In the age of digitalisation, data seems to be omnipresent and endless. Data has always existed and data analysis is not a new invention. Nevertheless, data is considered the ‘oil of the 21st century’. However, extracting value from data is far less easy than it seems. Data professionals have known this for a long time; the economy and our cities are just learning it.
At the same time, the term ‘smart city’ has been attracting a great deal of attention for several years now: data is available in cities and urban research on an unprecedented scale. This means that decision-making processes are changing enormously as a result of digitalisation. This makes the dialogue between urban planning and administration, data experts and, last but not least, civil society all the more important.
Smart City Charta
The Federal Institute for Research on Building, Urban Affairs and Spatial Development (BBSR) has been intensively involved in shaping this dialogue for several years. For example, the ‘Smart City Charter’ has emerged from an extensive Smart Cities dialogue platform. Since mid-2016, the participants in the dialogue platform have been discussing the opportunities and risks of digitalisation for cities and municipalities: Representatives of municipalities and municipal associations, federal ministries, ministries, academia and, last but not least, civil society.
‘With the Smart City Charta, the Smart Cities dialogue platform is calling for digitalisation not to simply happen, but to actively shape it in terms of sustainable and integrated urban development,’ writes the former head of the BBSR, Harald Hermann, in his foreword. ‘Two goals of the New Urban Agenda are particularly important to us: firstly, to create liveable cities for people and, secondly, to recognise and empower cities as development actors. After all, it's about how we want to live in the future and securing and strengthening the necessary ability to act and the creative power of local authorities,’ adds State Secretary Gunther Adler from the Federal Ministry for the Environment, Nature Conservation and Nuclear Safety (BMUB), which at the time was responsible for the BBSR. The Federal Ministry of the Interior, Building and Community (BMI), in turn, has just reissued the Smart City Charter.
But Smart City is not a ‘sure-fire success’. Big Data & Co. require education so that fears are not instrumentalised.
It is therefore all the more surprising that the charter - which has been discussed mainly in specialist circles for four years - was recently scandalised on the ‘Tichys Einblick’ blog as apparent news, with all statements being twisted into the opposite. In his article ‘Die Ersetzung der Demokratie durch ein Feedbacksystem: Der verwaltete Mensch’, non-fiction author and historian Klaus-Rüdiger Mai uses the Smart City Charter to fuel the fear of big data with relish.
Mai compares the charter with social dystopias such as George Orwell's novel 1984 and quotes selectively from the paper. The charter explicitly states:
Care must be taken to ensure that no new power structures are created that are beyond democratic control and pose a threat to the fundamental rights, security and privacy of every individual.
Mai indirectly admits that he has read this sentence by noting that the word ‘privacy’ only appears once in the document, namely in this very sentence. If you count the word ‘data protection’, which includes privacy, it is mentioned a total of 18 times in the document and is cited as a top priority or basic requirement for the smart city.
Even basic general knowledge about data and how it is used today can be found in his blog article with a magnifying glass. The possible applications of big data, which he denounces as ‘big brother methods’, involve recognising patterns within large amounts of data that can be used to calculate the probability of future developments. In this way, data can be used to predict and hopefully avoid weather, natural disasters, traffic jams, but also dangers at major events due to overloaded emergency exits or mass panic. Many people still remember the Love Parade, where it was obviously not possible to analyse such a mass gathering in advance and to calculate routes and dangers.
Perhaps it is simply the fear that demonstrations from circles critical of democracy, to which the author is obviously close, will not be allowed to take place due to a demonstrable threat to general health and safety. But this is not a problem caused by big data or the Smart City Charter.
The type of data utilisation of anonymous data and movement profiles described by Mai has been used thousands of times in practice for several decades. Of course, new technologies also harbour risks of undesirable developments. The BBSR publication therefore outlines worst-case scenarios for smart cities in an ‘impromptu scenario 2040’. Mr Mai draws on these scenarios in his fantasised dystopia and clearly does not realise that the strategy paper is precisely about avoiding the scenarios he describes. The way in which this is done without any knowledge of dates, people and their positions and without a basic understanding of data protection-compliant data use lacks any journalistic and scientific professionalism that one would expect from a PhD (see note at the end of the article).
However, this shows all the more how urgently persuasion is needed so that the Smart City Charter can be implemented. Above all, positive examples of implementation are needed. In order to succeed in creating new knowledge from data for the benefit of society, a distinction must be made between where digitalisation produces knowledge and where it merely produces data - and that more data does not necessarily mean more knowledge. Big data in itself is not yet a value.
