Smart Digital Urbanism: creating the conditions for equitably distributed opportunity in the digital age

(The sound artists FA-TECH [http://fa-tech.tumblr.com/] improvising in Shoreditch, London. Shoreditch's combination of urban character, cheap rents and proximity to London's business, financial centres and culture led to the emergence of a thriving technology startup community - although that community's success is now driving rents up, challenging some of the characteristics that enabled it.)

(The sound artists FA-TECH improvising in Shoreditch, London. Shoreditch’s combination of urban character, cheap rents and proximity to London’s business, financial centres and culture led to the emergence of a thriving technology startup community – although that community’s success is now driving rents up, challenging some of the characteristics that enabled it.)

(I first learned of the architect Kelvin Campbell‘s concept of “massive/small” just over two years ago – the idea that certain characteristics of policy and the physical environment in cities could encourage “massive amounts of small-scale innovation” to occur. Kelvin recently launched a collaborative campaign to capture ideas, tools and tactics for massive/small “Smart Urbanism“. This is my first contribution to that campaign.)

Over the past 5 years, enormous interest has developed in the potential for digital technologies to contribute to the construction and development of cities, and to the operation of the services and infrastructures that support them. These ideas are often referred to as “Smart Cities” or “Future Cities”.

Indeed, as the price of digital technologies such as smartphones, sensors, analytics, open source software and cloud platforms reduces rapidly, market dynamics will drive their aggressive adoption to make construction, infrastructure and city services more efficient, and hence make their providers more competitive.

But those market dynamics do not guarantee that we will get everything we want for the future of our cities: efficiency and resilience are not the same as health, happiness and opportunity for every citizen.

Is it realistic to ask ourselves whether we can achieve those objectives? Yes, it has to be.

Many of us believe in that possibility, and spend a lot of our efforts finding ways to achieve it. And over the same timeframe that interest in “smart” and “future” cities has emerged, a belief has developed around the world that the governance institutions of cities – local authorities and elected mayors, rather than the governments of nations – are the most likely political entities to implement the policies that lead to a sustainable, resilient future with more equitably distributed economic growth.

Consequently many Mayors and City Councils are considering or implementing legislation and policy frameworks that change the economic and financial context in which construction, infrastructure and city services are deployed and operated. The British Standards Institute recently published guidance on this topic as part of its overall Smart Cities Standards programme.

But whilst in principle these trends and ideas are incredibly exciting in their potential to create better cities, communities, places and lives in the future, in practise many debates about applying them falter on a destructive and misleading argument between “top-down” and “bottom-up” approaches – the same chasm that Smart Urbanism seeks to bridge in the physical world.

Policies and programmes driven by central government organisations or implemented by technology and infrastructure corporations that drive digital technology into large-scale infrastructures and public services are often criticised as crude, “top-down” initiatives that prioritise resilience and efficiency at the expense of the concerns and values of ordinary people, businesses and communities. However, the organic, “bottom-up” innovation that critics of these initatives champion as the better, alternative approach is ineffective at creating equality.

("Lives on the Line" by James Cheshire at UCL's Centre for Advanced Spatial Analysis, showing the variation in life expectancy and correlation to child poverty in London. From Cheshire, J. 2012. Lives on the Line: Mapping Life Expectancy Along the London Tube Network. Environment and Planning A. 44 (7). Doi: 10.1068/a45341)

(“Lives on the Line” by James Cheshire at UCL’s Centre for Advanced Spatial Analysis, showing the variation in life expectancy and correlation to child poverty in London. From Cheshire, J. 2012. Lives on the Line: Mapping Life Expectancy Along the London Tube Network. Environment and Planning A. 44 (7). Doi: 10.1068/a45341)

“Bottom-up innovation” is what every person, community and business does every day: using our innate creativity to find ways to use the resources and opportunities available to us to make a better life.

But the degree to which we fail to distribute those resources and opportunities equally is illustrated by the stark variation in life expectancy between the richest and poorest areas of cities in the UK: often this variation is as much as 20 years within a single city.

Just as the “design pattern”, a tool invented by a town planner in the 1970s, Christopher Alexander, is probably the single most influential concept that drove the development of the digital technology we all use today, two recent movements in town planning and urban design – “human scale cities” and “smart urbanism” – offer the analogies that can connect “top-down” technology policies and infrastructure with the factors that affect the success of “bottom-up” creativity to create “massive / small” success: future, digital cities that create “massive amounts of small-scale innovation“.

The tools to achieve this are relatively cheap, and the right policy environment could make it fairly straightforward to augment the business case for efficient, resilient “smart city” infrastructures to ensure that they are deployed. They are the digital equivalents of the physical concepts of Smart Urbanism – the use of open grid structures for spatial layouts, and the provision of basic infrastructure components such as street layouts and party walls in areas expected to attract high growth in informal housing. Some will be delivered as a natural consequence of market forces driving technology adoption; but others will only become economically viable when local or national government policies shape the market by requiring them:

  • Broadband, wi-if and 3G / 4G connectivity should be broadly available so that everyone can participate in the digital economy.
  • The data from city services should be made available as Open Data and published through “Application Programming Interfaces” (APIs) so that everybody knows how they work; and can adapt them to their own individual needs.
  • The data and APIs should be made available in the form of Open Standards so that everybody can understand them; and so that the systems that we rely on can work together.
  • The data and APIs should be available to developers working on Cloud Computing platforms with Open Source software so that anyone with a great idea for a new service to offer to people or businesses can get started for free.
  • The technology systems that support the services and infrastructures we rely on should be based on Open Architectures, so that we have freedom to chose which technologies we use, and to change our minds.
  • Governments, institutions, businesses and communities should participate in an open dialogue about the places we live and work in, informed by open data, enabled by social media and smartphones, and enlightened by empathy.

(Casserole Club, a social enterprise developed by FutureGov uses social media to connect people who have difficulty cooking for themselves with others who are happy to cook an extra portion for a neighbour; a great example of a locally-focused “sharing economy” business model which creates financially sustainable social value.)

These principles would encourage good “digital placemaking“: they would help to align the investments that will be made in improving cities using technology with the needs and motivations of the public sector, the private sector, communities and businesses. They would create “Smart Digital Urbanism”: the conditions and environment in which vibrant, fair digital cities grow from the successful innovations of their citizens, communities and businesses in the information economy.

In my new role at Amey, a vast organisation in the UK that delivers public services and operates and supports public infrastructure, I’m leading a set of innovative projects with our customers and technology partners to explore these ideas and to understand how we can collaboratively create economic, social and environmental value for ourselves; for our customers; and for the people, communities and businesses who live in the areas our services support.

It’s a terrifically exciting role; and I’ll soon be hiring a small team of passionate, creative people to help me identify, shape and deliver those projects. I’ll post an update here with details of the skills, experience and characteristics I’m looking for. I hope some of you will find them attractive and get in touch.

From concrete to telepathy: how to build future cities as if people mattered

(An infographic depicting realtime data describing Dublin - the waiting time at road junctions; the location of buses; the number of free parking spaces and bicycles available to hire; and sentiments expressed about the city through social meida)

(An infographic depicting realtime data describing Dublin – the waiting time at road junctions; the location of buses; the number of free parking spaces and bicycles available to hire; and sentiments expressed about the city through social media)

(I was honoured to be asked to speak at TEDxBrum in my home city of Birmingham this weekend. The theme of the event was “DIY” – “the method of building, modifying or repairing something without the aid of experts or professionals”. In other words, how Birmingham’s people, communities and businesses can make their home a better place. This is a rough transcript of my talk).

What might I, a middle-aged, white man paid by a multi-national corporation to be an expert in cities and technology, have to say to Europe’s youngest city, and one of its most ethnically and nationally diverse, about how it should re-create itself “without the aid of experts or professionals”?

Perhaps I could try to claim that I can offer the perspective of one of the world’s earliest “digital natives”. In 1980, at the age of ten, my father bought me one of the world’s first personal computers, a Tandy TRS 80, and taught me how to programme it using “machine code“.

But about two years ago, whilst walking through London to give a talk at a networking event, I was reminded of just how much the world has changed since my childhood.

I found myself walking along Wardour St. in Soho, just off Oxford St., and past a small alley called St. Anne’s Court which brought back tremendous memories for me. In the 1980s I spent all of the money I earned washing pots in a local restaurant in Winchester to travel by train to London every weekend and visit a small shop in a basement in St. Anne’s Court.

I’ve told this story in conference speeches a few times now, perhaps to a total audience of a couple of thousand people. Only once has someone been able to answer the question:

“What was the significance of St. Anne’s Court to the music scene in the UK in the 1980s?”

Here’s the answer:

Shades Records, the shop in the basement, was the only place in the UK that sold the most extreme (and inventive) forms of “thrash metal” and “death metal“, which at the time were emerging from the ashes of punk and the “New Wave of British Heavy Metal” in the late 1970s.

G157 Richard with his Tandy

(Programming my Tandy TRS 80 in Z80 machine code nearly 35 years ago)

The process by which bands like VOIVOD, Coroner and Celtic Frost – who at the time were three 17-year-olds who practised in an old military bunker outside Zurich – managed to connect – without the internet – to the very few people around the world like me who were willing to pay money for their music feels like ancient history now. It was a world of hand-printed “fanzines”, and demo tapes painstakingly copied one at a time, ordered by mail from classified adverts in magazines like Kerrang!

Our world has been utterly transformed in the relatively short time between then and now by the phenomenal ease with which we can exchange information through the internet and social media.

The real digital natives, though, are not even those people who grew up with the internet and social media as part of their everyday world (though those people are surely about to change the world as they enter employment).

They are the very young children like my 6-year-old son, who taught himself at the age of two to use an iPad to access the information that interested him (admittedly, in the form of Thomas the Tank Engine stories on YouTube) before anyone else taught him to read or write, and who can now use programming tools like MIT’s Scratch to control computers vastly more powerful than the one I used as a child.

Their expectations of the world, and of cities like Birmingham, will be like no-one who has ever lived before.

And their ability to use technology will be matched by the phenomenal variety of data available to them to manipulate. As everything from our cars to our boilers to our fridges to our clothing is integrated with connected, digital technology, the “Internet of Things“, in which everything is connected to the internet, is emerging. As a consequence our world, and our cities, are full of data.

(The programme I helped my 6-year old son write using MIT's "Scratch" language to draw a picture of a house)

(The programme I helped my 6-year old son write using MIT’s “Scratch” language to cause a cartoon cat to draw a picture of a house)

My friend the architect Tim Stonor calls the images that we are now able to create, such as the one at the start of this article, “data porn”. The image shows data about Dublin from the Dublinked information sharing partnership: the waiting time at road junctions; the location of buses; the number of free parking spaces and bicycles available to hire; and sentiments expressed about the city through social media.

Tim’s point is that we should concentrate not on creating pretty visualisations; but on the difference we can make to cities by using this data. Through Open Data portals, social media applications, and in many other ways, it unlocks secrets about cities and communities:

  • Who are the 17 year-olds creating today’s most weird and experimental music? (Probably by collaborating digitally from three different bedroom studios on three different continents)
  • Where is the healthiest walking route to school?
  • Is there a local company nearby selling wonderful, oven-ready curries made from local recipes and fresh ingredients?
  • If I set off for work now, will a traffic jam develop to block my way before I get there?

From Dublin to Montpellier to Madrid and around the world my colleagues are helping cities to build 21st-Century infrastructures that harness this data. As technology advances, every road, electricity substation, University building, and supermarket supply chain will exploit it. The business case is easy: we can use data to find ways to operate city services, supply chains and infrastructure more efficiently, and in a way that’s less wasteful of resources and more resilient in the face of a changing climate.

Top-down thinking is not enough

But to what extent will this enormous investment in technology help the people who live and work in cities, and those who visit them, to benefit from the Information Economy that digital technology  and data is creating?

This is a vital question. The ability of digital technology to optimise and automate tasks that were once carried out by people is removing jobs that we have relied on for decades. In order for our society to be based upon a fair and productive economy, we all need to be able to benefit from the new opportunities to work and be successful that are being created by digital technology.

(Photo of Masshouse Circus, Birmingham, a concrete urban expressway that strangled the citycentre before its redevelopment in 2003, by Birmingham City Council)

(Photo of Masshouse Circus, Birmingham, a concrete urban expressway that strangled the city centre before its redevelopment in 2003, by Birmingham City Council)

Too often in the last century, we got this wrong. We used the technologies of the age – concrete, lifts, industrial machinery and cars – to build infrastructures and industries that supported our mass needs for housing, transport, employment and goods; but that literally cut through and isolated the communities that create urban life.

If we make the same mistake by thinking only about digital technology in terms of its ability to create efficiencies, then as citizens, as communities, as small businesses we won’t fully benefit from it.

In contrast, one of the authors of Birmingham’s Big City Plan, the architect Kelvin Campbell, created the concept of “massive / small“. He asked: what are the characteristics of public policy and city infrastructure that create open, adaptable cities for everyone and that thereby give rise to “massive” amounts of “small-scale” innovation?

In order to build 21st Century cities that provide the benefits of digital technology to everyone we need to find the design principles that enable the same “massive / small” innovation to emerge in the Information Economy, in order that we can all use the simple, often free, tools available to us to create our own opportunities.

There are examples we can learn from. Almere in Holland use analytics technology to plan and predict the future development of the city; but they also engage in dialogue with their citizens about the future the city wants. Montpellier in France use digital data to measure the performance of public services; but they also engage online with their citizens in a dialogue about those services and the outcomes they are trying to achieve. The Dutch Water Authority are implementing technology to monitor, automate and optimise an infrastructure on which many cities depend; but making much of the data openly available to communities, businesses, researchers and innovators to explore.

There are many issues of policy, culture, design and technology that we need to get right for this to happen, but the main objectives are clear:

  • The data from city services should be made available as Open Data and through published “Application Programming Interfaces” (APIs) so that everybody knows how they work; and can adapt them to their own individual needs.
  • The data and APIs should be made available in the form of Open Standards so that everybody can understand it; and so that the systems that we rely on can work together.
  • The data and APIs should be available to developers working on Cloud Computing platforms with Open Source software so that anyone with a great idea for a new service to offer to people or businesses can get started for free.
  • The technology systems that support the services and infrastructures we rely on should be based on Open Architectures, so that we have freedom to chose which technologies we use, and to change our minds.
  • Governments, institutions, businesses and communities should participate in an open dialogue, informed by data and enlightened by empathy, about the places we live and work in.

