Sustainability in technology policy, and formerly led Arup’s cities business in Western Australia. Ryan has published over 30 papers and thought-pieces and presented to audiences in seven countries on cities and sustainable transport.

Spinifex is an opinion column open to all, so called because it’s at the “spiky” end of sustainability. Spinifex may be inconvenient or annoying at times, but in fact, it’s highly resilient in a hostile environment and essential to nurturing biodiversity and holding the topsoil together. If you would like to contribute, we require 700+ words. For a more detailed brief and style guide please email

(Visited 1 times, 1 visits today)

Leave a comment

Your email address will not be published.