DIGITAL DEMOCRACY How to make it work?

By Dirk Helbing (Draft Version 1)

Is democracy outdated, is it broken? Many people feel the current political system will not work much longer. Suddenly, we are faced with unsustainability, mass migration, terror, climate emergency, a financial system at the verge of collapse, and “Corona emergency”. Some have suggested it is time for a data-driven digital state, and China would lead the way. Eventually, however, people have realized that this might establish a global technological totalitarianism. They understand that a data-driven and AI-controlled society could easily end in a data dictatorship, where optimization will overrule more and more freedoms. So, how to prevent that the world would eventually be run like a digitally optimized “Animal Farm”? How to upgrade democracies with digital means? Here, I suggest to build participatory platforms that support collective intelligence, and to engage in open formats such as “City Olympics”. 

A digital “benevolent dictator”?

When the book “Limits to Growth” was published in the early 1970ies, the world started to worry about its future. In the 21st century, it was suggested that some of the planetary resources needed for survival would fall short, for example, oil or water. Moreover, all simulation scenarios indicated that the world would fail to get on a sustainable path, and the economy and world’s population would collapse. We would see sky-rocketing death rates as never before.

At this time, people started to change their behavior. They avoided plastic bags, had car-free Sundays, and established environmental movements. Politically, it should have been required that, whatever we do from now on, should reduce the overall consumption of resources every year. Then, however, industry demanded: “Put all the obstacles out of our way, and we will fix the problem.” Neoliberalism, globalism, and free trade were considered to be the solution.

Instead, however, all of this increased the global resource consumption further. The lack of sustainability of the industrialized word was exported to the entire world, and so the consumption of resources multiplied worldwide and even in industrialized states. The global competition of everyone against everyone had created a “race to the bottom”, a “tragedy of the commons”, and the outcome could be billions of early deaths.

So, what should we do? It appeared natural to measure the remaining resources in the world, where they were located, and who consumed them. It also seemed plausible to control this consumption. However, for this, it would be necessary to control individual behaviors. A considerable number of people found it justified to do this, because it was a matter of life and death. It seemed necessary to “save the planet”. Humans were seen as “enemies” of the environment that we needed to survive – an enemy of their own specimen, some people said. It appeared justified to control them.

So, mass surveillance made its way. The Big Data collected would then be fed into giant AI systems, which – some day in the future - would potentially be smarter than any human on this planet. Consequently, some argued, people would have to do what this superintelligence recommends or demands, as if it was a “digital God”.

Moreover, tools (such as Sentient World) were developed to simulate the entire world. In these simulations, everyone would be represented by a digital double. You may imagine it as a “black box” learning to behave like you. This is fed with a lot of surveillance data, which would, hence, allow to generate a “digital twin” behaving – more or less – like you...

The world simulator would simulate different scenarios. The best one for the planet would be implemented. For this, however, everyone would have to contribute to realization of the plan. Everyone would have to behave as suggested. We would be manipulated by personalized information (called “big nudging”, i.e. nudging based on Big Data – personal data gained through mass surveillance). If we would not follow the recommendations, i.e. “mess with the plan”, we would be punished by negative points in their citizen score (no matter whether this is a “credit score” as in China, a “customer lifetime value” as companies in the West use it, or some other “super-score” – a one-dimensional score created from a multitude of measurements). This score would determine our value for society, and it would determine our rights and opportunities.

According to its engineers, the superintelligent system would act like a “benevolent dictator”. Do you find this plausible so far? If yes, you are probably aligned with the way of thinking of many IT experts and decision makers back in 2015. Even though the above storyline sounds kind of plausible, I would like to ask you to spot the mistakes in it. Have you found some?