If local authorities and national government create planning policies, procurement practises and legislation that require that public infrastructure, property development and city services provide this openness and accessibility, then the money spent on city infrastructure and services will create cities that are open and adaptable to everyone in a digital age.

Bottom-up innovation is not enough, either

(Coders at work at the Birmingham “Smart Hack”, photographed by Sebastian Lenton)

Not everyone has access to the technology and skills to use this data, of course. But some of the people who do will create the services that others need.

I took part in my first “hackathon” in Birmingham two years ago. A group of people spent a weekend together in 2012 asking themselves: in what way should Birmingham be better? And what can we do about it? Over two days, they wrote an app, “Second Helping”, that connected information about leftover food in the professional kitchens of restaurants and catering services, to soup kitchens that give food to people who don’t have enough.

Second Helping was a great idea; but how do you turn a great idea and an app into a change in the way that food is used in a city?

Hackathons and “civic apps” are great examples of the “bottom-up” creativity that all of us use to create value – innovating with the resources around us to make a better life, run a better business, or live in a stronger community. But “bottom-up” on it’s own isn’t enough.

The result of “bottom-up” innovation at the moment is that life expectancy in the poorest parts of Birmingham is more than 10 years shorter than it is in the richest parts. In London and Glasgow, it’s more than 20 years shorter.

If you’re born in the wrong place, you’re likely to die 10 years younger than someone else born in a different part of the same city. This shocking situation arises from many, complex issues; but one conclusion that it is easy to draw is that the opportunity to innovate successfully is not the same for everyone.

So how do we increase everybody’s chances of success? We need to create the policies, institutions, culture and behaviours that join up the top-down thinking that tends to control the allocation of resources and investment, especially for infrastructure, with the needs of bottom-up innovators everywhere.

Translational co-operation

Harborne Food School

(The Harborne Food School, which will open in the New Year to offer training and events in local and sustainable food)

The Economist magazine reminded us of the importance of those questions in a recent article describing the enormous investments made in public institutions such as schools, libraries and infrastructure in the past in order to distribute the benefits of the Industrial Revolution to society at large rather than concentrate them on behalf of business owners and the professional classes.

But the institutions of the past, such as the schools which to a large degree educated the population for repetitive careers in labour-intensive factories, won’t work for us today. Our world is more complicated and requires a greater degree of localised creativity to be successful. We need institutions that are able to engage with and understand individuals; and that make their resources openly available so that each of us can use them in the way that makes most sense to us. Some public services are starting to respond to this challenge, through the “Open Public Services” agenda; and the provision of Open Data and APIs by public services and infrastructure are part of the response too.

But as Andrew Zolli describes in “Resilience: why things bounce back“, there are both institutional and cultural barriers to engagement and collaboration between city institutions and localised innovation. Zolli describes the change-makers who overcome those barriers as “translational leaders” – people with the ability to engage with both small-scale, informal innovation in communities and large-scale, formal institutions with resources.

We’re trying to apply that “translational” thinking in Birmingham through the Smart City Alliance, a collaboration between 20 city institutions, businesses and innovators. The idea is to enable conversations about challenges and opportunities in the city, between people, communities, innovators and  the organisations who have resources, from the City Council and public institutions to businesses, entrepreneurs and social enterprises. We try to put people and organisations with challenges or good ideas in touch with other people or organisations with the ability to help them.

This is how we join the “top-down” resources, policies and programmes of city institutions and big companies with the “bottom-up” innovation that creates value in local situations. A lot of the time it’s about listening to people we wouldn’t normally meet.

Partly as a consequence, we’ve continued to explore the ideas about local food that were first raised at the hackathon. Two years later, the Harborne Food School is close to opening as a social enterprise in a redeveloped building on Harborne High Street that had fallen out of use.

The school will be teaching courses that help caterers provide food from sustainable sources, that teach people how to set up and run food businesses, and that help people to adopt diets that prevent or help to manage conditions such as diabetes. The idea has changed since the “Second Helping” app was written, of course; but the spirit of innovation and local value is the same.

Cities that work like magic

So what does all this have to do with telepathy?

The innovations and changes caused by the internet over the last two decades have accelerated as it has made information easier and easier to access and exchange through the advent of technologies such as broadband, mobile devices and social media. But the usefulness of all of those technologies is limited by the tools required to control them – keyboards, mice and touchscreens.

Before long, we won’t need those tools at all.

Three years ago, scientists at the University of Berkely used computers attached to an MRI scanner to recreate moving images from the magnetic field created by the brain of a person inside the scanner watching a film on a pair of goggles. And last year, scientists at the University of Washington used similar technology to allow one of them to move the other’s arm simply by thinking about it. A less sensitive mind-reading technology is already available as a headset from Emotiv, which my colleagues in IBM’s Emerging Technologies team have used to help a paralysed person communicate by thinking directional instructions to a computer.

Telepathy is now technology, and this is just one example of the way that the boundary between our minds, bodies and digital information will disappear over the next decade. As a consequence, our cities and lives will change in ways we’ve never imagined, and some of those changes will happen surprisingly quickly.

I can’t predict what Birmingham will or should be like in the future. As a citizen, I’ll be one of the million or so people who decide that future through our choices and actions. But I can say that the technologies available to us today are the most incredible DIY tools for creating that future that we’ve ever had access to. And relatively quickly technologies like bio-technology, 3D printing and brain/computer interfaces will put even more power in our hands.

As a parent, I get engaged in my son’s exploration of these technologies and help him be digitally aware, creative and responsible. Whenever I can, I help schools, Universities, small businesses or community initiatives to use them, because I might be helping one of IBM’s best future employees or business partners; or just because they’re exciting and worth helping. And as an employee, I try to help my company take decisions that are good for our long term business because they are good for the society that the business operates in.

We can take for granted that all of us, whatever we do, will encounter more and more incredible technologies as time passes. By remembering these very simple things, and remembering them in the hundreds of choices I make every day, I hope that I’ll be using them to play my part in building a better Birmingham, and better cities and communities everywhere.

(Shades Records in St. Anne's Court in the 1980s)

(Shades Records in St. Anne’s Court in the 1980s. You can read about the role it played in the development of the UK’s music culture – and in the lives of its customers – in this article from Thrash Hits;  or this one from Every Record Tells a Story. And if you really want to find out what it was all about, try watching Celtic Frost or VOIVOD in the 1980s!)

11 reasons computers can’t understand or solve our problems without human judgement

(Photo by Matt Gidley)

(Photo by Matt Gidley)

Why data is uncertain, cities are not programmable, and the world is not “algorithmic”.

Many people are not convinced that the Smart Cities movement will result in the use of technology to make places, communities and businesses in cities better. Outside their consumer enjoyment of smartphones, social media and online entertainment – to the degree that they have access to them – they don’t believe that technology or the companies that sell it will improve their lives.

The technology industry itself contributes significantly to this lack of trust. Too often we overstate the benefits of technology, or play down its limitations and the challenges involved in using it well.

Most recently, the idea that traditional processes of government should be replaced by “algorithmic regulation” – the comparison of the outcomes of public systems to desired objectives through the measurement of data, and the automatic adjustment of those systems by algorithms in order to achieve them – has been proposed by Tim O’Reilly and other prominent technologists.

These approaches work in many mechanical and engineering systems – the autopilots that fly planes or the anti-lock braking systems that we rely on to stop our cars. But should we extend them into human realms – how we educate our children or how we rehabilitate convicted criminals?

It’s clearly important to ask whether it would be desirable for our society to adopt such approaches. That is a complex debate, but my personal view is that in most cases the incredible technologies available to us today – and which I write about frequently on this blog – should not be used to take automatic decisions about such issues. They are usually more valuable when they are used to improve the information and insight available to human decision-makers – whether they are politicians, public workers or individual citizens – who are then in a better position to exercise good judgement.

More fundamentally, though, I want to challenge whether “algorithmic regulation” or any other highly deterministic approach to human issues is even possible. Quite simply, it is not.

It is true that our ability to collect, analyse and interpret data about the world has advanced to an astonishing degree in recent years. However, that ability is far from perfect, and strongly established scientific and philosophical principles tell us that it is impossible to definitively measure human outcomes from underlying data in physical or computing systems; and that it is impossible to create algorithmic rules that exactly predict them.

Sometimes automated systems succeed despite these limitations – anti-lock braking technology has become nearly ubiquitous because it is more effective than most human drivers at slowing down cars in a controlled way. But in other cases they create such great uncertainties that we must build in safeguards to account for the very real possibility that insights drawn from data are wrong. I do this every time I leave my home with a small umbrella packed in my bag despite the fact that weather forecasts created using enormous amounts of computing power predict a sunny day.

(No matter how sophisticated computer models of cities become, there are fundamental reasons why they will always be simplifications of reality. It is only by understanding those constraints that we can understand which insights from computer models are valuable, and which may be misleading. Image of Sim City by haljackey)

We can only understand where an “algorithmic” approach can be trusted; where it needs safeguards; and where it is wholly inadequate by understanding these limitations. Some of them are practical, and limited only by the sensitivity of today’s sensors and the power of today’s computers. But others are fundamental laws of physics and limitations of logical systems.

When technology companies assert that Smart Cities can create “autonomous, intelligently functioning IT systems that will have perfect knowledge of users’ habits” (as London School of Economics Professor Adam Greenfield rightly criticised in his book “Against the Smart City”), they are ignoring these challenges.

A blog published by the highly influential magazine Wired recently made similar overstatements: “The Universe is Programmable” argues that we should extend the concept of an “Application Programming Interface (API)” – a facility usually offered by technology systems to allow external computer programmes to control or interact with them – to every aspect of the world, including our own biology.

To compare complex, unpredictable, emergent biological and social systems to the very logical, deterministic world of computer software is at best a dramatic oversimplification. The systems that comprise the human body range from the armies of symbiotic microbes that help us digest food in our stomachs to the consequences of using corn syrup to sweeten food to the cultural pressure associated with “size 0” celebrities. Many of those systems can’t be well modelled in their own right, let alone deterministically related to each other; let alone formally represented in an accurate, detailed way by technology systems (or even in mathematics).

We should regret and avoid the hubris that leads to the distrust of technology by overstating its capability and failing to recognise its challenges and limitations. That distrust is a barrier that prevents us from achieving the very real benefits that data and technology can bring, and that have been convincingly demonstrated in the past.

For example, an enormous contribution to our knowledge of how to treat and prevent disease was made by John Snow who used data to analyse outbreaks of cholera in London in the 19th century. Snow used a map to correlate cases of cholera to the location of communal water pipes, leading to the insight that water-borne germs were responsible for spreading the disease. We wash our hands to prevent diseases spreading through germs in part because of what we would now call the “geospatial data analysis” performed by John Snow.

Many of the insights that we seek from analytic and smart city systems are human in nature, not physical or mathematical – for example identifying when and where to apply social care interventions in order to reduce the occurrence of  emotional domestic abuse. Such questions are complex and uncertain: what is “emotional domestic abuse?” Is it abuse inflicted by a live-in boyfriend, or by an estranged husband who lives separately but makes threatening telephone calls? Does it consist of physical violence or bullying? And what is “bullying”?

IMG_0209-1

(John Snow’s map of cholera outbreaks in 19th century London)

We attempt to create structured, quantitative data about complex human and social issues by using approximations and categorisations; by tolerating ranges and uncertainties in numeric measurements; by making subjective judgements; and by looking for patterns and clusters across different categories of data. Whilst these techniques can be very powerful, just how difficult it is to be sure what these conventions and interpretations should be is illustrated by the controversies that regularly arise around “who knew what, when?” whenever there is a high profile failure in social care or any other public service.

These challenges are not limited to “high level” social, economic and biological systems. In fact, they extend throughout the worlds of physics and chemistry into the basic nature of matter and the universe. They fundamentally limit the degree to which we can measure the world, and our ability to draw insight from that information.

By being aware of these limitations we are able to design systems and practises to use data and technology effectively. We know more about the weather through modelling it using scientific and mathematical algorithms in computers than we would without those techniques; but we don’t expect those forecasts to be entirely accurate. Similarly, supermarkets can use data about past purchases to make sufficiently accurate predictions about future spending patterns to boost their profits, without needing to predict exactly what each individual customer will buy.

We underestimate the limitations and flaws of these approaches at our peril. Whilst Tim O’Reilly cites several automated financial systems as good examples of “algorithmic regulation”, the financial crash of 2008 showed the terrible consequences of the thoroughly inadequate risk management systems used by the world’s financial institutions compared to the complexity of the system that they sought to profit from. The few institutions that realised that market conditions had changed and that their models for risk management were no longer valid relied instead on the expertise of their staff, and avoided the worst affects. Others continued to rely on models that had started to produce increasingly misleading guidance, leading to the recession that we are only now emerging from six years later, and that has damaged countless lives around the world.

Every day in their work, scientists, engineers and statisticians draw conclusions from data and analytics, but they temper those conclusions with an awareness of their limitations and any uncertainties inherent in them. By taking and communicating such a balanced and informed approach to applying similar techniques in cities, we will create more trust in these technologies than by overstating their capabilities.

What follows is a description of some of the scientific, philosophical and practical issues that lead inevitability to uncertainty in data, and to limitations in our ability to draw conclusions from it:

But I’ll finish with an explanation of why we can still draw great value from data and analytics if we are aware of those issues and take them properly into account.

Three reasons why we can’t measure data perfectly

(How Heisenberg’s Uncertainty Principle results from the dual wave/particle nature of matter. Explanation by HyperPhysics at Georgia State University)

1. Heisenberg’s Uncertainty Principle and the fundamental impossibility of knowing everything about anything

Heisenberg’s Uncertainty Principle is a cornerstone of Quantum Mechanics, which, along with General Relativity, is one of the two most fundamental theories scientists use to understand our world. It defines a limit to the precision with which certain pairs of properties of the basic particles which make up the world – such as protons, neutrons and electrons – can be known at the same time. For instance, the more accurately we measure the position of such particles, the more uncertain their speed and direction of movement become.

The explanation of the Uncertainty Principle is subtle, and lies in the strange fact that very small “particles” such as electrons and neutrons also behave like “waves”; and that “waves” like beams of light also behave like very small “particles” called “photons“. But we can use an analogy to understand it.

In order to measure something, we have to interact with it. In everyday life, we do this by using our eyes to measure lightwaves that are created by lightbulbs or the sun and that then reflect off objects in the world around us.

But when we shine light on an object, what we are actually doing is showering it with billions of photons, and observing the way that they scatter. When the object is quite large – a car, a person, or a football – the photons are so small in comparison that they bounce off without affecting it. But when the object is very small – such as an atom – the photons colliding with it are large enough to knock it out of its original position. In other words, measuring the current position of an object involves a collision which causes it to move in a random way.

