Throughout history, cities have faced many problems: War and violence, disease, disasters, housing, utilities, traffic, crime, inequality, poverty, and greed. Moreover, the pace of population growth in cities is frightening. Every day, urban population increases by almost 150,000 – mostly poor – people, due to migration or births. Between to date and 2050, the world’s urban population is projected to rise from 3.6 billion to 6.3 billion residents.
The litany of problems affects all cities in the world, but not in the same degree. To cope with these problems, each city must make a diagnose of its own challenges and define solutions.
City-life is complex and most afore-mentioned problems are related and often at odds, think about struggling poverty and reversing global heating. Therefore, these problems cannot be solved in separated silos. This is the reason reason that I reject reductionist approaches like ‘smart city’, ‘sharing city’, ‘circular city’ and the like.
Instead, framing the challenges that cities face must start from the complexity of the city as such and the interrelations of people causing these problems. In this respect, I found the concept of a doughnut economy particularly helpful. It is elaborated by the British economist Kate Raworth in a report entitled A Safe and Just Space for Humanity. The report takes the simultaneous application of social and environmental sustainability as the point of department for humane behavior.
In essence, Raworth says that people have a great deal of freedom in the choice of activities in their city, if they stay within two types of boundaries:
The first limit is set by ecosystems; which make life on earth possible. However, we can also frustrate their operation, which has a direct impact on our living conditions.
Something similar applies to society. Here you can also distinguish several aspects and each of them has a level that people should not fall below, the second limit. If this does happen, it will jeopardize the survival of society.
If you look at a donut, you will see a small circle in the center and a large circle on the outside. The small circle represents the social foundation, the lower limit of the quality of society. The large circle refers to the ecological ceiling. Between the two circles lies the space within which people can act as they please. Kate Raworth calls this space a safe and just space for humanity.
On the way to a city for humanity , what we need to do is, first of all, to define human actions that comply with or are threatening the ecological ceiling and social foundation of our own city. What follows is the formulation of targets to correct and subsequently enforce all actual violations of ecological and social boundaries. This applies to the city itself and the global effects of its activities.
As an exercise, I created a table of principles for 10 clusters of activities to address the challenges that many cities in developed countries share, combined with one target for each principle. You may want to download this table here.
I recommend this procedure to any city that intends to develop an integral vision starting from the complexity of city life and the interdependency of its activities. Amsterdam went through this process, together with Kate Raworth. The Amsterdam city donut is worth exploring closely.
This post based on by the new e-book Better cities, the contribution of digital technology. Interested? Download the book here for free (90 pages)
Content:
Hardcore: Technology-centered approaches
1. Ten years of smart city technology marketing
2. Scare off the monster behind the curtain: Big Tech’s monopoly
Towards a humancentric approach
3. A smart city, this is how you do it
4. Digital social innovation: For the social good
Misunderstanding the use of data
5. Digital twins
6. Artificial intelligence
Embedding digitization in urban policy
7. The steps to urban governance
8. Guidelines for a responsible digitization policy
9. A closer look at the digitization agenda of Amsterdam
10. Forging beneficial cooperation with technology companies
Applications
11. Government: How digital tools help residents regaining power?
12. Mobility: Will MaaS reduce the use of cars?
13. Energy: Smart grids – where social and digital innovation meet
14. Healthcare: Opportunities and risks of digitization
Most adepts of the smart city-idea suggest a tight link between technology and the wellbeing of the citizens, symbolizing a new kind of technology-led urban utopia. They promise the solution to many urban problems, including crime, traffic congestion, inefficient services and economic stagnation, or a healthy life for all.
Siemens makes the strongest and most explicit statement of the philosophical underpinnings of the smart-city: Several decades from now cities will have countless autonomous, intelligently functioning IT systems that will have perfect knowledge of users’ habits and energy consumption and provide optimum service…The goal of such a city is to optimally regulate and control resources by means of autonomous IT systems[1].
It is unmistakably that business leaders, having in mind a multi-billion smart city technologies market overstate the benefits of technology, despite many examples that prove otherwise. Therefore, according to The Economist it is not surprising that a ‘techlash’ is underway: The monopolistic dominance of behemoths like Google, Amazon and Facebook and their treatment of sensitive data, the lack of transparency and accountability of algorithm-based decision making, the aversion of the gig economy are major drivers.