Here are a couple of them:

1. If you want to optimize the world, you would need to choose a goal function. Unfortunately, we don’t know, what is the right goal function for the world. There is not even a science I know of, which would tell us – on scientific grounds – what goal function to choose. Should it be profit (GDP per capita)? Should it be sustainability (if yes, how to define it)? Should it be life expectancy? Should it be happiness? Or what else should it be? 
2. In the past years, the economic players tried to maximize profit. This, however, has brought our planet to the brink of disaster – so much so that we are now talking about a “climate emergency”. Suppose we would now tell a superintelligent to maximize sustainability. Then, it could easily happen that the system would suggest to end the lives of many people – or if it was equipped with tools for this (as the Skynet system seems to be), then it might even put some people to death. 
3. I actually doubt that optimization is the right approach, even though “optimization” sounds like a good thing. The reason is as follows: In order to optimize, one needs a one-dimensional goal function, otherwise one cannot decide what solution is better and which one is worse. (Such decisions need “>” and “<” operations.) Hence, the complexity of the system to be optimized needs to be projected on one dimension. In many cases, this will lead to over-simplifications. In any case, once you have decided for the goal, you would push all other goals into the background, and after some time of neglecting these goals, say, 50 years later, one of them will have become an even bigger problem to solve. Therefore, in our society, we cannot afford to focus on one goal and push back all other goals, in contrast to what a company might do. For a society to thrive, one needs to pursue various goals at the same time, and find a suitable balance between these goals. That, however, requires pluralism and diversity, not global centralized optimization. We will discuss in the next chapter, how this may be done. 
4. Even if it was the right thing to maximize a particular goal function, one would need to rely on the outcome. However, algorithms (machine learning and others) do not always converge. They may imply biases and discrimination. They may also be sensitive to the data set, to the algorithm, or even the hardware used. In many cases, there will be classification errors and spurious correlations. So, Chris Anderson’s dream, according to which Big Data would just tell us what is true or false, and what had to be done, has NOT come true. Big Data has NOT made science obsolete. In the data deluge, where there is ever more “dark” data than ever before,[1] which one may never be able to analyze, science is needed to decide what data to look at and in what ways. Note that these problems do not go away with more data. 
5. When there is no solution for the world’s existential problems within the current system (which, therefore, cannot be found by optimization), creativity and innovation is the right approach. That is, we need to think out of the box in order to expand the solution space and find solutions outside the current system. Note, however, that innovation always challenges established ways of doing things – it challenges the system. It may not happen, if people are punished for deviations from the grand plan of a superintelligent system. Such a system may even stabilize a system of which we know that it is not going to work (at least not for everyone). Hence, controlling people and manipulating their behavior may create an even bigger problem. It can make disasters (due to lack of sustainability) inevitable, where there might otherwise be solutions. (Such solutions are not contained in the data of the past, on which the super-intelligent system runs.) 
6. Tragically, if we do not have one centralized system optimizing the world, but different companies trying to optimize it in parallel, with different goal functions, this is not making things better. The problem is that each optimization implies constraints – it reduces freedoms to reach the optimal solution. So, when many optimization processes are happening in parallel, a lot of freedoms will be gone. Your car insurance, your health insurance, your doctor, your dentist, your employer, your electricity provider, your sustainability guide… – all of them will have demands, and some of them will probably ask you for some contradictory actions. You will become “a slave of many masters”, so to say. Compared to this, it is easier to follow the demands of one master, as in the Chinese credit score system, but this is totalitarian in nature. It always claims to be right. It cannot be questioned (while in a system with competitive demands, one can say “but X demanded something else – please sort it out with X”).
   

Given the above problems, in the following I will demand systems that are based on empowerment and coordination rather than control and manipulation. I will propose approaches that promote mass innovation.

In the Corona crisis, the failure of the concept of superintelligence became obvious at least for experts. The Artificial Intelligence system was confronted with situations that were kind of new to it, and so it could not handle the problem and it was not of much help. In contrast, citizens managed to find ways through the crisis, based on solidarity and “collective intelligence”. It became clear that civil society was the force and resource that future societies would have to build on. But how?

The Concept of Digital Democracy

The question is, how can we upgrade democracy with digital means – in a way that is competitive with the Chinese system? Such an upgrade would have to be built on digitally unleashing creativity, on combinatorial innovation, and on better decision-making. The first and second might be promoted by participatory approaches, such as Open Innovation, as we will see, enabling people to do things by themselves that they could not do in the past. The second and third bring us to the subject of “collective intelligence”.