This analogy isn’t exact; but it conveys the general idea. (For a full explanation, see the figure and link above). Most of the time, we don’t notice the effects of Heisenberg’s Uncertainty Principle because it applies at extremely small scales. But it is perhaps the most fundamental law that asserts that “perfect knowledge” is simply impossible; and it illustrates a wider point that any form of measurement or observation in general affects what is measured or observed. Sometimes the effects are negligible,  but often they are not – if we observe workers in a time and motion study, for example, we need to be careful to understand the effect our presence and observations have on their behaviour.

2. Accuracy, precision, noise, uncertainty and error: why measurements are never fully reliable

Outside the world of Quantum Mechanics, there are more practical issues that limit the accuracy of all measurements and data.

(A measurement of the electrical properties of a superconducting device from my PhD thesis. Theoretically, the behaviour should appear as a smooth, wavy line; but the experimental measurement is affected by noise and interference that cause the signal to become "fuzzy". In this case, the effects of noise and interference - the degree to which the signal appears "fuzzy" - are relatively small relative to the strength of the signal, and the device is usable)

(A measurement of the electrical properties of a superconducting device from my PhD thesis. Theoretically, the behaviour should appear as a smooth, wavy line; but the experimental measurement is affected by noise and interference that cause the signal to become “fuzzy”. In this case, the effects of noise and interference – the degree to which the signal appears “fuzzy” – are relatively small compared to the strength of the signal, and the device is usable)

We live in a “warm” world – roughly 300 degrees Celsius above what scientists call “absolute zero“, the coldest temperature possible. What we experience as warmth is in fact movement: the atoms from which we and our world are made “jiggle about” – they move randomly. When we touch a hot object and feel pain it is because this movement is too violent to bear – it’s like being pricked by billions of tiny pins.

This random movement creates “noise” in every physical system, like the static we hear in analogue radio stations or on poor quality telephone connections.

We also live in a busy world, and this activity leads to other sources of noise. All electronic equipment creates electrical and magnetic fields that spread beyond the equipment itself, and in turn affect other equipment – we can hear this as a buzzing noise when we leave smartphones near radios.

Generally speaking, all measurements are affected by random noise created by heat, vibrations or electrical interference; are limited by the precision and accuracy of the measuring devices we use; and are affected by inconsistencies and errors that arise because it is always impossible to completely separate the measurement we want to make from all other environmental factors.

Scientists, engineers and statisticians are familiar with these challenges, and use techniques developed over the course of more than a century to determine and describe the degree to which they can trust and rely on the measurements they make. They do not claim “perfect knowledge” of anything; on the contrary, they are diligent in describing the unavoidable uncertainty that is inherent in their work.

3. The limitations of measuring the natural world using digital systems

One of the techniques we’ve adopted over the last half century to overcome the effects of noise and to make information easier to process is to convert “analogue” information about the real world (information that varies smoothly) into digital information – i.e. information that is expressed as sequences of zeros and ones in computer systems.

(When analogue signals are amplified, so is the noise that they contain. Digital signals are interpreted using thresholds: above an upper threshold, the signal means “1”, whilst below a lower threshold, the signal means “0”. A long string of “0”s and “1”s can be used to encode the same information as contained in analogue waves. By making the difference between the thresholds large compared to the level of signal noise, digital signals can be recreated to remove noise. Further explanation and image by Science Aid)

This process involves a trade-off between the accuracy with which analogue information is measured and described, and the length of the string of digits required to do so – and hence the amount of computer storage and processing power needed.

This trade-off can be clearly seen in the difference in quality between an internet video viewed on a smartphone over a 3G connection and one viewed on a high definition television using a cable network. Neither video will be affected by the static noise that affects weak analogue television signals, but the limited bandwidth of a 3G connection dramatically limits the clarity and resolution of the image transmitted.

The Nyquist–Shannon sampling theorem defines this trade-off and the limit to the quality that can be achieved in storing and processing digital information created from analogue sources. It determines the quality of digital data that we are able to create about any real-world system – from weather patterns to the location of moving objects to the fidelity of sound and video recordings. As computers and communications networks continue to grow more powerful, the quality of digital information will improve,  but it will never be a perfect representation of the real world.

Three limits to our ability to analyse data and draw insights from it

1. Gödel’s Incompleteness Theorem and the inconsistency of algorithms

Kurt Gödel’s Incompleteness Theorem sets a limit on what can be achieved by any “closed logical system”. Examples of “closed logical systems” include computer programming languages, any system for creating algorithms – and mathematics itself.

We use “closed logical systems” whenever we create insights and conclusions by combining and extrapolating from basic data and facts. This is how all reporting, calculating, business intelligence, “analytics” and “big data” technologies work.

Gödel’s Incompleteness Theorem proves that any closed logical system can be used to create conclusions that  it is not possible to show are true or false using the same system. In other words, whilst computer systems can produce extremely useful information, we cannot rely on them to prove that that information is completely accurate and valid. We have to do that ourselves.

Gödel’s theorem doesn’t stop computer algorithms that have been verified by humans using the scientific method from working; but it does mean that we can’t rely on computers to both generate algorithms and guarantee their validity.

2. The behaviour of many real-world systems can’t be reduced analytically to simple rules

Many systems in the real-world are complex: they cannot be described by simple rules that predict their behaviour based on measurements of their initial conditions.

A simple example is the “three body problem“. Imagine a sun, a planet and a moon all orbiting each other. The movement of these three objects is governed by the force of gravity, which can be described by relatively simple mathematical equations. However, even with just three objects involved, it is not possible to use these equations to directly predict their long-term behaviour – whether they will continue to orbit each other indefinitely, or will eventually collide with each other, or spin off into the distance.

(A computer simulation by Hawk Express of a Belousov–Zhabotinsky reaction,  in which reactions between liquid chemicals create oscillating patterns of colour. The simulation is carried out using “cellular automata” a technique based on a grid of squares which can take different colours. In each “turn” of the simulation, like a turn in a board game, the colour of each square is changed using simple rules based on the colours of adjacent squares. Such simulations have been used to reproduce a variety of real-world phenomena)

As Stephen Wolfram argued in his controversial book “A New Kind of Science” in 2002, we need to take a different approach to understanding such complex systems. Rather than using mathematics and logic to analyse them, we need to simulate them, often using computers to create models of the elements from which complex systems are composed, and the interactions between them. By running simulations based on a large number of starting points and comparing the results to real-world observations, insights into the behaviour of the real-world system can be derived. This is how weather forecasts are created, for example. 

But as we all know, weather forecasts are not always accurate. Simulations are approximations to real-world systems, and their accuracy is restricted by the degree to which digital data can be used to represent a non-digital world. For this reason, conclusions and predictions drawn from simulations are usually “average” or “probable” outcomes for the system as a whole, not precise predictions of the behaviour of the system or any individual element of it. This is why weather forecasts are often wrong; and why they predict likely levels of rain and windspeed rather than the shape and movement of individual clouds.

(Hello)

(A simple and famous example of a computer programme that never stops running because it calls itself. The output continually varies by printing out characters based on random number generation. Image by Prosthetic Knowledge)

3. Some problems can’t be solved by computing machines

If I consider a simple question such as “how many letters are in the word ‘calculation’?”, I can easily convince myself that a computer programme could be written to answer the question; and that it would find the answer within a relatively short amount of time. But some problems are much harder to solve, or can’t even be solved at all.

For example, a “Wang Tile” (see image below) is a square tile formed from four triangles of different colours. Imagine that you have bought a set of tiles of various colour combinations in order to tile a wall in a kitchen or bathroom. Given the set of tiles that you have bought, is it possible to tile your wall so that triangles of the same colour line up to each other, forming a pattern of “Wang Tile” squares?

In 1966 Robert Berger proved that no algorithm exists that can answer that question. There is no way to solve the problem – or to determine how long it will take to solve the problem – without actually solving it. You just have to try to tile the room and find out the hard way.

One of the most famous examples of this type of problem is the “halting problem” in computer science. Some computer programmes finish executing their commands relatively quickly. Others can run indefinitely if they contain a “loop” instruction that never ends. For others which contain complex sequences of loops and calls from one section of code to another, it may be very hard to tell whether the programme finishes quickly, or takes a long time to complete, or never finishes its execution at all.

Alan Turing, one of the most important figures in the development of computing, proved in 1936 that a general algorithm to determine whether or not any computer programme finishes its execution does not exist. In other words, whilst there are many useful computer programmes in the world, there are also problems that computer programmes simply cannot solve.

(A set of Wang Tiles, and a pattern created by tiling them so that tiles are placed next to other tiles so that their edges have the same colour. Given any particular set of tiles, it is impossible to determine whether such a pattern can be created by any means other than trial and error)

(A set of Wang Tiles, and a pattern of coloured squares created by tiling them. Given any random set of tiles of different colour combinations, there is no set of rules that can be relied on to determine whether a valid pattern of coloured squares can be created from them. Sometimes, you have to find out by trial and error. Images from Wikipedia)

Five reasons why the human world is messy, unpredictable, and can’t be perfectly described using data and logic

1. Our actions create disorder

The 2nd Law of Thermodynamics is a good candidate for the most fundamental law of science. It states that as time progresses, the universe becomes more disorganised. It guarantees that ultimately – in billions of years – the Universe will die as all of the energy and activity within it dissipates.

An everyday practical consequence of this law is that every time we act to create value – building a shed, using a car to get from one place to another, cooking a meal – our actions eventually cause a greater amount of disorder to be created as a consequence – as noise, pollution, waste heat or landfill refuse.

For example, if I spend a day building a shed, then to create that order and value from raw materials, I consume structured food and turn it into sewage. Or if I use an electric forklift to stack a pile of boxes, I use electricity that has been created by burning structured coal into smog and ash.

So it is literally impossible to create a “perfect world”. Whenever we act to make a part of the world more ordered, we create disorder elsewhere. And ultimately – thankfully, long after you and I are dead – disorder is all that will be left.

2. The failure of Logical Atomism: why the human world can’t be perfectly described using data and logic

In the 20th Century two of the most famous and accomplished philosophers in history, Bertrand Russell and Ludwig Wittgenstein, invented “Logical Atomism“, a theory that the entire world could be described by using “atomic facts” – independent and irreducible pieces of knowledge – combined with logic.

But despite 40 years of work, these two supremely intelligent people could not get their theory to work: “Logical Atomism” failed. It is not possible to describe our world in that way.

One cause of the failure was the insurmountable difficulty of identifying truly independent, irreducible atomic facts. “The box is red” and “the circle is blue”, for example, aren’t independent or irreducible facts for many reasons. “Red” and “blue” are two conventions of human language used to describe the perceptions created when electro-magnetic waves of different frequencies arrive at our retinas. In other words, they depend on and relate to each other through a number of sophisticated systems.

Despite centuries of scientific and philosophical effort, we do not have a complete understanding of how to describe our world at its most basic level. As physicists have explored the world at smaller and smaller scales, Quantum Mechanics has emerged as the most fundamental theory for describing it – it is the closest we have come to finding the “irreducible facts” that Russell and Wittgenstein were looking for. But whilst the mathematical equations of Quantum Mechanics predict the outcomes of experiments very well, after nearly a century, physicists still don’t really agree about what those equations mean. And as we have already seen, Heisenberg’s Uncertainty Principle prevents us from ever having perfect knowledge of the world at this level.

Perhaps the most important failure of logical atomism, though, was that it proved impossible to use logical rules to turn “facts” at one level of abstraction – for example, “blood cells carry oxygen”, “nerves conduct electricity”, “muscle fibres contract” – into facts at another level of abstraction – such as “physical assault is a crime”. The human world and the things that we care about can’t be described using logical combinations of “atomic facts”. For example, how would you define the set of all possible uses of a screwdriver, from prising the lids off paint tins to causing a short-circuit by jamming it into a switchboard?

Our world is messy, subjective and opportunistic. It defies universal categorisation and logical analysis.

(A Pescheria in Bari, Puglia, where a fish-market price information service makes it easier for local fisherman to identify the best buyers and prices for their daily catch. Photo by Vito Palmi)

3. The importance and inaccessibility of “local knowledge” 

Because the tool we use for calculating and agreeing value when we exchange goods and services is money, economics is the discipline that is often used to understand the large-scale behaviour of society. We often quantify the “growth” of society using economic measures, for example.

But this approach is notorious for overlooking social and environmental characteristics such as health, happiness and sustainability. Alternatives exist, such as the Social Progress Index, or the measurement framework adopted by the United Nations 2014 Human Development Report on world poverty; but they are still high level and abstract.

Such approaches struggle to explain localised variations, and in particular cannot predict the behaviours or outcomes of individual people with any accuracy. This “local knowledge problem” is caused by the fact that a great deal of the information that determines individual actions is personal and local, and not measurable at a distance – the experienced eye of the fruit buyer assessing not just the quality of the fruit but the quality of the farm and farmers that produce it, as a measure of the likely consistency of supply; the emotional attachments that cause us to favour one brand over another; or the degree of community ties between local businesses that influence their propensity to trade with each other.

Sharing economy” business models that use social media and reputation systems to enable suppliers and consumers of goods and services to find each other and transact online are opening up this local knowledge to some degree. Local food networks, freecycling networks, and land-sharing schemes all use this technology to the benefit of local communities whilst potentially making information about detailed transactions more widely available. And to some degree, the human knowledge that influences how transactions take place can be encoded in “expert systems” which allow computer systems to codify the quantitative and heuristic rules by which people take decisions.

But these technologies are only used in a subset of the interactions that take place between people and businesses across the world, and it is unlikely that they’ll become ubiquitous in the foreseeable future (or that we would want them to become so). Will we ever reach the point where prospective house-buyers delegate decisions about where to live to computer programmes operating in online marketplaces rather than by visiting places and imagining themselves living there? Will we somehow automate the process of testing the freshness of fish by observing the clarity of their eyes and the freshness of their smell before buying them to cook and eat?

In many cases, while technology may play a role introducing potential buyers and sellers of goods and services to each other, it will not replace – or predict – the human behaviours involved in the transaction itself.

(Medway Youth Trust use predictive and textual analytics to draw insight into their work helping vulnerable children. They use technology to inform expert case workers, not to take decisions on their behalf.)

4. “Wicked problems” cannot be described using data and logic

Despite all of the challenges associated with problems in mathematics and the physical sciences, it is nevertheless relatively straightforward to frame and then attempt to solve problems in those domains; and to determine whether the resulting solutions are valid.