Neglecting the human component is by far the worst mistake any aspiring smart city can make. If these future smart cities aim for efficiency, they just cannot be planned without the community. Robert Holland wrote: The real smart city has to begin to think with its collective social and political brain, rather than through its technological tools….. It is made up of myriads of initiatives where technology is used to empower community networks, to monitor equal access to urban infrastructures or scale up new forms of sustainable living.
A human-centric turn of the smart city narrative starts from the problems that citizens and their representatives experience. Then possible solutions are discussed and finally these solutions are specified, the role of technology included.
This post is based on the new e-book Better cities, the contribution of digital technology. Interested? Download the book here for free (90 pages)
Content:
Hardcore: Technology-centered approaches
1. Ten years of smart city technology marketing
2. Scare off the monster behind the curtain: Big Tech’s monopoly
Towards a humancentric approach
3. A smart city, this is how you do it
4. Digital social innovation: For the social good
Misunderstanding the use of data
5. Digital twins
6. Artificial intelligence
Embedding digitization in urban policy
7. The steps to urban governance
8. Guidelines for a responsible digitization policy
9. A closer look at the digitization agenda of Amsterdam
10. Forging beneficial cooperation with technology companies
Applications
11. Government: How digital tools help residents regaining power?
12. Mobility: Will MaaS reduce the use of cars?
13. Energy: Smart grids – where social and digital innovation meet
14. Healthcare: Opportunities and risks of digitization
Wrapping up: Better cities and technology
15. Two 100 city missions: India and Europe
Epilogue: Beyond the Smart City
[1] Cited in: Adam Greenfeld: Against the smart city. A pamphlet
I suggest that anybody who is talking about ‘big data’ and ‘data driven policy’ or using grotesque statements like data is the new oil to revisit the foundations of scientific research and the embedded vision on data.
Without elementary insight in the way scientists arrive at their conclusions ‘data driven policy’ can have disastrous consequences. The city of Chattanooga has build a digital twin. That is a digital model that is connected to reality with the help of sensors. Such a dynamic model can be used for simulation purposes if the connections between the variables have been established. Here things can go wrong. In Chattanooga the model was used to simulate the impact of flexible lane assignment and traffic light phasing. It turned out that this could result in a 30% decrease of congestion.
Had this experiment been carried out in the real world, the result would probably have been disastrous. Traffic experts note time and again that every newly opened road gets satiated after a short time, while the traffic on other roads hardly decreases. In econometrics this phenomenon is called induced demand. In a study of urban traffic patterns between 1983 and 2003, economists Gilles Duranton and Matthew Turner found that car use increases proportionally with the growth of road capacity: Every road user reacts differently to the opening or closing of a road. Those reactions can be to move the ride to another time, to use a different road, to ride with someone else, to use public transport or to cancel the ride. To understand this pattern data must be collected from e sufficient large sample of road behavior of individual drivers.
What the computer scientist in Chattanooga did wrong is assuming that only the adding of a single lane and changing the intervals of the traffic lights would cause all drivers’ behavior change into the same direction, as if they were metal balls, reacting upon a change in the magnetic field. If the ICT-experts had collaborated with traffic experts, the digital twin might have been fed with an empirical justifiable model, that incorporates the assumption of induced demand.
In essence, data is useless without a theory, based on already established insights or views.
This post based on by the new e-book Better cities, the contribution of digital technology. Interested? Download the book here for free (90 pages)
Content:
Hardcore: Technology-centered approaches
1. Ten years of smart city technology marketing
2. Scare off the monster behind the curtain: Big Tech’s monopoly
Towards a humancentric approach
3. A smart city, this is how you do it
4. Digital social innovation: For the social good
Misunderstanding the use of data
5. Digital twins
6. Artificial intelligence
Embedding digitization in urban policy
7. The steps to urban governance
8. Guidelines for a responsible digitization policy
9. A closer look at the digitization agenda of Amsterdam
10. Forging beneficial cooperation with technology companies
Applications
11. Government: How digital tools help residents regaining power?
12. Mobility: Will MaaS reduce the use of cars?
13. Energy: Smart grids – where social and digital innovation meet
14. Healthcare: Opportunities and risks of digitization
Artificial intelligence is the ‘independent construction of pattern in large datasets by computers’. Still, people hold an important role in this. This role consists in the first place in writing an instruction – an algorithm – and then in the composition of a training set, a selection of many examples, for example of animals that are labeled as dog or cat and if necessary, lion or tiger and more. In essence, the computer looks for statistically significant similarities in whatever data, provided by the operator, to predict the probability that some relation will exist or phenomenon will occur.