“Collective intelligence” is also often called “swarm intelligence”, which is an impressive phenomenon known from the animal world. Well-known examples are flocks of birds, fish swarms, bee hives or ant colonies. “The fable of the bees” published in 1714, suggests that the economy should work like a bee hive. Even though the queen bee does not give commands and even though the activities of the hive are self-organized in a distributed way, bees maintain a highly differentiated animal society, including different kinds of “jobs”. Ant colonies are impressive as well. Even though a single ant has a brain with 250.000 neurons only, the number of neurons in an ant colony could be as big as the number of neurons in a human brain. Nevertheless, ants run an entire society in a distributed way, again with several different kinds of “jobs”. Can we learn something from the way these social animals are organized?

When it comes to bees, it is known that they send out “scouts” to scan the surrounding for food sources. They fly into different directions, explore the environment, and return. Then, they communicate their findings by means of a “bee dance”. The average direction indicates the direction of the food source they found, and the excitedness of the dance indicates the amount of food. The bystanders will evaluate the dances of many bees and then decide for the food source to exploit. The “scouts” don’t have an interest to exaggerate, because the food returned will benefit the entire bee hive. If they would lie, it would harm the entire hive. Therefore, the bees have no incentives to trick their fellow bees. Most importantly, however, there are three stages of the process: 1. The “scouts” explore the food sources independently of each other. 2. Information is shared with others. 3. The information of several “scouts” is evaluated, compared and integrated. This is the basis of the collective decision taken by the swarm.

In a sense, one could say that democracies are built on the principle of “swarm intelligence” as well. Alternatively, one speaks of the “wisdom of crowds”. When one needs to solve a problem where nobody knows the exact answer, a collective of people may often outperform the judgment of experts. The “Netflix Challenge” is a famous example for this, but there are in fact many more examples. A study at the prestigious MIT (Massachussetts Institute of Technology) has clearly demonstrated the existence of social intelligence, if a group is diverse and communication is balanced. Publications on “collective intelligence” are abundant.

However, on a population level today’s democracies use the principle of “collective intelligence” only every few years (during elections), while we could benefit from it on an everyday basis. In parliament, the “collective intelligence” principle may be used on a more regular basis, but it is often overruled by coalition agreements and party discipline. In the end, all that remains is a “yes/no” decision in parliament, where the majority wins over the minority. In the worst case, this could end with a dictatorship of the majority over minorities, as it occurs in some populist systems. (By the way, if we had an AI system, which figures out our opinions based on mass surveillance and always does whatever the majority wants, we would end in a society of “digital populism”.) In such societies, minorities would be systematically marginalized, even though most functions of our society are based on minorities: intellectuals, inventors, entrepreneurs, politicians, judges, artists, etc. One can easily imagine that such a system might turn against the people on which societies depend.

A few months after we published our paper “Build Digital Democracy” in Nature, it was claimed that Brexit was the first major casualty of “digital democracy”. This is, of course, not true. That article was using the word “digital democracy” in a very different, misleading way. There, it meant something that some people call “Facebook democracy”. As many people realized after the Cambridge Analytical scandal, Facebook can be very manipulative. Algorithms determine which opinions will spread and which ideas will never get noticed. Some people would say, it is a propaganda and censorship tool, which is disguised as a platform for the “freedom of speech”. A similar thing might apply to other Social Media as well.

In recent years, many Social Media have been criticized for becoming platforms promoting flame wars and hate speech, misinformation and fake news. Hence, they are often presented as proofs for the “madness of crowds”. It is then typically concluded that one should not offer The People a stronger participation in political decision-making processes. However, this conclusion is short-sighted, as the Social Media of today are not designed to promote the “Wisdom of Crowds”. They are built on the principle of the “attention economy”. That is, those who get more attention will have more influence. No wonder discussions are getting ever more noisy, more fake, and more emotional. This is what maximizes attention. It is also no wonder that Social Media have become battlefields for our minds. Often enough, one gets the impression we are in the middle of an information warfare.