As the failure of Logical Atomism showed, though, problems in the human domain are much more difficult to describe in any systematic, complete and precise way – a challenge known as the “frame problem” in artificial intelligence. This is particularly true of “wicked problems” – challenges such as social mobility or vulnerable families that are multi-faceted, and consist of a variety of interdependent issues.

Take job creation, for example. Is that best accomplished through creating employment in taxpayer-funded public sector organisations? Or by allowing private-sector wealth to grow, creating employment through “trickle-down” effects? Or by maximising overall consumer spending power as suggested by “middle-out” economics? All of these ideas are described not using the language of mathematics or other formal logical systems, but using natural human language which is subjective and inconsistent in use.

The failure of Logical Atomism to fully represent such concepts in formal logical systems through which truth and falsehood can be determined with certainty emphasises what we all understand intuitively: there is no single “right” answer to many human problems, and no single “right” action in many human situations.

(An electricity bill containing information provided by OPower comparing one household’s energy usage to their neighbours. Image from Grist)

5. Behavioural economics and the caprice of human behaviour

Behavioural economics” attempts to predict the way that humans behave when taking choices that have a measurable impact on them – for example, whether to put the washing machine on at 5pm when electricity is expensive, or at 11pm when it is cheap.

But predicting human behaviour is notoriously unreliable.

For example, in a smart water-meter project in Dubuque, Iowa, households that were told how their water conservation compared to that of their near neighbours were found to be twice as likely to take action to improve their efficiency as those who were only told the details of their own water use. In other words, people who were given quantified evidence that they were less responsible water user than their neighbours changed their behaviour. OPower have used similar techniques to help US households save 1.9 terawatt hours of power simply by including a report based on data from smart meters in a printed letter sent with customers’ electricity bills.

These are impressive achievements; but they are not always repeatable. A recycling scheme in the UK that adopted a similar approach found instead that it lowered recycling rates across the community: households who learned that they were putting more effort into recycling than their neighbours asked themselves “if my neighbours aren’t contributing to this initiative, then why should I?”

Low carbon engineering technologies like electric vehicles have clearly defined environmental benefits and clearly defined costs. But most Smart Cities solutions are less straightforward. They are complex socio-technical systems whose outcomes are emergent. Our ability to predict their performance and impact will certainly improve as more are deployed and analysed, and as University researchers, politicians, journalists and the public assess them. But we will never predict individual actions using these techniques, only the average statistical behaviour of groups of people. This can be seen from OPower’s own comparison of their predicted energy savings against those actually achieved – the predictions are good, but the actual behaviour of OPower’s customers shows a high degree of apparently random variation. Those variations are the result of the subjective, unpredictable and sometimes irrational behaviour of real people.

We can take insight from Behavioural Economics and other techniques for analysing human behaviour in order to create appropriate strategies, policies and environments that encourage the right outcomes in cities; but none of them can be relied on to give definitive solutions to any individual person or situation. They can inform decision-making, but are always associated with some degree of uncertainty. In some cases, the uncertainty will be so small as to be negligible, and the predictions can be treated as deterministic rules for achieving the desired outcome. But in many cases, the uncertainty will be so great that predictions can only be treated as general indications of what might happen; whilst individual actions and outcomes will vary greatly.

(Of course it is impossible to predict individual criminal actions as portrayed in the film “Minority Report”. But is is very possible to analyse past patterns of criminal activity, compare them to related data such as weather and social events, and predict the likelihood of crimes of certain types occurring in certain areas. Cities such as Memphis and Chicago have used these insights to achieve significant reductions in crime)

Learning to value insight without certainty

Mathematics and digital technology are incredibly powerful; but they will never perfectly and completely describe and predict our world in human terms. In many cases, our focus for using them should not be on automation: it should be on the enablement of human judgement through better availability and communication of information. And in particular, we should concentrate on communicating accurately the meaning of information in the context of its limitations and uncertainties.

There are exceptions where we automate systems because of a combination of a low-level of uncertainty in data and a large advantage in acting autonomously on it. For example, anti-lock braking systems save lives by using automated technology to take thousands of decisions more quickly than most humans would realise that even a single decision needed to be made; and do so based on data with an extremely low degree of uncertainty.

But the most exciting opportunity for us all is to learn to become sophisticated users of information that is uncertain. The results of textual analysis of sentiment towards products and brands expressed in social media are far from certain; but they are still of great value. Similar technology can extract insights from medical research papers, case notes in social care systems, maintenance logs of machinery and many other sources. Those insights will rarely be certain; but properly assessed by people with good judgement they can still be immensely valuable.

This is a much better way to understand the value of technology than ideas like “perfect knowledge” and “algorithmic regulation”. And it is much more likely that people will trust the benefits that we claim new technologies can bring if we are open about their limitations. People won’t use technologies that they don’t trust; and they won’t invest their money in them or vote for politicians who say they’ll spend their taxes on it.

Thankyou to Richard Brown and Adrian McEwen for discussions on Twitter that helped me to prepare this article. A more in-depth discussion of some of the scientific and philosophical issues I’ve described, and an exploration of the nature of human intelligence and its non-deterministic characteristics, can be found in the excellent paper “Answering Descartes: Beyond Turing” by Stuart Kauffman published by MIT press.

From field to market to kitchen: smarter food for smarter cities

(A US Department of Agriculture inspector examines a shipment of imported frozen meat in New Orleans in 2013. Photo by Anson Eaglin)

One of the biggest challenges associated with the rapid urbanisation of the world’s population is working out how to feed billions of extra citizens. I’m spending an increasing amount of my time understanding how technology can help us to do that.

It’s well known that the populations of many of the world’s developing nations – and some of those that are still under-developed – are rapidly migrating from rural areas to cities. In China, for example, hundreds of millions of people are moving from the countryside to cities, leaving behind a lifestyle based on extended family living and agriculture for employment in business and a more modern lifestyle.

The definitions of “urban areas” used in many countries undergoing urbanisation include a criterion that less than 50% of employment and economic activity is based on agriculture (the appendices to the 2007 revision of the UN World Urbanisation Prospects summarise such criteria from around the world). Cities import their food.

In the developed countries of the Western world, this criterion is missing from most definitions of cities, which focus instead on the size and density of population. In the West, the transformation of economic activity away from agriculture took place during the Industrial Revolution of the 18th and 19th Centuries.

Urbanisation and the industrialisation of food

The food that is now supplied to Western cities is produced through a heavily industrialised process. But whilst the food supply chain had to scale dramatically to feed the rapidly growing cities of the Industrial Revolution, the processes it used, particularly in growing food and creating meals from it, did not industrialise – i.e. reduce their dependence on human labour – until much later.

As described by Population Matters, industrialisation took place after the Second World War when the countries involved took measures to improve their food security after struggling to feed themselves during the War whilst international shipping routes were disrupted. Ironically, this has now resulted in a supply chain that’s even more internationalised than before as the companies that operate it have adopted globalisation as a business strategy over the last two decades.

This industrial model has led to dramatic increases in the quantity of food produced and distributed around the world, as the industry group the Global Harvest Initiative describes. But whether it is the only way, or the best way, to provide food to cities at the scale required over the next few decades is the subject of much debate and disagreement.

(Irrigation enables agriculture in the arid environment of Al Jawf, Libya. Photo by Future Atlas)

One of the critical voices is Philip Lymbery, the Chief Executive of Compassion in World Farming, who argues passionately in “Farmageddon” that the industrial model of food production and distribution is extremely inefficient and risks long-term damage to the planet.

Lymbery questions whether the industrial system is sustainable financially – it depends on vast subsidy programmes in Europe  and the United States; and he questions its social benefits – industrial farms are highly automated and operate in formalised international supply chains, so they do not always provide significant food or employment in the communities in which they are based.

He is also critical of the industrial system’s environmental impact. In order to optimise food production globally for financial efficiency and scale, single-use industrial farms have replaced the mixed-use, rotational agricultural systems that replenish nutrients in soil  and that support insect species that are crucial to the pollination of plants. They also create vast quantities of animal waste that causes pollution because in the single-use industrial system there are no local fields in need of manure to fertilise crops.

And the challenges associated with feeding the growing populations of the worlds’ cities are not only to do with long-term sustainability. They are also a significant cause of ill-health and social unrest today.

Intensity, efficiency and responsibility

Our current food systems fail to feed nearly 1 billion people properly, let alone the 2 billion rise in global population expected by 2050. We already use 60% of the world’s fresh water to produce food – if we try to increase food production without changing the way that water is used, then we’ll simply run out of it, with dire consequences. In fact, as the world’s climate changes over the next few decades, less fresh water will be available to grow food. As a consequence of this and other effects of climate change, the UK supermarket ASDA reported recently that 95% of their fresh food supply is already exposed to climate risk.

The supply chains that provide food to cities are vulnerable to disruption – in the 2000 strike by the drivers who deliver fuel to petrol stations in the UK, some city supermarkets came within hours of running out of food completely; and disruptions to food supply have already caused alarming social unrest across the world.

These challenges will intensify as the world’s population grows, and as the middle classes double in size to 5 billion people, dramatically increasing demand for meat – and hence demand for food for the animals which produce it. Overall, the United Nations Food and Agriculture Organization estimates that we will need to produce 70% more food than today by 2050.

insect delicacies

(Insect delicacies for sale in Phnom Penh’s central market. The United Nations suggested last year that more of us should join the 2 billion people who include insects in their diet – a nutritious and environmentally efficient source of food)

But increasing the amount of food available to feed people doesn’t necessarily mean growing more food, either by further intensifying existing industrial approaches or by adopting new techniques such as vertical farming or hydroponics. In fact, a more recent report issued by the United Nations and partner agencies cautioned that it was unlikely that the necessary increase in available food would be achieved through yield increases alone. Instead, it recommended reducing food loss, waste, and “excessive demand” for animal products.

There are many ways we might grow, distribute and use food more efficiently. We currently waste about 30% of the food we produce: some through food that rots before it reaches our shops or dinner tables, some through unpopularity (such as bread crusts or fruit and vegetables that aren’t the “right” shape and colour), and some because we simply buy more than we need to eat. If those inefficiencies were corrected, we are already producing enough food to feed 11billion people, let alone the 9 billion population predicted for the Earth by 2050.

I think that technology has some exciting roles to play in how we respond to those challenges.

Smarter food in the field: data for free, predicting the future and open source beekeeping

New technologies give us a great opportunity to monitor, measure and assess the agricultural process and the environment in which it takes place.

The SenSprout sensor can measure and transmit the moisture content of soil; it is made simply by printing an electronic circuit design onto paper using commercially-available ink containing silver nano-particles; and it powers itself using ambient radio waves. We can use sensors like SenSprout to understand and respond to the natural environment, using technology to augment the traditional knowledge of farmers.

By combining data from sensors such as SenSprout and local weather monitoring stations with national and international forecasts, my colleagues in IBM Research are investigating how advanced weather prediction technology can enable approaches to agriculture that are more efficient and precise in their use of water. A trial project in Flint River, Georgia is allowing farmers to apply exactly the right amount of water at the right time to their crops, and no more.

Such approaches improve our knowledge of the natural environment, but they do not control it. Nature is wild, the world is uncertain, and farmers’ livelihoods will always be exposed to risk from changing weather patterns and market conditions. The value of technology is in helping us to sense and respond to those changes. “Pasture Scout“, for example, does that by using social media to connect farmers in need of pasture to graze their cattle with other farmers with land of the right sort that is currently underused.

These possibilities are not limited to industrial agriculture or to developed countries. For example, the Kilimo Salama scheme adds resilience to the traditional practises of subsistence farmers by using remote weather monitoring and mobile phone payment schemes to provide affordable insurance for their crops.

Technology is also helping us to understand and respond to the environmental impact of the agricultural practises that have developed in previous decades: as urban beekeepers seek to replace lost natural habitats for bees, the Open Source Beehive project is using technology to help them identify the factors leading to the “colony collapse disorder” phenomenon that threatens the world’s bee population.

Smarter food in the marketplace: local food, the sharing economy and soil to fork traceability

The emergence of the internet as a platform for enabling sales, marketing and logistics over the last decade has enabled small and micro-businesses to reach markets across the world that were previously accessible only to much larger organisations with international sales and distribution networks. The proliferation of local food and urban farming initiatives shows that this transformation is changing the food industry too, where online marketplaces such as Big Barn and FoodTrade make it easier for consumers to buy locally produced food, and for producers to sell it.

This is not to say that vast industrial supply-chains will disappear overnight to be replaced by local food networks: they clearly won’t. But just as large-scale film and video production has adapted to co-exist and compete with millions of small-scale, “long-tail” video producers, so too the food industry will adjust. The need for co-existence and competition with new entrants should lead to improvements in efficiency and impact – the supermarket Tesco’s “Buying Club” shows how one large food retailer is already using these ideas to provide benefits that include environmental efficiences to its smaller suppliers.

(A Pescheria in Bari, Puglia photographed by Vito Palmi)

One challenge is that food – unlike music and video – is a fundamentally physical commodity: exchanging it between producers and consumers requires transport and logistics. The adoption by the food industry of “sharing economy” approaches – business models that use social media and analytics to create peer-to-peer transactions, and that replace bulk movement patterns by thousands of smaller interactions between individuals – will be dependent on our ability to create innovative distribution systems to support them. Zaycon Foods operate one such system, using online technology to allow consumers to collectively negotiate prices for food that they then collect from farmers at regular local events.

Rather than replacing existing markets and supply chains, one role that technology is already playing is to give food producers better insight into their behaviour. M-farm links farmers in Kenya to potential buyers for their produce, and provides them with real-time information about prices; and the University of Bari in Puglia, Italy operates a similar fish-market pricing information service that makes it easier for local fisherman to identify the best buyers and prices for their daily catch.

Whatever processes are involved in getting food from where it’s produced to where it’s consumed, there’s an increasing awareness of the need to track those movements so that we know what we’re buying and eating, both to prevent scandals such as last year’s discovery of horsemeat in UK food labelled as containing beef; and so that consumers can make buying decisions based on accurate information about the source and quality of food. The “eSporing” (“eTraceability”) initiative between food distributors and the Norwegian government explored these approaches following a breakout of E-Coli in 2006.

As sensors become more capable and less expensive, we’ll be able to add more data and insight into this process. Soil quality can be measured using sensors such as SenSprout; plant health could be measured by similar sensors or by video analytics using infra-red data. The gadgets that many of us use whilst exercising to measure our physical activity and use of calories could be used to assess the degree to which animals are able to exercise. And scientists at the University of the West of England in Bristol have developed a quick, cheap sensor that can detect harmful bacteria and the residues of antibiotics in food. (The overuse of antibiotics in food production has harmful side effects, and in particular is leading some bacteria that cause dangerous diseases in humans to develop resistance to treatment).