New knowledge for the city
Nevertheless, big data is changing how we see the world, how cities will take care of their tasks in the future and how science will approach the pressing issues of urban development.
BBSR - STAT-UP
Data Science Case Studies | Gamification, Prognosemärkte, Wikis & Co: Neues Wissen für die Stadt? | STUDIO | STADT | REGION | TU München | Urban Progress
In the study ‘Gamification, prediction markets, wikis & co: new knowledge for the city?’, STAT-UP has therefore investigated the topic of ‘new knowledge’ for the city on behalf of the BBSR. Together with a large panel of experts from urban research, administrative practice, but also from the fields of data ethics and data protection, a series of possible examples of data applications for work in cities and municipalities are outlined and evaluated from different perspectives. The concept of ‘digital fairness’ plays a central role here.
Data literacy is required for such application examples to be implemented effectively.
Data literacy makes it possible to understand the value of data and the effort required to turn it into knowledge.
This effort is not always worthwhile. Sometimes legal hurdles prohibit the linking of sensitive data sources, sometimes the required financial, technical and human resources are beyond the realms of possibility, sometimes the data simply contains too little relevant information to adequately answer a question.
When is new data relevant and when can it be used?
Digitalisation is on the rise and new data providers are entering the playing field. This cannot be denied. However, it is important to consider what this means and how this data can be integrated as effectively as possible. Data-based decision-making ultimately leads to far-reaching changes. Power structures are often called into question and previous decision-making rules turn out to be myths. Those involved must therefore be convinced to share their data so that more value can be created for everyone.
Many people take a critical view of such new ideas because they are unsure about data security and data protection. Cities and local authorities need to clarify exactly which legal framework conditions they need to observe and what effort they need to make to ensure that these are complied with. Certain ideas are not compatible with the current legal situation in Germany because some data sources may not be linked with each other by law.
The issue of liability should not be neglected either: Liability cases can arise, for example, if incorrect decisions are made due to poor data quality or incorrect models. Who is liable in such cases?
This doesn't just play a role with self-driving cars if they don't process the environmental data correctly and are then involved in accidents. It is just as relevant in the case of incorrect forecasts in municipal planning.
Data and data analysis do not release anyone from responsibility for their decisions based on this data.
This is not the only reason why continuous training is required for those involved. And this raises further questions: What new requirements are emerging in terms of communication and cooperation between various municipal organisations and with non-administrative stakeholders, for example in the course of open governance efforts and comprehensive information portals? Is there perhaps even a need for reorganisation?
How can the various stakeholders learn from each other? How can administrative processes be adapted? And what effort does it take for project management, internal and external communication to ensure acceptance of the new data and the decisions made with its help - especially if the results of data-based decision-making contradict previous practice?
Können wir uns dann einfach auf die Algorithmen berufen?
Algorithms are today what chemical formulae, construction and production plans were in the 20th century. They determine how precisely value can be extracted from data in a specific application and are used in a wide variety of planning, control and decision-making processes:
Which traffic lights should switch to green and when, so that traffic in the city can flow as smoothly as possible? When citizens report road damage via a defect portal, which should be repaired as a high priority and which as a lower priority? When will more underground trains and security forces be deployed to optimise the flow of visitors to the Oktoberfest? How can the life cycles of neighbourhoods be mapped in planning so that supply and demand for public facilities are coordinated sustainably and dynamically?
The ‘New knowledge for the city’ project at a glance, image source: BBSR
Identifying such questions and answering them with the help of data requires not only competent employees, but also suitable organisational models.
Reliable traffic rules are also needed to turn data oil into mobility for all: It's about informational self-determination and digital credibility.
The digital transformation has a significant impact on civil society, especially when cities want to utilise new data sources. There are laws and rules for official data; not every organisation is happy about the statistical laws, but at least it is clear who has to provide which data. Ideally, it is even clear why we all need this data.
‘Digital credibility’ is therefore an essential prerequisite for cities and local authorities to be able to collect new data and make decisions based on it. Without credibility, there will be no willingness for digital interaction between civil society and official organisations. In other words, ‘trust is the beginning of everything’.
Just think of the outcry when the supermarket chain Target selected potentially pregnant customers in order to send them targeted adverts. Or a patent from Mastercard: ‘A system, method and computer-readable storage medium configured to analyse the physical size of payment beneficiaries based on payment transactions and to allow a transportation provider to consider the physical size of payment beneficiaries when assigning a seat.’ - In other words, height and weight are calculated from customers' purchases and passed on to an airline. The airline may then not allow overweight passengers to fly, or only at significantly higher prices. Imagine that for the Berlin underground - unthinkable!