The “digital democracy” I have in mind is of a very different nature. It is not about one fraction of people winning over another fraction of people. It is about learning to combine the best ideas of many minds which each other. The goal is to find better solutions – solutions that work for many, solutions that empower us. But how to do this? This goes in several steps:

1. Information search and search for solutions.
2. Information exchange to give the “big picture”.
3. Integration of solution approaches
4. Voting.

Some people call this process “Massive Open Online Deliberation” (MOODs). Let me now explain the different steps in more detail.

First, it is important that various individuals will search for relevant information on a problem and for possible solution approaches. These are analogous to the “scouts” mentioned before. In this step, it is crucial that the scouts pursue diverse approaches. It is also important that these individuals will not be manipulated, because this could reduce the solution space explored, which might prevent finding the best possible solution. Consequently, during the first step, the information platforms used should not make any recommendations, and the scouts should not communicate with each other. Otherwise, the “wisdom of crowds” effect would be undermined.

Second, the information found needs to be shared with others. In this stage, it is not important to “win against others”. Rather, the purpose of this step is to add to a “bigger picture”. When a complex problem needs to be solved, it will require the combination of many different perspectives in order to get a more or less complete picture. The information collected in the first step should add to this “big picture”. Therefore, the information of the various contributing individuals does not need to be complete. It is important, however, that the partial views will complement each other.

In the second step, the various bits of information should be well structured and put into a logical order. What follows from what? Which argument is adding further details to a particular perspective, which argument establishes a new perspective? Such different perspectives could be due to different interest groups, but not necessarily so. (Just think of a beautiful cathedral, which cannot be captured by a single photograph, but only by a collection of photographs from different perspectives.)

In other words, the arguments should be mapped out on a virtual table. For this, one might use tools such as Argument Graph. In the end, everyone should be able see all relevant arguments in a well-structured way, such that different perspectives become visible.

In the third step, well-versed representatives of the different perspectives should be invited to a round table – either a virtual or real one. In this step, the goal again is not to win against the others. Rather, the representatives of the different perspectives would have the task to work out integrated solution approaches that take on board many perspectives. If the round table does not succeed with representatives of the different perspectives, it is worth trying to work with people who are to represent perspectives that are not their own. As a result of step three, one should have several integrated solutions that satisfy various perspectives. In many cases, of course, it will be difficult to find a solution that satisfies all the different perspectives.

Hence, in step four, a decision needs to be taken for one of the integrated solutions. This would happen by voting, where typically those people would be the voters, who are concerned by the solution (i.e. people with “skin in the game”).

However, rather than deciding by majority vote, one may consider to use different voting rules. Quadratic voting, for example, allows every voter to give a certain number of points to each solution, representing the pain the solution would produce to the respective voter. The solution with the smallest number of points would be chosen, corresponding to the “minimization of pain”. A similar procedure could be applied for the “maximization of gain”. It is clear that our society urgently needs to collect experiences with various voting rules in order to see which one works best in what kind of situation.

Note that, even in step four, the overall goal is not to “win against others”, but to find a solution that works for everyone, or at least for many. The more people benefit from a solution, the greater would be the chance that society benefits as well. Of course, it is unlikely that everyone can benefit from every decision taken, but it is expected that the resulting decisions would be better in the sense that more people would benefit than when majority voting is applied. It would, moreover, be desirable to ensure that it is not always the same group of people who benefit from the decisions made, but that benefits are distributed over different interest groups in a fair way.

All in all, the above four-step process is expected to deliver solutions that will benefit more people. When averaged over many decisions and fairness considerations are taken on board, it might be even reached that everyone benefits (some from one set of decisions, others from another set). Hence, the resulting system is expected to be superior to one that is based on classical majority decisions or dictatorial decisions.

Note that the above approach is kind of similar to the way the Swiss basic democracy works, which is geared towards consensual decision-making and is using rotation principles to ensure that everyone can raise their most important issues. Also, The People can interfere with the process at any time by means of referenda. Digital technology would now allow us to implement these democratic principles in a digital platform. Such a platform would realize “democracy by design”. It could increase the efficiency of democratic processes. However, it would also be possible to support this successful system to other countries – and to companies and institutions as well. Finally, it might be possible to scale up the system in order to solve some global problems as well. Hence, you can see that “digital democracy” is not primarily about electronic voting (which many people find very concerning, because it may create possibilities to manipulate democratic elections electronically). Digital democracy is, in fact, about unleashing “collective intelligence”.