This advice from the Mayo Clinic in the United States gives one example of the link between the provenance of food and its health qualities, explaining that beef from cows fed on grass can have lower levels of fat and higher levels of beneficial “omega-3 fatty acids” than what they call “conventional beef” – beef from cows fed on grain delivered in lorries. (They appear to have forgotten the “convention” established by several millennia of evolution and thousands of years of animal husbandry that cows eat grass).

(Baltic Apple Pie – a recipe created by IBM’s Watson computer)

All of this information contributes to describing both the taste and health characteristics of food; and when it’s available, we’ll have the opportunity to make more informed choices about what we put on our tables.

Smarter food in the kitchen: cooking, blogging and cognitive computing

One of the reasons that the industrial farming system is so wasteful is that it is optimised to supply Western diets that include an unhealthy amount of meat; and to do so at an unrealistically low price for consumers. Enormous quantities of fish and plants – especially soya beans – that could be eaten by people as components of healthy diets are instead fed to industrially-farmed animals to produce this cheap meat. As a consequence, in the developed world many of us are eating more meat than is healthy for us. (Some of the arguments on this topic were debated by the UK’s Guardian newspaper last year).

But whilst eating less meat and more fish and vegetables is a simple idea, putting it into practise is a complex cultural challenge.

A recent report found that “a third of UK adults struggle to afford healthy food“. But the underlying cause is not economic: it is a lack of familiarity with the cooking and food preparation techniques that turn cheap ingredients into healthy, tasty food; and a cultural preference for red meat and packaged meals. The Sustainable Food School that is under development in Birmingham is one example of an initiative intending to address those challenges through education and awareness.

Engagement through traditional and social media also has an influence. The celebrity chefs that have campaigned for a shift in our diets towards more sustainably sourced fish and the schoolgirl who  provoked a national debate concerning the standard and health of school meals simply by blogging about the meals that were offered to her each day at school, are two recent examples in the UK; as is the food blogger Jack Monroe who demonstrated how she could feed herself and her two-year-old son healthy, interesting food on a budget of £10 a week.

My colleagues in IBM Research have explored turning IBM’s Watson cognitive computing technology to this challenge. In an exercise similar to the “invention test” common to television cookery competitions, they have challenged Watson to create recipes from a restricted set of ingredients (such as might be left in the fridge and cupboards at the end of the week) and which meet particular criteria for health and taste.

(An example of local food processing: my own homemade chorizo.)

Food, technology, passion

The future of food is a complex and contentious issue – the controversy between the productivity benefits of industrial agriculture and its environmental and social impact being just one example. I have touched on but not engaged in those debates in this article – my expertise is in technology, not in agriculture, and I’ve attempted to link to a variety of sources from all sides of the debate.

Some of the ideas for providing food to the world’s growing population in the future are no less challenging, whether those ideas are cultural or technological. The United Nations suggested last year, for example, that more of us should join the 2 billion people who include insects in their diet. Insects are a nutritious and environmentally efficient source of food, but those of us who have grown up in cultures that do not consider them as food are – for the most part – not at all ready to contemplate eating them. Artificial meat, grown in laboratories, is another increasingly feasible source of protein in our diets. It challenges our assumption that food is natural, but has some very reasonable arguments in its favour.

It’s a trite observation, but food culture is constantly changing. My 5-year-old son routinely demands foods such as humus and guacamole that are unremarkable now but that were far from commonplace when I was a child. Ultimately, our food systems and diets will have to adapt and change again or we’ll run out of food, land and water.

Technology is one of the tools that can help us to make those changes. But as Kentaro Toyama famously said: technology is not the answer; it is the amplifier of human intention.

So what really excites me is not technology, but the passion for food that I see everywhere: from making food for our own families at home, to producing it in local initiatives such as Loaf, Birmingham’s community bakery; and from using technology in programmes that contribute to food security in developing nations to setting food sustainability at the heart of corporate business strategy.

There are no simple answers, but we are all increasingly informed and well-intentioned. And as technology continues to evolve it will provide us with incredible new tools. Those are great ingredients for an “invention test” for us all to find a sustainable, healthy and tasty way to feed future cities.

No-one wants top-down, technology-driven cities. They’d be dumb, not smart.

("Visionary City" by William Robinson Leigh)

(William Robinson Leigh’s 1908 painting “Visionary City” envisaged future cities constructed from mile-long buildings of hundreds of storeys connected by gas-lit skyways for trams, pedestrians and horse-drawn carriages. A century later we’re starting to realise not only that developments in transport and power technology have eclipsed Leigh’s vision, but that we don’t want to live in cities constructed from buildings on this scale.)

But “bottom up” is not enough; in order to succeed at scale, grass-roots innovation and localism need support from a new environment of policy, finance, infrastructure and technology.

I took part in a panel discussion last week with Leo Johnson, co-author of “Turnaround Challenge: Business and the City of the Future” (and, coincidentally, the brother of London’s Mayor, Boris Johnson). Leo argued in an impassioned speech that we should avoid overly deterministic “top-down” approaches to developing sustainable cities, and should instead encourage “bottom-up” innovation. His points echoed some of the criticisms levelled at parts of the Smart Cities movement by writers such as Adam Greenfield and Richard Sennett.

But these are arguments against a proposition that I simply don’t think anyone is advocating today.

In all of my contacts across the world, in technology, government and urban design, I don’t know anyone who thinks it would be “smart” for cities to be run wholly by technological systems; who believes that digital data can provide “perfect knowledge” about city systems; or who thinks that cities built and run entirely by deterministic plans driven from the top down would be healthy, vibrant places to live (or indeed are possible at all).

Smart cities are not about putting machines in control, and they are not about imposing an idealistic, corporate way of life. They are simply about harnessing the ever-advancing capabilities of technology in our efforts to create a more sustainable, equitable, resilient world in the cities in which more and more of us are living.

The ultimate purpose of cities is to enable the people who live and work in them to lead safe and rewarding lives with their families. The raw material from which the life of cities is built is therefore small-scale – it is the activity of individual people in their personal and family life or going about their work. Consequently, there is an enormous focus in smart cities and smart urbanism on “bottom-up” thinking : how can we enable private businesses, community innovators and citizen-led initiatives to be successful, and to create sustainable wealth and social value? If the opportunities to do that are widely available, then cities as a whole will be more successful, and, when economic or climate events affect their circumstances, they will be more adaptable and resilient.

But let’s be frank: that’s an awfully big “if”.

There’s nothing new about “bottom-up” creativity – that’s simply what people do as they get on with life, using whatever resources are available to them to craft a living, support their families and build successful businesses. But the truth is that we are not very good at all at creating environments in which everybody has an equal chance of succeeding in those efforts.

For bottom-up creativity to be broadly successful, citizens, communities and businesses must be able to adapt the city infrastructures that provide food, water, energy, transport and resources to serve their specific needs and opportunities. Those infrastructures are vast – they support 3 billion urban lives worldwide today, and will need to scale to support 3 billion more by 2050. Communities and neighbourhoods with persistently low levels of economic activity and social mobility – those most in need of innovative answers to their challenges – are often those who have the least access to those infrastructures, and whose issues can include poor schools, disconnection from transport networks, exclusion from mainstream financial systems, fuel poverty and so on. Those problems will not solve themselves: we will only adapt city infrastructures and institutions to serve these communities better through significant effort from the businesses and governments that control and govern them.

(When planning policy and other regulations allow, urban farms can adapt the physical infrastructure of cities to create new sources of food. A similar combination of policy innovation and grass-roots creativity could enable similarly creative uses of digital infrastructure and information in cities. Photo by ToadLickr)

From the governance of cities, to the policies that affect investment, to the oversight, administration and operation of city infrastructures – these processes work top-down; and in order for us to rely on “bottom-up” creativity improving cities for all of their citizens, we must adapt and improve them to better support that creativity.

Technology plays three roles in this context. Firstly, smartphones, tablets, 3D printers and social media are examples of new consumer and citizen tools that we could barely imagine as recently as a decade ago. They make immense power available to bottom-up, small-scale activity and local innovations, and have resulted in the emergence of significant economic trends such as the “sharing economy” of business models based on peer-to-peer transactions.

Secondly, though, many of those technologies depend fundamentally on the availability of connectivity infrastructure; and that infrastructure is not available everywhere. Some 18% of adults in the UK have never been online; and children today without access to the internet at home and in school are at an enormous disadvantage. Most cities and countries have not yet addressed this challenge. Private sector network providers will not deploy connectivity in areas which are insufficiently economically active for them to make a profit, and Government funding is not yet sufficient to close the gap. This challenge has not and will not be addressed by bottom-up creativity; it requires top-down legislation and investment.

Thirdly, technology can help to open up the operations and infrastructures of big institutions and companies to local innovation – from the provision of “open data” and API interfaces that allow these systems to be adapted to new uses; to the use of technology to measure and trace the social and environmental impact of goods and services in order to inform consumer choice so that it can become a lever to improve the impact of the vast supply chains that supply cities. Unilever and Tesco are just two examples of businesses pursuing this business strategy.

These are the roles of technology that enable a meeting or balance between top-down and bottom-up forces in cities – a balance that Anthony Townsend, author of “Smart Cities: Big Data, Civic Hackers, and the Quest for a New Utopia” has advocated in our online exchanges.

Smart cities is not a prescriptive, top-down, corporate movement. The perception that it was arose because a handful of early and highly visible examples such as Masdar and Songdo were new, large-scale developments financed by strong economic growth in emerging markets; or because some of the rapid urbanisation taking place today is in countries with strongly hierarchical governance. These examples also gave emphasis to the importance of efficiently and intelligently operating large-scale city infrastructures – without which we’ll never sustainably and resiliently support the 6 billion city inhabitants predicted by the United Nations’ World Urbanisation Prospects report by 2050.

(Delegates at Gov Camp 2013 at IBM’s Southbank office, London. Gov Camp is an annual conference which brings together anyone interested in creating new uses of digital technology in public services. Photo by W N Bishop)

But we must give equal recognition to the vast amount of bottom-up creativity that took place throughout this period; that continues today; and which has exploited technology in strikingly innovative ways.

The “open data” movement has become a force for transparency in government and for addressing social and environmental issues. “Civic hacking” communities have sprung up around the world, using this data to create novel new public services. Many of my colleagues have contributed to that movement, either representing IBM, or simply as personal contributions to the cities in which they live – as have the employees of many other businesses. And community initiatives everywhere now routinely exploit technologies such as social media and crowdfunding; or co-create schemes to apply commercial technologies for their own purposes. For example, in the village of Chale on the Isle of Wight, a community with significant levels of fuel poverty worked together to use smart energy meters to reduce their energy bills by up to 50%.

There are two serious challenges in how we apply these ideas more broadly that demand debate:

And:

The Economist magazine reminded us of the importance of those questions in a recent article describing the enormous investments made in public institutions in the past in order to distribute the benefits of the Industrial Revolution to society at large rather than concentrate them on behalf of business owners and the professional classes.

We have only partially been successful in those efforts. As one measure, it’s common for life expectancy to vary by around 20 years between the poorest and richest parts of the same city in the UK. Scandinavian cities do not show that disparity – their culture and system of taxation, benefits and collective insurance create a more equal opportunity to live. In the UK, the US and other societies that emphasise greater retention of private wealth and the distribution of opportunity through flexible market economies, how can we better approach Scandinavia’s level of equality?

These questions are much more important than perpetuating an adversarial debate between “top down” and “bottom up” thinking. No-one wants top-down, technology driven cities. They’d be dumb, not smart. And no-one believes that digital data can provide “perfect knowledge” – we all understand that perfect knowledge is neither possible nor desirable.

Digital data and technology do much more realistic and exciting things. They allow us to uncover the hidden opportunity to transact locally with people and businesses in our community. They reveal patterns in the messy complexity of social, economic, physical and environmental systems that help us to look ahead to likely outcomes, take proactive measures and do more with less. And they make it possible for us to connect to people around the world who we’ve never met but with whom we share an interest or can create a new opportunity.

A smart city creates an environment in which technology, infrastructure, policies and culture make people safe, and provide the resources and opportunities they need – including better access to technology and information – to create safer and more rewarding lives.

That’s not top-down or bottom-up. It’s common sense. Let’s stop arguing and start applying it.

Six ways to design humanity and localism into Smart Cities

(Birmingham’s Social Media Cafe, where individuals from every part of the city share their experience using social media to promote their businesses and community initiatives. Photograph by Meshed Media)

The Smart Cities movement is sometimes criticised for appearing to focus mainly on the application of technology to large-scale city infrastructures such as smart energy grids and intelligent transportation.

It’s certainly vital that we manage and operate city services and infrastructure as intelligently as possible – there’s no other way to deal with the rapid urbanisation taking place in emerging economies; or the increasing demand for services such as health and social care in the developed world whilst city budgets are shrinking dramatically; and the need for improved resilience in the face of climate change everywhere.

But to focus too much on this aspect of Smart Cities and to overlook the social needs of cities and communities risks forgetting what the full purpose of cities is: to enable a huge number of individual citizens to live not just safe, but rewarding lives with their families.

Maslow’s Hierarchy of Needs identifies our most basic requirements to be food, water, shelter and security. The purpose of many city infrastructures is to answer those needs, either directly (buildings, utility infrastructures and food supply chains) or indirectly (the transport systems that support us and the businesses that we work for).

Important as those needs are, though – particularly to the billions of people in the world for whom they are not reliably met – life would be dull and unrewarding if they were all that we aspired to.

Maslow’s hierarchy next relates the importance of family, friends and “self-actualisation” (which can crudely be described as the process of achieving things that we care about). These are the more elusive qualities that it’s harder to design cities to provide. But unless cities provide them, they will not be successful. At best they will be dull, unrewarding places to live and work, and will see their populations fall as those can migrate elsewhere. At worst, they will create poverty, poor health and ultimately short, unrewarding lives.

A Smart City should not only be efficient, resilient and sustainable; it should improve all of these qualities of life for its citizens.

So how do we design and engineer them to do that?

(Maslow’s Hierarchy of Needs, image by Factoryjoe via Wikimedia Commons)

Tales of the Smart City

Stories about the people whose lives and businesses have been made better by technology tell us how we might answer that question.

In the Community Lover’s Guide to Birmingham, for example, Nick Booth describes the way his volunteer-led social media surgeries helped the Central Birmingham Neighbourhood Forum, Brandwood End Cemetery and Jubilee Debt Campaign to benefit from technology.