‘Respect for informational self-determination‘ must be the underlying guiding principle: there is no general right of the state to citizens’ data.
Anyone who generates data should also have the right to view and use this data, as there is a right to ownership of one's own data.
Perhaps the public has a specific claim to specific individual data, just as the state has a certain claim to citizens' income in the form of taxes and fees. It is worth considering this idea further, especially if we view data as a valuable commodity.
Specifically, we could make the following five considerations, which are based on the seven theses on ‘digital fairness’ by theologian and business ethicist Ulrich Hemel, among others:
Firstly, there is the question of entitlement to and compensation for data. Which data can the public sector lay claim to for legitimate reasons and for which data must it provide a corresponding service in return? What can we learn from statistical laws, can new technologies perhaps even relieve the burden here because they simplify the provision of data? What positive effects result from participation because citizens experience that their data is important and leads to change?
Secondly, it is about the balance between transparency and discretion. Who is granted what insight into the data and, if applicable, at what price? How much effort does the public sector have to bear itself, how much do citizens have to pay, how do you deal with other stakeholder groups? Are there legitimate reasons to refuse access because the common good and the interests of the individual are in conflict? What positive effects arise because citizens feel better informed?
Thirdly, we should think about retention and expiry periods. How long can personal data be stored and can it be used in anonymised form afterwards? Conversely, how long must data be stored so that rights to information can be upheld and who bears the costs for this? What positive effects arise because authorities are better networked and more service is possible?
Fourthly, who is responsible for resolving conflicts? How can we safeguard the interests of citizens if there are no general rules yet? Do we need ombudspersons? How can we take into account the interests of those who, due to a lack of knowledge or resources, do not actively inform themselves or complain when their rights are violated? What positive effects arise because the public sector actively looks after the rights of citizens - unlike Google, Facebook & Co.
Fifthly and finally, what about resource conservation? On the one hand, resource conservation refers to the question of whether the digitalisation of processes per se leads to savings compared to previous analogue processes. On the other hand, resource conservation refers to the aspect of data minimisation. Should it generally be permissible to collect data, even if it is not needed in a specific application but can be used later, if resources (i.e. ultimately taxpayers' money) can be saved as a result?
New data: Yes, but not at any price.
The public sector - cities, municipalities, authorities - faces the same problem as the private sector. On the one hand, they have to bring together a variety of data sources in order to generate smart data from big data - in doing so, they have to master technical, data protection and licensing tasks, among other things.
On the other hand, there is the desire for better planning and control, more efficient implementation of administrative processes and perhaps even new data products that can be made available to other stakeholders.
One thing is clear: it is not enough to buy in data scientists and pack as much data as possible from as many new sources as possible into a cloud.
The biggest challenge is not a technical one. It is the challenge of persuading the many different stakeholders to share their data in order to create more value for everyone and to make this value visible.
‘This persuasion task is probably more difficult than any technological issues that might come up’, write Stephen Goldsmith and Susan Crawford in their highly readable book “The Responsive City”. We can only master the path to smart cities together by empowering as many people as possible to handle their own data with confidence. Euphoria is just as out of place as ideological scaremongering. Instead, we need education, transparency and the courage to create innovative structures and decision-making processes.
Remark
An earlier version of this article stated:
Mai compares the charter to social dystopias such as George Orwell's novel 1984 and directly attacks personalities such as SPD politician Svenja Schulze: ‘Comrade Schulze’ has presented ‘a strategy paper with the vision of abolishing democracy with the charter because democracy is to be replaced by a feedback system.’ The SPD politician has been Federal Minister at the BMUB since 18 March 2018.
However, at the time the charter was published in May 2017, she was still a state politician in North Rhine-Westphalia and therefore not responsible for the BBSR. The accusation that she did not collect the charter a year later after taking office also collapses because the BBSR was already subordinate to another ministry: the Federal Office for Building and Regional Planning, which is superior to the BBSR, moved from the Ministry of the Environment to the Ministry of the Interior (BMI) on 15 March 2018. The BMI, in turn, has just reissued the Smart City Charter - but Mr Mai links to the old version from 2017, which still names the BMUB as the publisher. To suspect Federal Minister Horst Seehofer of supporting ‘left-wing green’ ideologies would probably be too bold a thesis.
My article on the Smart City Charter in particular seems to have served Mr Mai as inspiration for crude interpretations and distorted quotes.
I drew Roland Tichy's attention to the factual misrepresentation by Mr Mai. As a result, the blog post was amended. In the end, it is encouraging to see that respectful communication can help to overcome even major differences.
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