If computers are learned to make judgement about people, things can go terribly wrong. The St. George Hospital Medical School in London has employed disproportionately many white males for at least a decade because the ‘learning set’ reflected the incumbent staff. The learning set itself represented the bias of those who selected it.
The fight against crime in the United States, has been the scene of artificial intelligence’s abuse for years. The two most used techniques that resulted are predictive policing (PredPol) and facial recognition. In the case of predictive policing, patrols are given directions in which neighborhood or even street they should patrol at a given moment because computers have calculated that the risk of crimes (vandalism, burglary, violence) is highest then.
Predictive policing and facial recognition are based on a “learning set” of thousands of “suspicious” individuals. At one point, New York police had a database of 48,000 individuals. 66% of those were black, 31.7% were Latino and only 1% were white. The composition of this dataset was completely biases, and therefore the computerized ‘decisions’ ware biased too. Even worse is that the final ‘decisions’ made by the computer cannot be explained, and the underlying process is a blackbox. This is a serious ethical issue and the reason why many demand to forbit the application of artificial intelligence.
Bias is not the only thing. In so-called fight against crime the computer calculates on request the chances that crime would happen at a certain time and in a certain place. But if the client exchanged the dominant paradigm of identifying, prosecuting and incarcerating criminals for that of finding potential offenders in a timely manner and giving them the help, they need? A large proportion of those arrested by the police in the US are addicted to drugs or alcohol and severely mentally disturbed. The University of Chicago Data Science for Social Good Program used artificial intelligence to analyze a database of 127,000 people. The aim was to find out, based on historical data, which of those involved was most likely to be arrested within a month. This is not with the intention of hastening an arrest with predictive techniques, but instead to offer them targeted medical assistance. This program was picked up in several cities and in Miami it resulted in a 40% reduction in arrests and the closing of an entire prison.
AI means computer power. Intelligence resides in those who are using this power. Less biased application of artificial intelligence depends on the through-out choice of the connections in the learning sets. These connections must be scientifically validated and approved by scholars with different backgrounds instead of police officers or computer scientists.
This post is based on the new e-book Better cities, the contribution of digital technology. Interested? Download the book here for free (90 pages)
Content:
Hardcore: Technology-centered approaches
1. Ten years of smart city technology marketing
2. Scare off the monster behind the curtain: Big Tech’s monopoly
Towards a humancentric approach
3. A smart city, this is how you do it
4. Digital social innovation: For the social good
Misunderstanding the use of data
5. Digital twins
6. Artificial intelligence
Embedding digitization in urban policy
7. The steps to urban governance
8. Guidelines for a responsible digitization policy
9. A closer look at the digitization agenda of Amsterdam
10. Forging beneficial cooperation with technology companies
Applications
11. Government: How digital tools help residents regaining power?
12. Mobility: Will MaaS reduce the use of cars?
13. Energy: Smart grids – where social and digital innovation meet
14. Healthcare: Opportunities and risks of digitization
In 2009, IMB launched a global marketing campaign around the previously little-known concept of ‘smart city’ with the aim of making city governments receptive to ICT applications in the public sector. The initial emphasis was on process control. Emerging countries were interested in the first place: Many made plans to build smart cities ‘from scratch’, in the first place to attract foreign investors. The Korean city of Songdo, developed by Cisco and Gale International, is a well-known example.
The emphasis soon shifted from process control to using data from the residents themselves. Google wanted to supplement its already rich collection of data with data that city dwellers provide with their mobile phones to create a range of new commercial applications. Its sister company Sidewalk Labs, which was set up for that purpose, started developing a pilot project in Toronto. That failed, partly due to the growing resistance to the prospective violation of privacy. This opposition has had global repercussions and resulted in many countries in legislation to protect privacy.
The rapid development of digital technologies, such as artificial intelligence, gave further impetus to discussion about the ethical implications of technology. Especially in the US, applications in facial recognition and predictive police were heavily criticized.