Participatory Resilience

When the world is in trouble, what we would want to have is a “resilient system”. This means, whatever disaster, crisis, shock or surprise our system experiences, it will be able to flexibly adapt and recover, and in the best case even get to a better system performance afterwards (as the principle of “anti-fragility” suggests). In other words, we need special system designs and operations for such flexibility.

The good news is that we know some of the principles that can make systems more resilient. Among them are

1. redundancy,
2. decentralization and modular design,
3. local autonomy,
4. solidarity,
5. diversity and pluralism,
6. distributed control,
7. participatory approaches,
8. local digital assistance.

Redundancy ensures that, if one system element is broken, there is still a backup system that one can rely on.

A modular system design makes sure that, if one part of the system gets in trouble, other parts can be decoupled and saved, particularly if the modules can operate autonomously locally (for some time at least). Behind this concept is the idea of creating a firewall, which will be able to keep a problem from spreading, as it would happen in a densely connected system, known as “domino effect” or “cascading effect”. Note that autonomy, or sovereignty, as some people like to call it, typically also comes with sustainability. Interestingly, “autonomy” is also one of the most important factors that matter for the happiness of people. Another one is “having good relationships with others”. This means people like to show empathy, responsibility, and solidarity, particularly in situations when others need help.

Diversity makes sure that, if one mechanism or approach fails, there are still others, which may work under the adverse conditions faced.

Participatory approaches allow people to take action locally, while first aid units are still not there. After a natural disaster, it often takes 72 hours until public help is fully operational. However, most people die within 3 days after a disaster strikes, such that public help often comes late.

Digital assistance can keep up communication by creating an ad-hoc network and empower people to help themselves, coordinate, and support each other.

Interestingly, these resilience principles question the usefulness of centralized information and control systems to master future disasters, existential threats and crises. Centralized systems tend to roll out one solution (the “best” one) everywhere, which undermines diversity. They also violate the modular design principle. And they often fail, when help is needed most. For example, when disasters strike, the regular communication network and other critical infrastructures will often break down.

Given the recommended decentralization, cities (and the regions around them!) are suitable organizational units for a resilient world. In fact, if issues are regulated locally rather than globally, one will have more degrees of freedom to find a fitting solution. It is easy to imagine that it largely restricts our freedom of decision-making and our capacity to act, if people, who live hundreds or thousands of kilometers away, are trying to interfere with our decisions. Rather than focusing on regulation, which restricts possibilities, one should focus on responsible empowerment, i.e. empowerment that cares about the impact on others and on nature. So, how to do this? How can we activate the full potential of cities and the regions around them? “Good question, next question”, some would say…

Beyond Smart Cities[2]

How can we combine smart cities with collective intelligence? How can we empower cities and citizens? How can we turn cities and regions into innovation motors? How can cities help to make the world more sustainable and resilient? These are some of the questions discussed in the following.

The dream of building “good cities” is old1. Since the 20th century, there have been many attempts to create, develop or shape cities, sometimes even from scratch. Examples range from gigantic modernistic approaches known from Brasilia and Chandigarh, to more radical, but theoretical concepts aimed at changing society and engineering social order, such as Ecotopia or the Venus project. Recent developments are driven by the planetary trend towards urbanization, mass migration, and the need for sustainability. New visions of a global urban future were developed, such as “Sustainable”, “Eco”, or “Resilient” Cities, typically based on a top-down approach to the design of urban habitats.

Cities created from scratch heavily depend on massive private investments, for example, Songdo in South Korea or Lavasa in India. Despite ambitious goals and many technological innovations, their long-term success cannot be taken for granted, as they are often conceived by urban planners without the participation of people who later live in these cities. Such projects are typically implemented without much feedback from citizens. This makes it difficult to meet their needs. In fact, some of these cities have ended as “ghost cities”.