Another Birmingham initiative, the Northfield Ecocentre, crowdfunded £10,000 to support their “Urban Harvest” project. The funds helped the Ecocentre pick unwanted fruit from trees in domestic gardens in Birmingham and distribute it between volunteers, children’s centres, food bank customers and organisations promoting healthy eating; and to make some of it into jams, pickles and chutneys to raise money so that in future years the initiative can become self-sustaining.

In the village of Chale on the Isle of Wight, a community not served by the national gas power network and with significant levels of fuel poverty, my colleague Andy Stanford-Clark has helped an initiative not only to deploy smart meters to measure the energy use of each household; but to co-design with residents how they will use that technology, so that the whole community feels a sense of ownership and inclusion in the initiative. The project has resulted in a significant drop in rent arrears as residents use the technology to reduce their utility bills, in some cases by up to 50 percent. Less obviously, the sense of shared purpose has extended to the creation of a communal allotment area in the village and a successful compaign to halve bus fares in the area.

There are countless other examples. Play Fitness “gamify” exercise to persuade children to get fit, and work very hard to ensure that their products are accessible to children in communities of any level of wealth.  Casserole Club use social media to introduce people who can’t cook for themselves to people who are prepared to volunteer to cook for others. The West Midlands Collaborative Commerce Marketplace uses analytics technology to help it’s 10,000 member businesses win more than £4billion in new contracts each year. … and so on.

None of these initiatives are purely to do with technology. But they all use technologies that simply were not available and accessible as recently as a few years ago to achieve outcomes that are important to cities and communities. By understanding how the potential of technology was apparent to the stakeholders in such initiatives, why it was affordable and accessible to them, and how they acquired the skills to exploit it, we can learn how to design Smart Cities in a way that encourages widespread grass-roots, localised innovation.

(Top: Birmingham's Masshouse Circus roundabout, part of the inner-city ringroad that famously impeded the city's growth. Bottom: This pedestrian roundabout in Lujiazui, China, constructed over a busy road junction, is a large-scale city infrastructure that balances the need to support traffic flows through the city with the importance that Jane Jacobs first described of allowing people to walk freely about the areas where they live and work. Photo by ChrisUK)

(Top: Birmingham’s Masshouse Circus roundabout, part of the inner-city ringroad that famously impeded the city’s growth until it was demolished. Photo by Birmingham City Council. Bottom: Pedestrian roundabout in Lujiazui, China, constructed over a busy road junction, is a large-scale city infrastructure that balances the need to support traffic flows through the city with the importance that Jane Jacobs first described of allowing people to walk freely about the areas where they live and work. Photo by ChrisUK)

A tale of two roundabouts

History tells us that we should not assume that it will be straightforward to design Smart Cities to achieve that objective, however.

A measure of our success in building the cities we know today from the generations of technology that shaped them – concrete, cars and lifts – is the variation in life expectancy across them. In the UK, it’s common for life expectancy to vary by around 20 years between the poorest and richest parts of the same city.

That staggering difference is the outcome of a complex set of issues including the availability of education and opportunity, lifestyle factors such as diet and exercise, and the accessibility of city services. But a significant influence on many of those issues is the degree to which the large-scale infrastructures built to support our physiological needs and the demands of the economy also create a high-quality environment for daily life.

The photograph on the right shows two city transport infrastructures that are visually similar, but that couldn’t be more different in their influence on the success of the cities that they are part of.

The picture at the top shows Masshouse Circus in Birmingham in 2001 shortly before it was demolished. It was constructed in the 1960s as part of the city’s inner ring-road, intended to improve connectivity to the national economy through the road network. However, the impact of the physical barrier that it created to pedestrian traffic can be seen by the stark difference in land value inside and outside the “concrete collar” of the ring-road. Inside the collar, land is valuable enough for tall office blocks to be constructed on it; whilst outside it is of such low value that it is used as a ground-level carpark.

In contrast, the pedestrian roundabout in Lujiazui, China pictured at the bottom, constructed over a busy road junction, balances the need to support traffic flows through the city with the need for people to walk freely about the areas in which they live and work. As can be seen from the people walking all around it, it preserves the human vitality of an area that many busy roads flow through. 

We should take insight from these experiences when considering the design of Smart City infrastructures. Unless those infrastructures are designed to be accessible to and usable by citizens, communities and local businesses, they will be as damaging as poorly constructed buildings and poorly designed transport networks. If that sounds extreme, then consider the dangers of cyber-stalking, or the implications of the gun-parts confiscated from a suspected 3D printing gun factory in Manchester last year that had been created on general purpose machinery from digital designs shared through the internet. Digital technology has life and death implications in the real world.

For a start, we cannot take for granted that city residents have the basic ability to access the internet and digital technology. Some 18% of adults in the UK have never been online; and children today without access to the internet at home and in school are at an enormous disadvantage. As digital technology becomes even more pervasive and important, the impact of this digital divide – within and between people, cities and nations – will become more severe. This is why so many people care passionately about the principle of “Net Neutrality” – that the shared infrastructure of the internet provides the same service to all of its users; and does not offer preferential access to those individuals or corporations able to pay for it.

These issues are very relevant to cities and their digital strategies and governance. The operation of any form of network requires physical infrastructure such as broadband cables, wi-fi and 4G antennae and satellite dishes. That infrastructure is regulated by city planning policies. In turn, those planning policies are tools that cities can and should use to influence the way in which technology infrastructure is deployed by private sector service providers.

(Photograph of Aesop’s fable “The Lion and the Mouse” by Liz West)

Little and big

Cities are enormous places in which what matters most is that millions of individually small matters have good outcomes. They work well when their large scale systems support the fine detail of life for every one of their very many citizens: when “big things” and “little things” work well together.

A modest European or US city might have 200,000 to 500,000 inhabitants; a large one might have between one and ten million. The United Nations World Urbanisation Prospects 2011 revision recorded 23 cities with more than 10 million population in 2011 (only six of them in the developed world); and predicted that there would be nearly 40 by 2025 (only eight of them in the developed world – as we define it today). Overall, between now and 2050 the world’s urban population will double from 3 billion to 6 billion. 

A good example of the challenges that this enormous level of urbanisation is already creating is the supply of food. One hectare of highly fertile, intensively farmed land can feed 10 people. Birmingham, my home city, has an area of 60,000 hectares of relatively infertile land, most of which is not available for farming at all; and a population of around 1 million. Those numbers don’t add up to food self-sufficiency; and Birmingham is a very low-density city – between one-half and one-tenth as dense as the growing megacities of Asia and South America Feeding the 7 to 10 billion people who will inhabit the planet between now and 2050, and the 3 to 6 billion of them that will live in dense cities, is certainly a challenge on an industrial scale. 

In contrast, Casserole Club, the Northfield Eco-Centre, the Chale Project and many other initiatives around the world have demonstrated the social, health and environmental benefits of producing and distributing food locally. Understanding how to combine the need to supply food at city-scale with the benefits of producing it locally and socially could make a huge difference to the quality of urban lives.

The challenge of providing affordable broadband connectivity throughout cities demonstrates similar issues. Most cities and countries have not yet addressed that challenge: private sector network providers will not deploy connectivity in areas which are insufficiently economically active for them to make a profit, and Government funding is not yet sufficient to close the gap.

In his enjoyable and insightful book “Smart Cities: Big Data, Civic Hackers, and the Quest for a New Utopia“, Anthony Townsend describes a grass-roots effort by civic activists to provide New York with free wi-fi connectivity. I have to admire the vision and motivation of those involved, but – rightly or wrongly; and as Anthony describes – wi-fi has ultimately evolved to be dominated by commercial organisations.  

As technology continues to improve and to reduce in price, the balance of power between large, commercial, resource-rich institutions and small, agile, resourceful  grassroots innovators will continue to changeTechnologies such as Cloud Computing, social media, 3D printing and small-scale power generation are reducing the scale at which many previously industrial technologies are now economically feasible; however, it will remain the case for the foreseeable future that many city infrastructures – physical and digital – will be large-scale, expensive affairs requiring the buying power and governance of city-scale authorities and the implementation resources of large companies.

But more importantly, neither small-scale nor large-scale solutions alone will meet all of our needs. Many areas in cities – usually those that are the least wealthy – haven’t yet been provided with wi-fi or broadband connectivity by either.  

(Cars in Frederiksberg, Copenhagen wishing to join a main road must give way to cyclists and pedestrians)

(A well designed urban interface between people and infrastructure. Cars in Frederiksberg, Copenhagen wishing to join a main road must give way to cyclists and pedestrians passing along it)

We need to find the middle ground between the motivations, abilities and cultures of large companies and formal institutions on one hand; and those of agile, local innovators and community initiatives on the other. The pilot project to provide broadband connectivity and help using the internet to Castle Vale in Birmingham is a good example of finding that balance.

And I am optimistic that we can find it more often. Whilst Anthony is rightly critical of approaches to designing and building city systems that are led by technology, or that overlook the down-to-earth and sometimes downright “messy” needs of people and communities for favour of unrealistic technocratic and corporate utopias; the reality of the people I know that are employed by large corporations on Smart City projects is that they are acutely aware of the limitations as well as the value of technology, and are passionately committed to the human value of their work. That passion is often reflected in their volunteered commitment to “civic hacking“, open data initiatives, the teaching of technology in schools and other activities that help the communities in which they live to benefit from technology.

But rather than relying on individual passion and integrity, how do we encourage and ensure that large-scale investments in city infrastructures and technology enable small-scale innovation, rather than stifle it?

Smart urbanism and massive/small innovation

I’ve taken enormous inspiration in recent years from the architect Kelvin Campbell whose “Massive / Small” concept and theory of “Smart Urbanism” are based on the belief that successful cities emerge from physical environments that encourage “massive” amounts of “small”-scale innovation – the “lively, diversified city, capable of continual, close- grained improvement and change” that Jane Jacobs described in “The Death and Life of Great American Cities“.

We’ll have to apply similar principles in order for large-scale city technology infrastructures to support localised innovation and value-creation. But what are the practical steps that we can take to put those principles into practise?

Step 1: Make institutions accessible

There’s a very basic behaviour that most of us are quite bad at – listening. In particular, if the institutions of Smart Cities are to successfully create the environment in which massive amounts of small-scale innovation can emerge, then they must listen to and understand what local activists, communities, social innovators and entrepreneurs want and need.

Many large organisations – whether they are local authorities or private sector companies – are poor at listening to smaller organisations. Their decision-makers are very busy; and communications, engagement and purchasing occur through formally defined processes with legal, financial and confidentiality clauses that can be difficult for small or informal organisations to comply with. The more that we address these barriers, the more that our cities will stimulate and support small-scale innovation. One way to do so is through innovations in procurement; another is through the creation of effective engagements programmes, such as the Birmingham Community Healthcare Trust’s “Healthy Villages” project which is listening to communities expressing their need for support for health and wellbeing. This is why IBM started our “Smarter Cities Challenge” which has engaged hundreds of IBM’s Executives and technology experts in addressing the opportunities and challenges of city communites; and in so doing immersed them in very varied urban cultures, economies, and issues.

But listening is also a personal and cultural attitude. For example, in contrast to the current enthusiasm for cities to make as much data as possible available as “open data”, the Knight Foundation counsel a process of engagement and understanding between institutions and communities, in order to identify the specific information and resources that can be most usefully made available by city institutions to individual citizens, businesses and social organisations.

(Delegates at Gov Camp 2013 at IBM’s Southbank office, London. Gov Camp is an annual conference which brings together anyone interested in the use of digital technology in public services. Photo by W N Bishop)

In IBM, we’ve realised that it’s important to us to engage with, listen to and support small-scale innovation in its many forms when helping our customers and partners pursue Smarter City initiatives; from working with social enterprises, to supporting technology start-ups through our Global Entrepreneur Programme, to engaging with the open data and civic hacking movements.

More widely, it is often talented, individual leaders who overcome the barriers to engagement and collaboration between city institutions and localised innovation. In “Resilience: why things bounce back“, Andrew Zolli describes many examples of initiatives that have successfully created meaningful change. A common feature is the presence of an individual who shows what Zolli calls”translational leadership“: the ability to engage with both small-scale, informal innovation in communities and large-scale, formal institutions with resources.

Step 2: Make infrastructure and technology accessible

Whilst we have a long way to go to address the digital divide, Governments around the world recognise the importance of access to digital technology and connectivity; and many are taking steps to address it, such as Australia’s national deployment of broadband internet connectivity and the UK’s Urban Broadband Fund. However, in most cases, those programmes are not sufficient to provide coverage everywhere.

Some businesses and social initiatives are seeking to address this shortfall. CommunityUK, for example, are developing sustainable business models for providing affordable, accessible connectivity, and assistance using it, and are behind the Castle Vale project in Birmingham. And some local authorities, such as Sunderland and Birmingham, have attempted to provide complete coverage for their citizens – although just how hard it is to achieve that whilst avoiding anti-competition issues is illustrated by Birmingham’s subsequent legal challenges.

We should also tap into the enormous sums spent on the physical regeneration of cities and development of property in them. As I first described in June last year, while cities everywhere are seeking funds for Smarter City initiatives, and often relying on central government or research grants to do so, billions of Pounds, Euros, and Dollars are being spent on relatively conventional property development and infrastructure projects that don’t contribute to cities’ technology infrastructures or “Smart” objectives.

Local authorities could use planning regulations to steer some of that investment into providing Smart infrastructure, basic connectivity, and access to information from city infrastructures to citizens, communities and businesses. Last year, I developed a set of “Smart City Design Principles” on behalf a city Council considering such an approach, including:

Principle 4: New or renovated buildings should be built to contain sufficient space for current and anticipated future needs for technology infrastructure such as broadband cables; and of materials and structures that do not impede wireless networks. Spaces for the support of fixed cabling and other infrastructures should be easily accessible in order to facilitate future changes in use.

Principle 6: Any development should ensure wired and wireless connectivity is available throughout it, to the highest standards of current bandwidth, and with the capacity to expand to any foreseeable growth in that standard.

(The Birmingham-based Droplet smartphone payment service, now also operating in London, is a Smart City start-up that has won backing from Finance Birmingham, a venture capital company owned by Birmingham City Council)

Step 3: Support collaborative innovation

Small-scale, local innovations will always take place, and many of them will be successful; but they are more likely to have significant, lasting, widespread impact when they are supported by city institutions with resources.