This current situation – particularly in the Netherlands – can be characterized on the one hand by the development of regulations to safeguard ethical principles and on the other by the search for responsible applications of digital technology.
The question is therefore how useful the term ‘smart city’ is. Touria Meliani, alderman of Amsterdam, prefers to speak of ‘wise city’ than of ‘smart city’ to emphasize that she is serious about putting people first. But instead of introducing other adjectives, skipping them all is better.
The best way to understand human life in the city is respecting the complexity of the city and life within it. Exactly because of the city’s complexity, the use of reductionist adjectives such as ‘smart’, ‘sharing’, circular, climate-neutral’, ‘resilient’ is better omitted. The doughnut-principle is the best way to analyze the city from different perspectives and to define the way people can live in a social and ecological sustainable way, the use of digital technology included.
This post based on by the new e-book Better cities, the contribution of digital technology. Interested? Download the book here for free
I am a happy user of a Sonos sound system. Nevertheless, the helpdesk must be involved occasionally. Recently, it knew within five minutes that my problem was the result of a faulty connection cable between the modem and the amplifier. As it turned out, the helpdesk was able to remotely generate a digital image of the components of my sound system and their connections and saw that the cable in question was not transmitting any signal. A simple example of a digital twin. I was happy with it. But where is the line between the sense and nonsense of collecting masses of data?
What is a digital twin
A digital twin is a digital model of an object, product, or process. In my training as a social geographer, I had a lot to do with maps, the oldest form of ‘twinning’. Maps have laid the foundation for GIS technology, which in turn is the foundation of digital twins. Geographical information systems relate data based on geographical location and provide insight into their coherence in the form of a model. If this model is permanently connected to reality with the help of sensors, then the dynamics in the real world and those in the model correspond and we speak of a ‘digital twin’. Such a dynamic model can be used for simulation purposes, monitoring and maintenance of machines, processes, buildings, but also for much larger-scale entities, for example the electricity grid.
From data to insight
Every scientist knows that data is indispensable, but also that there is a long way to go before data leads to knowledge and insight. That road starts even before data is collected. The first step is assumptions about the essence of reality and thus the possibility of knowing it. There has been a lot of discussion about this within the philosophy of science, from which two points of view have been briefly crystallized, a systems approach and a complexity approach.
The systems approach assumes that reality consists of a stable series of actions and reactions in which law-like connections can be sought. Today, almost everyone assumes that this only applies to physical and biological phenomena. Yet there is also talk of social systems. This is not a question of law-like relationships, but of generalizing assumptions about human behavior at a high level of aggregation. The homo economicus is a good example. Based on such assumptions, conclusions can be drawn about how behavior can be influenced.
The complexity approach sees (social) reality as the result of a complex adaptive process that arises from countless interactions, which – when it comes to human actions – are fed by diverse motives. In that case it will be much more difficult to make generic statements at a high level of aggregation and interventions will have a less predictable result.
Traffic models
Traffic policy is a good example to illustrate the distinction between a process and a complexity approach. Simulation using a digital twin in Chattanooga of the use of flexible lane assignment and traffic light phasing showed that congestion could be reduced by 30%. Had this experiment been carried out, the result would probably have been very different. Traffic experts note time and again that every newly opened road becomes full after a short time, while the traffic picture on other roads hardly changes. In econometrics this phenomenon is called induced demand. In a study of urban traffic patterns between 1983 and 2003, economists Gilles Duranton and Matthew Turner found that car use increases proportionally with the growth of road capacity. The cause only becomes visible to those who use a complexity approach: Every road user reacts differently to the opening or closing of a road. That reaction can be to move the ride to another time, to use a different road, to ride with someone else, to use public transport or to cancel the ride.
Carlos Gershenson, a Mexican computer specialist, has examined traffic behavior from a complexity approach and he concludes that self-regulation is the best way to tackle congestion and to maximize the capacity of roads. If the simulated traffic changes in Chattanooga had taken place in the real world, thousands of travelers would have changed their driving behavior in a short time. They had started trying out the smart highway, and due to induced demand, congestion there would increase to old levels in no time. Someone who wants to make the effect of traffic measures visible with a digital twin should feed it with results of research into the induced demand effect, instead of just manipulating historical traffic data.