In the wake of the digital revolution, data-driven approaches promised to overcome these problems. “Smart cities”, “smart nations,” and even a “smarter planet” were proposed. Various big IT companies decided to invest huge amounts of money into platforms designed to run the “cities of the future”. Fueled by the upcoming Internet of Things, cities would be covered with plenty of sensors to automate them and thereby turn them into a technology-driven “paradise.” So far, however, these expectations have not been met.2 Why?

Geoffrey West points out that cities cannot be run like companies.3 A company is oriented at maximizing profit, i.e. a single quantity, while a city must balance a lot of different goals and interests. This tends to make companies efficient, but vulnerable to mistakes. Cities are often less efficient, but more resilient. Driven by diverse interests, cities naturally do not put all eggs in one basket. This is why cities typically live longer than businesses, kingdoms, empires, and nation states.4

Importantly, cities are not just giant supply chains. They are also not huge entertainment parks, in which citizens consume premanufactured experiences. Instead, they are places of experimentation, learning, social interaction, creativity, innovation, and participation. Cities are places, in which diverse talents and perspectives come together, and collective intelligence emerges. Quality of life results, when many kinds of people can pursue their interests and unfold their talents while these activities inspire and catalyse each other. In other words, cities partly self-organize, based on a co-evolutionary dynamics.5,6

While rapid urbanization comes with many problems, such as the overuse of resources, climate change and inequality,5 cities become ever more important, as they are motors of innovation.3,5 Presently, more than half of humanity lives in cities, and the urban population is expected to increase to 68% by 2050. To meet the social, economic, and ecological challenges, innovation must be further accelerated, as the UN Agenda 2030 Sustainable Development Goals stress.

Given the digital revolution and the sustainability challenges, we now have to re-invent the way cities and human settlements are built and operated, and how cities can contribute to the solutions of humanity’s present and future existential problems. In the past, we had primarily two ways of addressing such issues:

(1) nation-states (and their organization in the United Nations) and

(2) global corporations.

Both have not managed to deliver the necessary solutions on time, e.g. to problems such as climate change and lack of sustainability. Therefore, we propose a third way of addressing global problems: through networks of smarter cities, which enhance the

• classical, technology-driven smart city concept (smart cities 1.0)
• by collective intelligence (smart cities 2.0),
• by co-creation (smart cities 3.0), and
• by design for values (namely, constitutional and cultural ones) (smart cities 4.0).7

So, how to unleash the urban innovation engine to the benefit of citizens, societies, and the world?

City Olympics

“City Olympics” or “City Challenges” or “City Cups” could boost innovation on the level of cities and regions and across cities, involving all stakeholders. They would be national, international or even global competitions to find innovative solutions to important challenges. Competitive disciplines could, for example, be
 

• to reduce climate change,
• to increase energy efficiency,
• to reduce the consumption of resources,
• to improve sustainability,
• to enhance resilience,
• to promote fairness, solidarity and peace, and
• to develop organizational frameworks that empower cities and citizens to be innovative, take collective action, and make effective contributions to achieving local and global goals.

Increasing the role of cities and regions as drivers of innovation would allow innovative solutions and initiatives to be taken in a bottom-up way. All stakeholders and interested circles would be encouraged to contribute to City Challenges. Politicians would mobilize the society and call for everyone’s engagement. Scientists and engineers would invent new solutions. Of course, citizens would also be invited to participate, e.g. through Citizen Science. Media would continuously feature the various projects, the efforts, and progress made. Companies would try to sell better products and services, thereby promoting practical implementations.

Overall, this effort would create a positive, playful and forward-looking spirit and collective action, which could largely promote the transformation towards a sustainable digital society. In the short time available (remember that the UN wants to accomplish the sustainability goals by around 2030), the ecological transformation of our society can only succeed if the majority of our society is taken on board, and if everyone can participate and benefit.