That support might vary from introducing local technology entrepreneurs to mentors and investors through the networks of contacts of city leaders and their business partners; through to practical assistance for social enterprises, helping them to put in place very basic but costly administration processes to support their operations.

City institutions can also help local innovations to thrive simply by becoming their customers. If Councils, Universities and major local employers buy services from innovative local providers – whether they be local food initiatives such as the Northfield Ecocentre or high-tech innovations such as Birmingham’s Droplet smartphone payment service – then they provide direct support to the success of those businesses.

In Birmingham,for example, Finance Birmingham (a Council-owned venture capital company) and the Entrepreneurs for the Future (e4F) scheme provide real, material support to the city’s innovative companies; whilst Bristol’s Mayor George Ferguson and Lambeth’s Council both support their local currencies by allowing salaries to be paid in them.

It becomes more obvious  why stakeholders in a city might become involved in collaborative innovation when they have the opportunity to co-create a clear set of shared priorities. Those priorities can be compared to the objectives of innovative proposals seeking support, whether from social initiatives or businesses; used as the basis of procurement criteria for goods, services and infrastructure; set as the objectives for civic hacking and other grass-roots creative events; or even used as the criteria for funding programmes for new city services, such as the “Future Streets Incubator” that will shortly be launched in London as a result of the Mayor of London’s Roads Task Force.

In this context, businesses are not just suppliers of products and services, but also local institutions with significant supply chains, carbon and economic footprints, purchasing power and a huge number of local employees. There are many ways such organisations can play a role in supporting the development of an open, Smarter, more sustainable city.

The following “Smart City Design Principles” promote collaborative innovation in cities by encouraging support from development and regeneration initiatives:

Principle 12: Consultations on plans for new developments should fully exploit the capabilities of social media, virtual worlds and other technologies to ensure that communities affected by them are given the widest, most immersive opportunity possible to contribute to their design.

Principle 13: Management companies, local authorities and developers should have a genuinely engaging presence in social media so that they are approachable informally.

Principle 14: Local authorities should support awareness and enablement programmes for social media and related technologies, particularly “grass roots” initiatives within local communities.

Step 4: Promote open systems

A common principle between the open data movement; civic hacking; localism; the open government movement; and those who support “bottom-up” innovations in Smart Cities is that public systems and infrastructure – in cities and elsewhere – should be “open”. That might mean open and transparent in their operation; accessible to all; or providing open data and API interfaces to their technology systems so that citizens, communities and businesses can adapt them to their own needs. Even better, it might mean all of those things.

The “Dublinked” information sharing partnership, in which Dublin City Council, three surrounding County Councils and  service providers to the city share information and make it available to their communities as “open data”, is a good example of the benefits that openness can bring. Dublinked now makes 3,000 datasets available to local authority analysts; to researchers from IBM Research and the National University of Ireland; and to businesses, entrepreneurs and citizens. The partnership is identifying new ways for the city’s public services and transport, energy and water systems to work; and enabling the formation of new, information-based businesses with the potential to export the solutions they develop in Dublin to cities internationally. It is putting the power of technology and of city information not only at the disposal of the city authority and its agencies, but also into the hands of communities and innovators.

(I was delighted this year to join Innovation Birmingham as a non-Executive Director in addition to my role with IBM. Technology incubators – particularly those, like Innovation Birmingham and Sunderland Software City, that are located in city centres – are playing an increasingly important role in making the support of city institutions and major technology corporations available to local communities of entrepreneurs and technology activists)

In a digital future, the more that city infrastructures and services provide open data interfaces and APIs, the more that citizens, communities and businesses will be able to adapt the city to their own needs. This is the modern equivalent of the grid system that Jane Jacobs promoted as the most adaptable urban form. A grid structure is the basis of Edinburgh’s “New Town”, often regarded as a masterpiece of urban planning that has proved adaptable and successful through the economic and social changes of the past 250 years, and is also the starting point for Kelvin Campbell’s work.

But open data interfaces and APIs will only be widely exploitable if they conform to common standards. In order to make it possible to do something as simple as changing a lightbulb, we rely on open standards for the levels of voltage and power from our electricity supply; the physical dimensions of the socket and bulb and the characteristics of their fastenings; specifications of the bulb’s light and heat output; and the tolerance of the bulb and the fitting for the levels of moisture found in bathrooms and kitchens. Cities are much more complicated than lightbulbs; and many more standards will be required on order for us to connect to and re-configure their systems easily and reliably.

Open standards are also an important tool in avoiding city systems becoming “locked-in” to any particular supplier. By specifying common characteristics that all systems are required to demonstrate, it becomes more straightforward to exchange one supplier’s implementation for another.

Some standards that Smarter City infrastructures can use are already in place – for example, Web services and REST that specify the general ways in which computer systems interact, and the Common Alerting Protocol which is more specific to interactions between systems that monitor and control the physical world. But many others will need to be invented and encouraged to spread. The City Protocol Society is one organisation seeking to develop those new standards; and the British Standards Institute recently published the first set of national standards for Smarter Cities in the UK, including a standard for the interoperability of data between Smart City systems.

Some open source technologies will also be pivotal; open source (software whose source code is freely available to anyone, and which is usually written by unpaid volunteers) is not the same as open standards (independently governed conventions that define the way that technology from any provider behaves). But some open source technologies are so widely used to operate the internet infrastructures that we have become accustomed to – the “LAMP” stack of operating system, web server, database and web progamming language, for example – that they are “de facto” standards that convey some of the benefits of wide usability and interoperability of open standards. For example, IBM recently donated MQTT, a protocol for connecting information between small devices such as sensors and actuators in Smart City systems to the open source community, and it is becoming increasingly widely adopted as a consequence.

Once again, local authorities can contribute to the adoption of open standards through planning frameworks and procurement practises:

Principle 7: Any new development should demonstrate that all reasonable steps have been taken to ensure that information from its technology systems can be made openly available without additional expenditure. Whether or not information is actually available will be dependent on commercial and legal agreement, but it should not be additionally subject to unreasonable expenditure. And where there is no compelling commercial or legal reason to keep data closed, it should actually be made open.

Principle 8: The information systems of any new development should conform to the best available current standards for interoperability between IT systems in general; and for interoperability in the built environment, physical infrastructures and Smarter Cities specifically.

(The town plan for Edinburgh’s New Town, clearly showing the grid structure that gives rise to the adaptability that it is famous for showing for the past 250 years. Image from the JR James archive)

Finally, design skills will be crucial both to creating interfaces to city infrastructures that are truly useful and that encourage innovation; and in creating innovations that exploit them that in turn are useful to citizens.

At the technical level, there is already a rich corpus of best practise in the design of interfaces to technology systems and in the architecture of technology infrastructures that provide them.

But the creativity that imagines new ways to use these capabilities in business and in community initiatives will also be crucial. The new academic discipline of “Service Science” describes how designers can use technology to create new value in local contexts; and treats services such as open data and APIs as “affordances” – capabilities of infrastructure that can be adapted to the needs of an individual. In the creative industries, “design thinkers” apply their imagination and skills to similar subjects.

Step 5: Provide common services

At the 3rd EU Summit on Future Internet, Juanjo Hierro, Chief Architect for the FI-WARE “future internet platform” project, identified the specific tools that local innovators need in order to exploit city information infrastructures. They include real-time access to information from physical city infrastructures; tools for analysing “big data“; and access to technologies to ensure privacy and trust.

The Dublinked information sharing partnership is already putting some of these ideas into practise. It provides assistance to innovators in using, analysing and visualising data; and now makes available realtime data showing the location and movements of buses in the city. The partnership is based on specific governance processes that protect data privacy and manage the risk associated with sharing data.

As we continue to engage with communities of innovators in cities, we will discover further requirements of this sort. Imperial College’s “Digital Cities Exchange” research programme is investigating the specific digital services that could be provided as enabling infrastructure to support innovation and economic growth in cities, for example. And the British Standards Institute’s Smart Cities programme includes work on standards that will enable small businesses to benefit from Smart City infrastructure.

Local authorities can adapt planning frameworks to encourage the provision of these services:

Principle 9: New developments should demonstrate that they have considered the commercial viability of providing the digital civic infrastructure services recommended by credible research sources.

Step 6: Establish governance of the information economy

From the exponential growth in digital information we’ve seen in recent years, to the emergence of digital currencies such as Bitcoin, to the disruption of traditional industries by digital technology; it’s clear that we are experiencing an “information revolution” just as significant as the “industrial revolution” of the 18th and 19th centuries. We often refer to the resulting changes to business and society as the development of an “information economy“.

But can we speak in confidence of an information economy when the basis of establishing the ownership and value of its fundamental resource – digital information – is not properly established?

(Our gestures when using smartphones may be directed towards the phones, or the people we are communicating with through them; but how are they interpreted by the people around us? “Oh, yeah? Well, if you point your smartphone at me, I’m gonna point my smartphone at you!” by Ed Yourdon)

A great deal of law and regulation already applies to information, of course – such as the European Union’s data privacy legislation. But practise in this area is far less established than the laws governing the ownership of physical and intellectual property and the behaviour of the financial system that underlie the rest of the economy. This is evident in the repeated controversies concerning the use of personal information by social media businesses, consumer loyalty schemes, healthcare providers and telecommunications companies.

The privacy, security and ownership of information, especially personal information, are perhaps the greatest challenges of the digital age. But that is also a reflection of their importance to all aspects of our lives. Jane Jacobs’ description of urban systems in terms of human and community behaviour was based on those concepts, and is still regarded as the basis of our understanding of cities. New technologies for creating and using information are developing so rapidly that it is not only laws specifically concerning them that are failing to keep up with progress; laws concerning the other aspects of city systems that technology is transforming are failing to adapt quickly enough too.

A start might be to adapt city planning regulations to reflect and enforce the importance of the personal information that will be increasingly accessed, created and manipulated by city systems:

Principle 21: Any information system in a city development should provide a clear policy for the use of personal information. Any use of that information should be with the consent of the individual.

The triumph of the commons

I wrote last week that Smarter Cities should be a “middle-out” economic investment – in other words, an investment in common interests – and compared them to the Economist’s report on the efforts involved in distributing the benefits of the industrial revolution to society at large rather than solely to business owners and the professional classes.

One of the major drivers for the current level of interest in Smarter Cities and technology is the need for us to adapt to a more sustainable way of living in the face of rising global populations and finite resources. At large scale, the resources of the world are common; and at local scale, the resources of cities are common too.

For four decades, it has been widely assumed that those with access to common resources will exploit them for short term gain at the expense of long term sustainability – this is the “tragedy of the commons” first described by the economist Garrett Hardin. But in 2009, Elinor Ostrum won the Nobel Prize for economics by demonstrating that the “tragedy” could be avoidedand that a community could manage and use shared resources in a way that was sustainable in the long-term.

Ostrum’s conceptual framework for managing common resources successfully is a set of criteria for designing “institutions” that consist of people, processes, resources and behaviours. These need not necessarily be formal political or commercial institutions, they can also be social structures. It is interesting to note that some of those criteria – for example, the need for mechanisms of conflict resolution that are local, public, and accessible to all the members of a community – are reflected in the development over the last decade of effective business models for carrying out peer-to-peer exchanges using social media, supported by technologies such as reputation systems.

Of course, there are many people and communities who have championed and practised the common ownership of resources regardless of the supposed “tragedy” – not least those involved in the Transition movement founded by Rob Hopkins, and which has developed a rich understanding of how to successfully change communities for the better using good ideas; or the translational leaders described by Andrew Zolli. But Elinor Ostrum’s ideas are particularly interesting because they could help us to link the design, engineering and governance of Smarter Cities to the achievement of sustainable economic and social objectives based on the behaviour of citizens, communities and businesses.

Combined with an understanding of the stories of people who have improved their lives and communities using technology, I hope that the work of Kelvin Campbell, Rob Hopkins, Andrew Zolli, Elinor Ostrum and many others can inspire technologists, urban designers, architects and city leaders to develop future cities that fully exploit modern technology to be efficient, resilient and sustainable; but that are also the best places to live and work that we can imagine, or that we would hope for for our children.

Cities created by people like that really would be Smart.

Creating successful Smart Cities in 2014 will be an economic, financial and political challenge, not an engineering accomplishment

Why insurers, pension funds and politics will be more important to Smart Cities in 2014 than “Living Labs” or technology.

(The 2nd Futurama exhibition at the 1964 New York World’s Fair. In 50 years’ time, how will we perceive today’s visions of Smart Cities? Photo by James Vaughan)

I hope that 2014 will be the year in which we see widespread and large-scale investments in future city technology infrastructures that enable sustainable, equitably distributed economic and social growth. The truth is that we are still in the very early stages of that process.

In 2012 I spoke with a Director at a financial consultancy who’d performed a survey of European Smart City initiatives. She confirmed something that I suspected at the time: that the great majority of Smart City initiatives up to that point in the mature markets of Europe and North America had been financed by research funding, rather than on a commercial basis.

Four trends characterised the subsequent development of Smart Cities throughout 2013. Firstly, emerging markets continued to invest in supporting the rapid urbanisation they are experiencing; and businesses, Universities and national governments in developed nations recognised the commercial opportunity for them to supply that market with “Smart” solutions.

Secondly, it remains the case that the path to growth for undeveloped nations is still extremely slow and complex; so whilst there is private sector and national government interest in investing in those nations – IBM’s new Research centre in Nairobi being an example – many “smart” initiatives are carried out at small scale by local innovators, the third sector or development agencies.

In Europe and North America, a third trend was the continuing announcement of investments by the European Union and national governments in the applied research and innovation agenda in cities – such as the EU’s Horizon 2020 programme, for example.

Perhaps most importantly, though, the final trend was for cities in Europe and North America to start to make investments in the underlying technology platforms for Smart Cities from their own operational budgets, on the basis of their ability to deliver cost savings or improvements in outcomes. For example, some cities are replacing traditional parking management and enforcement services with “smart parking” schemes that are reducing congestion and pollution whilst paying for themselves through improved revenues. Others are investing their allocation of central government infrastructure funds in Smart solutions – such as Cambridge, Ontario’s use of the Canadian government’s Gas Tax Fund to invest in a sensor network and analytics infrastructure to manage the city’s physical assets intelligently.

This trend to create business cases for investment from normal operating budgets or infrastructure investment programmes is important not only because it shows that these cities are developing the business models to support investment in “Smart” solutions locally, where the finances associated with rapid economic growth and urbanisation are not present; but also because (at the risk of simplifying a challenging and complex issue) some of those business models might serve as a template for self-sustainable adoption in less developed nations.