The value of digital twins
Digital twins prove their worth when simulating physical systems, i.e. processes with a parametric progression. This concerns, for example, the operation of a machine, or in an urban context, the relationship between the amount of UV light, the temperature, the wind (speed) and the number of trees per unit area. In Singapore, for example, digital twins are being used to investigate how heat islands arise in the city and how their effect can be reduced. Schiphol Airporthas a digital twin that shows all moving parts at the airport, such as roller conveyors and stairs. This enables technicians to get to work immediately in the event of a malfunction. It is impossible to say in advance whether the costs of building such a model outweigh the benefits. Digital twins often develop from small to large, driven by proven needs.
Boston also developed a digital twin of part of the city in 2017, with technical support from Esri. A limited number of processes have been merged into a virtual 3D model. One is the shadowing caused by the height of buildings. One of the much-loved green spaces in the city is the Boston Common. For decades, it has been possible to limit the development of high-rise buildings along the edges of the park and thus to limit shade. Time and again, project developers came up with new proposals for high-rise buildings. With the digital twin, the effect of the shadowing of these buildings can be simulated in different weather conditions and in different seasons (see title image). The digital twin can be consulted online, so that everyone can view these and other effects of urban planning interventions at home.
Questions in advance
Three questions precede the construction of a digital twin. In the first place, what the user wants to achieve with it, then which processes will be involved and thirdly, which knowledge is available of these processes and their impact. Chris Andrews, an urban planner working on the ESRI ArcGIS platform, emphasizes the need to limit the number of elements in a digital twin and to pre-calculate the relationship between them: To help limit complexity, the number of systems modeled in a digital twin should likely be focused on the problems the twin will be used to solve.
Both the example of traffic forecasts in Chattanooga, the formation of heat islands in Singapore and the shadowing of the Boston Common show that raw data is insufficient to feed a digital twin. Instead, data are used that are the result of scientific research, after the researcher has decided whether a systems approach or a complexity approach is appropriate. In the words of Nigel Jacob, former Chief Technology Officer in Boston: For many years now, we’ve been talking about the need to become data-driven… But there’s a step beyond that. We need to make the transition to being science-driven in …… It’s not enough to be data mining to look for patterns. We need to understand root causes of issues and develop policies to address these issues.
Digital twins are valuable tools. But if they are fed with raw data, they provide at best insight into statistical connections and every scientist knows how dangerous it is to draw conclusions from that: Trash in, trash out.
Digitale sociale innovatie – also referred to as smart city 3.0 – is a modest counterweight to the growing dominance and yet lagging promises of ‘Big Tech’. It concerns “a type of social and collaborative innovation in which final users and communities collaborate through digital platforms to produce solutions for a wide range of social needs and at a scale that was unimaginable before the rise of Internet-enabled networking platforms.”
Digital innovation in Europe has been boosted by the EU project Growing a digital social Innovation ecosystem for Europa (2015 – 2020), in which De Waag Society in Amsterdam participated for the Netherlands. One of the achievements is a database of more than 3000 organizations and companies.
It is a pity that this database is no longer kept up to date after the project has expired and – as I have experienced – quickly loses its accuracy.
Many organizations and projects have interconnections, usually around a ‘hub’. In addition to the Waag Society, these are for Europe, Nesta, Fondazione Mondo Digitale and the Institute for Network Cultures. These four organizations are also advisors for new projects. Important websites are: digitalsocial.eu(no longer maintained) and the more business-oriented techforgood.
A diversity of perspectives
To get to know the field of digital innovation better, different angles can be used:
• Attention to a diversity of issues such as energy and climate, air and noise pollution, health care and welfare, economy and work, migration, political involvement, affordable housing, social cohesion, education and skills.
• The multitude of tools ranging from open hardware kits for measuring air pollution, devices for recycling plastic, 3D printers, open data, open hardware and open knowledge. Furthermore, social media, crowdsourcing, crowdfunding, big data, machine learning et cetera.
• The variety of project types: Web services, networks, hardware, research, consultancy, campaigns and events, courses and training, education, and research.
• The diverse nature of the organizations involved: NGOs, not-for-profit organizations, citizens’ initiatives, educational and research institutions, municipalities and increasingly social enterprises.
Below, these four perspectives are only discussed indirectly via the selected examples. The emphasis is on a fifth angle, namely the diversity of objectives of the organizations and projects involved. At the end of this article, I will consider how municipalities can stimulate digital social innovation. But I start with the question of what the organizations involved have in common.