(Downtown Cambridge, Ontario. Photo by Justin Scott Campbell)

Whilst the idea of a “Smart City” has been capturing the imagination for several years now, the reality is that many cities are still deciding what that idea might mean for them. For example, London’s “Smart London Board” published it’s Smart London plan in December, following Birmingham’s Smart City Commission report earlier in the year. And most cities who are considering such plans now or who have recently published them are still determining how to put the finance in place to carry them out.

Will “Living Labs” be the death of Smart Cities?

A concept that I see in many such plans that is intended to assist in securing finance, but that I think risks being a distraction from addressing it properly, is the “Living Lab”. 

Living labs emerged as a set of best practises for carrying out applied research into consumer or citizen services with a focus on collaborative, user-centred design and co-creation. Many cities are now seeking to win funding for their Smarter Cities initiatives by offering themselves as “Living Labs” in which consortia constructing proposals for applied research funding can carry out their activities.

The issue is not that Living Lab’s aren’t a good idea – on the contrary, they are undoubtably a very good set of prescriptions for carrying out such research and design successfully. The problem is that there are now so many cities intending to follow this approach that it no longer makes them stand out as particularly effective environments in which to perform research.

Research programmes will continue to fund the first deployments of new Smart City ideas and technology; but competition for those funds will be fierce. Cities, universities and companies that bid for them will invest many months – often more than a year – in developing their proposals; and in competitions, most entrants do not win.

The real need in cities is for the development and regeneration of infrastructure. There are certainly research topics concerning infrastructure that will attract funding from national and international government bodies; but those funds will not support the rollout of citywide infrastructure to every city in every country.

(Birmingham's new city-centre tram)

(Birmingham’s new city-centre tram is an infrastructure investment that will contribute to the same objectives as the city’s Smart City vision.)

The big questions for European and American cities in 2014 are then:

Will they continue to invest resources competing for applied research and innovation funding, limiting the speed at which the widespread deployment of new infrastructure will take place?

Or will they focus on developing independently viable business cases for investment in the infrastructure to support their
Smarter City visions?

There’s a real need for clarity about these issues. Whilst the enormous level of innovation funding being made into smart buildings, smart transport and smart cities by the EU Horizon 2020 programme and national equivalents such as the UK’s Technology Strategy Board will stimulate the field and fund important demonstration projects that deliver real value, these bodies will not pay for all of our cities to become Smarter.

The same is true for the research investments made by commercial organisations including technology companies such as IBM. Commercial research investments fund the first attempts to apply technology to solve problems or achieve objectives in new ways; those that succeed are subsequently deployed elsewhere on a commercial basis.

The risk is that in seeking investment from research programmes, we become distracted from addressing the real challenge: how to make the case for private sector investment in new technology infrastructures based on the economic and social improvements they will enable; or on the direct financial returns that they will generateIn the UK, for example, a specialist body in Government, Infrastructure UK, coordinates private sector funding for public infrastructure. And if we can persuade property developers of the value of “Smart” technologies, then cities could benefit from the enormous investments made in property every year that currently don’t result in the deployment of technology – the British Property Federation, for example, estimate that £14 billion is invested in the development of new space in the UK each year.

(This pedestrian roundabout in Lujiazui, China, constructed over a busy road junction, is a large-scale city infrastructure that balances the need to support traffic flows through the city with the importance that Jane Jacobs first described of allowing people to walk freely about the areas where they live and work. Photo by ChrisUK)

This is an opportunity we should treat with urgency. Whilst public sector finances are under immense pressure, the vast wealth held in private investment funds is seeking new opportunities following the poor returns that many traditional forms of investment have yielded over the last few years. There is a lot of work to do between the stakeholders in cities, government and finance before these investment sources can be exploited by Smart Cities – not least in agreeing reasonable expectations for how the risks and returns will be measured and shared. But I personally believe that until we do so, we will not be able to properly finance the development of our next generation of cities.

As Jane Jacobs wrote in her seminal 1961 work “The Death and Life of Great American Cities“:

“Private investment shapes cities, but social ideas (and laws) shape private investment. First comes the image of what we want, then the machinery is adapted to turn out that image. The financial machinery has been adjusted to create anti-city images because, and only because, we as a society thought this would be good for us. If and when we think that lively, diversified city, capable of continual, close-grained improvement and change, is desirable, then we will adjust the financial machinery to get that.”

Overcoming these challenges won’t be easy, and doing so will require each of the various stakeholder organisations facing them to take bold steps this year.

Local Government

Whilst their finances throughout the developed world have been under severe pressure for a long time now, local government bodies are still responsible for procuring a significant volume of goods and services. Smart Cities will only become a reality when local authority visions for the future are reflected in procurement practises and scoring criteria for contracts issued today. It’s only very recently that procurements for contracts to build, update and manage physical infrastructures such as roads and pavements have been based on outcomes such as minimising congestion or increasing the overall quality of performance throughout the lifetime of the asset within the contract value, rather than on securing the maximum volume of concrete (or number of traffic wardens).

Outcomes-based procurements are challenging to be sure, both for the purchaser and the provider; especially so when they are for such new solutions. But service and infrastructure providers will only be motivated to propose and deliver innovative, smart solutions when they’re rewarded for doing so.

Local authorities can also exploit indirect mechanisms such as planning and development frameworks. I worked last year with one authority which asked how its planning framework should evolve in order to promote the development of a “Smart City”, and published a set of 23 “Design principles for a Smarter City” as a result. They require that investments in property also deliver technology infrastructures such as wi-fi, broadband, open-data, and multi-channel self-service access.

(An analysis based on GPS data from mobile phones of end-to-end journeys undertaken by users of Abidjan’s bus services. By comparing existing bus routes to end-to-end journey requirements, the analysis identified four new bus routes and led to changes in many others. As a result, 22 routes now show increased ridership, and city-wide journey times have decreased by 10%. The techniques and technologies behind the project build on those developed for projects in Dubuque, Istanbul and Dublin.)

Private Sector

The technology companies associated with Smart Cities have sometimes been criticised for focussing too much on the technology that can be applied to city infrastructures, and not enough on the improvements to people’s work and lives that technology can enable, or on the business cases for investing in it.

To make the business case clearer, my colleague the economist Mary Keeling has been working for IBM’s Institute for Business Value to more clearly analyse and express the benefits of Smart approaches – in water management and transportation, for example. And I’ll be contributing along with representatives from many of the other companies that provide technology and infrastructure for Smart Cities to the TSB’s Future Cities Catapult’s finance initiative.

But we also need to respect the principles of Living Labs and the experience of urban designers – not least the writing of Jane Jacobs – which reflect that our starting point for thinking about Smart Cities should be the everyday lives and experiences of individual citizens in their family lives; at work; and moving through cities. In one sense, this is business as usual in the technology industry – “user-centered design“, “use cases” and “user stories” have been at the heart of software development since the 1980s. So one of our challenges is simply to communicate that approach more clearly within our descriptions of Smart Cities. This is a topic I’ve written about in many articles on this blog that you can find described in “7 Steps to a Smarter City“; and that I tried to address in IBM’s new Smarter Cities video.

The other challenge is for technology companies to become more familiar and expert in the disciplines associated with good quality urban design – town planning, architecture, social science and the psychology of human behaviour, for example. This is one of the reasons why IBM started the “Smarter Cities Challenge” programme through which we have donated our technology expertise to 100 cities worldwide to help them address the opportunities and challenges they face; and in so doing become more familiar with their very varied cultures, economies, issues and capabilities. It’s also why I joined the Academy of Urbanism, along with representatives of several other technology companies.

We also need to embrace the “Smart Urbanism” thinking exemplified by Kelvin Campbell. Kelvin’s “Massive / Small” approach is intended to design large-scale urban infrastructures that encourage and support “massive” amounts of “small-scale” innovation. I think that’s an extremely powerful idea that we should embrace in Smarter Cities; and that translates directly to the practise of providing open-standard, public interfaces to city technology infrastructures – open data feeds and APIs (“Application Programming Interfaces”), for example – that not only reduce the risk that city systems become “locked-in” to any proprietary provider; but that also open up the power of large scale technology systems and “big data” sources so that local businesses, innovators and communities are able to adapt public infrastructures to their own needs. I think of these interfaces as creating an “innovation boundary” between a city’s infrastructure and its stakeholders.

(George Ferguson, Mayor of Bristol, one of the few cities in the UK with an elected Mayor with significant authority and responsibility. His salary is paid in the city’s local currency, the Bristol Pound, rather than in the national currency. His red trousers are famous. Photo by PaulNUK)

Central Government

In most countries in the developed world – i.e. those which are not being driven by rapid urbanisation today because they urbanised during the Industrial Revolution – the majority of Smart City initiatives that have momentum are driven by Mayors convening city stakeholders and institutions to co-create, finance and deliver those initiatives. Correspondingly, in countries without strong mayoral systems – such as the UK – progress can be slower. Worryingly, Centre for Cities’ recent Outlook 2014 report pointed out that only 17% of funding for UK cities comes from locally administered taxation, as opposed to the OECD average of 55%.

To risk stating the obvious, every city is different, and different in very many important ways, from its geographical situation to its linkage to national and international transport infrastructure; from its economic and business capabilities to the skills and wealth of its population; from its social challenges and degree of social mobility to its culture and heritage. Successful Smart City initiatives are specific, not generic; and the greater degree of autonomy that cities are allowed in setting strategy and securing financing, the greater their capability to pursue those initiatives. Programmes such as “City Deals” and the recent reforms resulting from Lord Heseltine’s “No Stone Unturned” report are examples of progress towards greater autonomy for the UK’s cities, but they are not enough.

Central government will always have a significant role in funding the infrastructures that cities rely on, of course; whether that’s national infrastructures that connect cities (such as the planned “HS2” high-speed train network in the UK, or Australia’s national deployment of broadband internet connectivity), or specific infrastructures within cities, such as Birmingham’s new city-centre tram. And so just as local governments should consider how they can use procurement practises and planning frameworks to encourage investments in property and infrastructure that deliver “Smart” solutions, so central government should consider how the funding programmes that it administers can contribute to cities’ “Smart” objectives.

Financial Services

If the challenge is to unlock investment in new assets and outcomes, then we should turn to banks, insurers and investors to help us shape the new financial vehicles that we will require to do so. In Canada, for example, a collaboration between Canadian insurers and cities has developed a set of tools to create a common understanding of the financial risk created by the effects of climate change on the resilience of city infrastructures. These tools are the first step towards creating investment and insurance models for city infrastructures that will be exposed to new levels of risk; that will need to exhibit new levels of resilience; and that in turn may require Smart solutions to achieve them.

(Luciana Berger, Shadow Minister for Energy and Climate Change pictured talking to Northfield, Birmingham resident Abraham Weekes and James McKay, Birmingham City Council’s Cabinet Member for a Green, Safe and Smart city. Abraham lives in the house pictured, which has been fitted with exterior house covering, solar panels and energy efficient windows through the Birmingham Energy Savers scheme. Photo by Birmingham City Council)

More internationally, the “Little Rock Accord” between the Madrid Club of former national Presidents and Prime Ministers and the P80 group of pension funds agreed to create a task force to increase the degree to which pension and sovereign wealth funds invest in the deployment of technology to address climate change issues, shortages in resources such as energy, water and food, and sustainable, resilient growth. And more locally, I’m proud to note that my home city of Birmingham is a pioneer in this area through the Birmingham Energy Savers project, financed through a mixture of prudential borrowing and private sector investment.

It has taken us too long to get to this point, but I’m encouraged that several initiatives are now convening discussions between the traditionally understood stakeholders in Smart Cities – local authorities, technology companies, universities and built-environment companies – and the financial sector. For example, in addition to the Future Cities Catapult’s financing programme, on March 13th, I’ll be speaking at an event organised by the Lord Mayor of the City of London to encourage the City’s financial institutions and UK city authorities to undertake a similar collaboration to develop new financing models for future city infrastructures.

Are Smarter Cities a “middle out” economic intervention?

In his 2011 Presidential Campaign speech Barack Obama promised an economic strategy based on “middle-out” economics – the philosophy that equitable, sustainable growth is driven by the spending power of middle class consumers, as an alternative to “trickle-down” economics – the philosophy that growth is best created when very rich “wealth-creators” are free to become as successful as possible.

As this analysis in “The Atlantic” shows, job creation does depend on the investments of the wealthiest; but also on the spending power of the masses; and on a lot of very hard work making sure that a reasonable portion of the profits created by both of those activities are used to invest in making skills, education and opportunity available to all. The Economist magazine made the same point in a recent article by reminding us of the enormous investments made into public institutions in the past in order to distribute the benefits of the Industrial Revolution to society at large rather than concentrate them on behalf of business owners and the professional classes; though with only partial success.

(The discussion group at the #SmartHack event in Birmingham)

(The discussion group at the #SmartHack event in Birmingham, described in “Tea, trust and hacking – how Birmingham is getting Smarter“, photographed by Sebastian Lenton)

 Those ideas are reflected in what it takes to craft an investment in a technology-enabled Smart City initiative that successfully creates social and economic improvements in a city.

Whilst a huge number of effective “Smart” ideas will be created “bottom-up” by innovators and social entrepreneurs intimately familiar with specific local communities and context, those ideas will not succeed as well or rapidly as we need them to without significant investment in new infrastructures – such as wi-fi, broadband and realtime open data – that are deployed everywhere, not just in the most economically active areas of cities that reward commercial investment most quickly. Accessibility to these infrastructures creates the “innovation boundary” between city institutions and infrastructures, and local innovators and communities.

This is not an abstract concept; it is an idea that some cities are making very real today. For example, the “Dublinked” information-sharing partnership between Dublin County Council, three surrounding County Councils and the National University of Ireland now makes available 3,000 city datasets as “open data” – including a realtime feed showing the location of buses in the city. That’s a resource that local innovators can use to create their own new applications and services. Similarly, in Birmingham the “West Midlands Open Data Forum” has emerged as a community in which city local businesses and innovators can negotiate access to data held by city institutions and service providers.

(David Willets, MP, Minister for Universities and Science, launches the UK Government’s Smart Cities Forum)

At launch of the UK Government’s “Smart Cities Forum” last year, I remarked that we were not inviting key stakeholders to the Smarter Cities debate – specifically, banks, investors, insurers and entrepreneurs. Some of the initiatives I’ve described in this article are starting to address that omission; and to recognise that the most significant challenges are to do with finance, politics, social issues and economics, not engineering and technology.

And those are challenges that all of us should focus on. No-one is going to pay for our cities to become Smarter, more successful, more sustainable and fairer: we will have to figure out how to pay for  those things ourselves.

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