A common denominator
A number of organizations drew up the Manifesto for Digital Social Innovation in 2017 and identified central values for digital social innovation: Openness and transparency, democracy and decentralization, experimentation and adoption, digital skills, multidisciplinary and sustainability. These give meaning to the three components of the concept of digital social technology:
Social issues.
The multitude of themes of projects in the field of digital social innovation has already been mentioned. Within all these themes, the perspective of social inequality, diversity, human dignity, and gender are playing an important role. In urban planning applications, this partly shifts the focus from the physical environment to the social environment: We’re pivoting from a focus on technology and IoT and data to a much more human-centered process, in the words of Emily Yates, smart cities director of Philadelphia.
Innovation
Ben Green writes in his book ‘The smart enough city’: One of the smart city’s greatest and most pernicious tricks is that it …. puts innovation on a pedestal by devaluing traditional practices as emblematic of the undesirable dumb city.(p. 142). In digital social, innovation rather refers to implement, experiment, improve and reassemble.
(Digital) technology
Technology is not a neutral toolbox that can be used or misused for all purposes. Again Ben Green: We must ask, what forms of technology are compatible with the kind of society we want to build (p. 99). Current technologies have been shaped by commercial or military objectives. Technologies that contribute to ‘the common good’ still need to be partly developed. Supporters of digital social innovation emphasize the importance of a robust European open, universal, distributed, privacy-aware and neutral peer-to-peer network as a platform for all forms of digital social innovation.
Objectives and focus
When it comes to the objective or focus, five types of projects can be distinguished: (1) New production techniques (2) participation (3) cooperation (4 raising awareness and (5) striving for open access.
1. New production techniques
A growing group of ‘makers’ is revolutionizing open design. 3D production tools CAD/CAM software is not expensive or available in fab labs and libraries. Waag Society in Amsterdam is one of the many institutions that host a fab lab. This is used, among other things, to develop several digital social innovations. One example was a $50 3D-printed prosthesis intended for use in developing countries.
2. Participation
Digital technology can allow citizens to participate in decision-making processes on a large scale. In Finland, citizens are allowed to submit proposals to parliament. Open Ministry supports citizens in making an admissible proposal and furthermore in obtaining the minimum required 50,000 votes. Open Ministry is now part of the European D-CENTproject a decentralized social networking platform that has developed tools for large-scale collaboration and decision making across Europe.
3. Collaboration
It is about enabling people to exchange skills, knowledge, food, clothing, housing, but also includes new forms of crowdfunding and financing based on reputation and trust. The sharing economy is becoming an important economic factor. Thousands of alternative payment methods are also in use worldwide. In East Africa, M-PESA (a mobile financial payment system) opens access to secure financial services for nine million people. Goteo is a social network for crowdfunding and collaborative collaboration that contribute to the common good.
4. Awareness
These are tools that seek to use information to change behavior and mobilize collective action. Tyze is a closed and online community for family, friends, neighbors, and care professionals to strengthen mutual involvement around a client and to make appointments, for example for a visit. Safecast is the name of a home-built Geiger counter with which a worldwide community performs radiation measurements and thus helps to increase awareness in radiation and (soon) the presence of particulate matter.
5. Open Access
The open access movement (including open content, standards, licenses, knowledge and digital rights) aims to empower citizens. The CityService Development Kit (CitySDK) is a system that collects open data from governments to make it available uniformly and in real time. CitySDK helps seven European cities to release their data and provides tools to develop digital services. It also helps cities to anticipate the ever-expanding technological possibilities, for example a map showing all 9,866,539 buildings in the Netherlands, shaded by year of construction. Github is a collaborative platform for millions of open software developers, helping to re-decentralize the way code is built, shared, and maintained.
Cities Support
Cities can support organizations pursuing digital social innovations in tackling problems in many ways.
Financing
Direct support through subsidies, buying shares, loans, social impact bonds, but also competitions and matching, whereby the municipality doubles the capital obtained by the organization, for example through crowdfunding. An example of a project financed by the municipality is Amsterdammers, maak je stad.
Cooperation
Involvement in a project, varying from joint responsibility and cost sharing, to material support by making available space and service s, such as in the case Maker Fairs or the Unusual Suspects Festival. Maker Fairs or the Unusual Suspects Festival. Municipalities can also set up and support a project together, such as Cities for Digital Rights. A good example is the hundreds of commons in Bologna, to which the municipality delegates part of its tasks.
Purchasing Policy
Digital social innovation projects have provided a very wide range of useful software in many areas, including improving communication with citizens and their involvement in policy. Consul was first used in Madrid but has made its way to 33 countries and more than 100 cities and businesses and is used by more than 90 million people. In many cases there is also local supply. An alternative is Citizenlab.
Infrastructure
Municipalities should seriously consider setting up or supporting a fab lab. Fab Foundation is helpful in this regard. Another example is the Things Network and the Smart citizen kit.. Both are open tools that enable citizens and entrepreneurs to build an IoT application at low cost. These facilities can also be used to measure noise nuisance, light pollution, or odors with citizens in a neighborhood, without having to install an expensive sensor network.
Skills Training
Municipalities can offer citizens and students targeted programs for training digital skills, or support organizations that can implement them, through a combination of physical and digital means. One of the options is the lie detector program, developed by a non-profit organization that teaches young children to recognize and resist manipulative information on (social) media.
Incubators and accelerators
We mainly find these types of organizations in the world of start-ups, some of which also have a social impact. Targeted guidance programs are also available for young DSI organizations. In the Netherlands this is the Waag Society in Amsterdam. A typical tech for good incubator in the UK is Bethnal Green Ventures. An organization that has also helped the Dutch company Fairphone to grow. In the Netherlands, various startup in residence programs also play a role in the development of DSI organisations.
Urban problems are always complicated, contradictory, and complex and rarely have simple solutions. Therefore, like all other projects, digital social projects need to be carefully embedded and their interfaces explored with the other aspects of policy.
This post is the third episode in the series Better cities: The contribution of digital technologies. It deals with the rise of the smart city movement, the different forms it has taken and what its future can be.
The term smart cities shows up in the last decade of the 20th century. Most definitions refer to the use of (digital) technology as a tool for empowering cities and citizens, and a key to fuel economic growth and to attract investments. Some observants will add as an instrument to generate large profits.
Barcelona, Ottawa, Brisbane, Amsterdam, Kyoto, and Bangalore belong to the forerunners of cities that flagged themselves as ‘smart’. In 2013 approximately 143 ‘self-appointed’ smart cities existed worldwide. To date, this number has exploded over more than 1000.
Five smart city tales
In their article Smart Cities as Company Story tellingOla Söderström et al. document how technology companies crafted the smart city as a fictional story that framed the problems of world cities in a way these companies can offer to solve. Over time, the story has multiplied, resulting in what I have called the Smart city tales, a series of narratives used by companies and city representatives. I will address with five dominant ones below: The connected city, the entrepreneurial city, the data-driven city, the digital services city and the consumers’ city.
The connected city
On November 4th 2011, the trademark smarter cities was officially registered as belonging to IBM. It marked a period in which the company became the leader of the smart city technology market. Other companies followed fast, attracted by an expected growth of this market by 20% per year from over $300bn in 2015 to over $750bn to date. In the IBM vision cities are systems of systems: Planning and management services, infrastructural services and human services, each to be differentiated further, to be oversighted and controlled from one cenral point, such as the iconic control center that IBM has build in Rio de Janeiro. All systems can be characterized by three ‘I’s, which are the hard core of any smart city: Being instrumented, interconnected and intelligent.
The corporate smart city
In many cities in the world, emerging and developing countries in the first place, administrators were dreaming about building smart towns from scratch. They envisioned being ‘connected’ as a major marketing tool for new business development.
Cisco and Gale, an international property development company, became the developers of New Songdo in South Korea. New Songdo was in the first place meant to become a giant business park and it is set out to enable a decent corporate lifestyle and business experience for people from abroad, offering houses full of technical gadgets, attractive parks, full-featured office space, outstanding connectivity and accessibility.
Quite some other countries took comparable initiatives in order to attract foreign capital and experts to boost economic growth. For example, India, that has planned to build 100 smart cities.
The data driven city
The third narrative is fueled by the collection and refined analyses of data that technology companies ‘tap’ for commercial reasons from citizens’ Internet and mobile phones communication. Google was the first to discover the unlimited opportunities of integrating its huge knowledge of consumer behavior with city data.
Sidewalk Labs – legally operating under the umbrella of Alphabet – responded to an open call for a proposal for redevelopment of Quayside, brownfield land around Toronto’s old port, and won the competition. Its plans were on par with contemporary urbanist thinking. However, that was not Sidewalk Labs’ first motive. Instead, its interest was ‘ubiquitous sensing’ of city life’, to expand Google’s already massive collection of personalized profiles with real-time geotagged knowledge of where people are, what they are whishing or doing in order to provide them with commercial information.
As could be expected, privacy issues dominated the discussion over the urbanist merits of the plan and most observers believe that therefore the company put the plug out of the project in May 2020. The official reason was investors’ restraint, due to Covid-19.
The consumers’ smart city
The fourth narrative is focusing on rise of urban tech targeted on consumers. Amazon, Uber and Airbnb are forerunners disrupting traditional sectors like retail, taxi and hotel business. They introduced a platform approach that decimated the middleclass in in the US. Others followed, such as bike- and scooter-sharing companies Bird and Lyme, co-working companies like We Work and meal delivery services like Delivero.
City tech embodies the influence of entrepreneurship backed by venture capitalists and at the same time the necessity for city governments to establish a democratic legitimized framework to manage these initiatives.
The smart services city
Thanks to numerous ‘apps’, cities started to offer a wealth of information and services to citizens concerning employment, housing, administration, mobility, health, security and utilities. These apps enable city administrators, transit authorities, utility services and many others to inform citizens better than before. With these apps, citizens also can raise questions or make a request to repair broken street furniture.
Some cities, for instance Barcelona and Madrid, started to use digital technologies to increase public engagement, or to give people a voice in decision making or budgeting.
All aforementioned narratives suggest a tight link between technology and the wellbeing of citizens, symbolizing a new kind of technology-led urban utopia. In essence, each narrative puts available technology in the center and looks for a good-looking rationale to put it into the market. Probably, the fifth one witnesses an upcoming change into a more human-centric direction.
An upcoming techlash or a second wave of smart cities
It is unmistakably that business leaders, having in mind a multi-billion smart city technologies market overstate the proven benefits of technology. Garbage containers with built-in sensors and adaptive street lighting are not that great after all, and the sensors appearing everywhere raise many questions. According to The Economist, it is not surprising that a techlash is underway. As I accentuated in last week’s post, politicians are becoming more critical regarding behemoths like Google, Amazon and Facebook, because of their treatment of sensitive data, their lack of transparency of algorithm-based decision making, their profits and tax evasion and the gig economy in general. Skepticism within the general public is increasing too.
Nevertheless, a second wave of smart cities is upcoming. The first wave lacked openess for the ethics of urban technology and the governance of urban development. The second wave excels in ethical considerations and intentions to preserve privacy. Intentions alone are insufficient, politics will also have to break the monopolies of Big Tech
Besides, in order to gain trust in the general public, city governors must discuss the city’s real challenges with residents, (knowledge) institutions, and other stakeholder before praising the role of technologies of all kind. Governance comes prior to technology. As Francesca Bria, former chief technology officer of Barcelona said: We are reversing the smart city paradigm.Instead of starting from technology and extracting all the data we can before thinking about how to use it, we started aligning the tech agenda with the agenda of the city.
Apart from Barcelona, this also happens in cities such as Amsterdam, Boston, Portland and the Polish city of Lublin. The question is no longer which problems technology is going to solve, but which exactly are these problems, who is trusted to define them, which are their causes, whose intersts are involved, who is most affected, and which ones must be solved most urgently. Only after answering these questions, the discussion can be extended to the contribution of (digital) technology. In a next contribution, I explore digital social innovation, as a contribution to a revised smart city concept.
This post is a brief summary of my article Humane by choice. Smart by default: 39 building blocks for cities in the future. Published in the Journal of the American Institution of Engineers and Technology, June 2020. You will fine a copy of this article below:
This post is about the omnipotence of Big Tech. So far, resistance mainly results in regulation of its effects. The core of the problem, the monopoly position of the technology giants, is only marginally touched. What is needed is a strict antitrust policy and a government that once again takes a leading role in setting the technology agenda.
I just started a new series on the site of Amsterdam Smart City. In more than 20 short articles I will deal with the contribution of digital technology to making cities better. Read the prologue here:
Science for Society 