The resulting solutions would be evaluated and “best of” lists created for the different disciplines of the City Challenge. Accordingly, prizes would be handed out to the winners. However, as the creation of these solutions would be publicly funded, they would be a public good, i.e. Open Source (for example, under a Creative Commons license). This will allow that any city can take and implement any of the solutions developed. In other words, any city can potentially benefit from all the innovations made by other cities. Moreover, big business, small and medium-size enterprises, spin-off companies, scientific institutions, NGOs, and citizen initiatives could take any of these solutions, combine them with each other and develop them further. This would create a lively, participatory information and innovation ecosystem, where everyone with good ideas and solutions can add something to a public city platform benefiting cities, citizens, and society.

We are actually not that far from such solutions. Berlin, for example, has recently organized a “Make City” festival. Suppose, such festivals would take place in many cities in a synchronized way, and that there would be more reporting and more participation. Further assume that the solutions would be evaluated and shared, and that there was an alternation of competitive and cooperative phases, as suggested above. Then, we could truly identify the best ideas in the world, and combine them with each other, thereby promoting the emergence of a global collective intelligence.

The proposed approach combines some of the greatest success principles we know of:

• competition (capitalism),
• collaboration (social systems),
• collective intelligence (democracies),
• experimentation and selection of superior solutions (evolution, meritocratic cultures), and
• intelligent design (using AI and other suitable methods).

The proposed approach also pushes for a new paradigm of globalisation, which one may call “glocalisation”. It would be based on

• thinking global,
• acting local (and diverse),
• experimentation,
• learning from each other, and
• helping each other.

The approach would be scalable. It would be more diverse and less vulnerable to disruptions than today’s attempted global governance approaches. It would, furthermore, promote innovation and collective intelligence, while being compatible with privacy, freedom, participation, democracy, and a high quality of life. If cities would open up and engage in co-creation and sharing, they would quickly become more innovative and efficient. This brings us to the next subject.

Open Everything, Making, and Citizen Science

In recent years, we have seen the spread of new ways of addressing problems – both local and global. We are seeing new solutions to problems that politics and capitalism could not fix. These solutions are often based on the engagement of citizens and on contributions by the civil society. Such contributions are various and often useful and effective, particularly in many locations, whose problems have not been noticed and addressed by business and politics, because they are too particular and too remote.

These new solutions have often been based on open approaches, ranging from Open Access over Open Data and Open Source to Open Innovation. Such approaches have been able to catalyze massive public engagement. Think of the thousands of hackathons in the past years. In the “We vs. Virus Hackathon”, for example, 40.000 people have been mobilized to work on solutions of all kinds. However, public institutions still need to learn, how to integrate the power of collective action into public policies.

This concerns crowd-sourced approaches of all kinds: crowd sourcing, crowd-based sensing, and crowd funding, for example. Citizen science has been another remarkable recent development, which has been able to address complex problems that machine learning could not tackle alone. In the meantime, citizen science and machine learning are combined, thereby nicely illustrating human-machine symbiosis and augmented intelligence.

Another pillar of this movement are Fablabs and Maker Spaces as well as Gov Labs (government labs). Fablabs and Maker Spaces provide technology and machines such as 3D printers, which allow ordinary citizens to generate their own tools and products. Such capacities can be extremely valuable during crises and disasters, particularly if they have autonomous energy supply (e.g. based on solar power). Fablabs can produce tools needed for survival, when supply chains are interrupted or if delivery would take too long. The United States was even so excited about the perspective that it wanted to become “A Nation of Makers”.

In a sense, City Olympics would build on all these exciting recent developments, and take them to the next level. Over a period of several months, such approaches would be used to craft innovative solutions that could benefit cities, regions, or even the entire world. I firmly believe the success principles of the information age will be co-* principles such as

• co-learning,
• co-creation,
• combinatorial innovation,
• co-ordination,
• co-operation,
• co-evolution, and
• collective intelligence.

This holds, in particular, as the use of digital goods and services is not as competitive and exclusive as it applies to most material resources. Sharing information can have a benefit for many, while a material good can typically be used only by one person at a time. Why don’t we use this particular benefit of the information age, when the existential pressure of unsustainable economies is so big that a lot of people are in a danger of dying early? For example, why don’t we have a public data set of the world’s resources and materials flows (i.e. logistics), such that everyone could make an effort to improve supply chains and promote a circular economy? We have access to all sorts of stock market data, but we don’t have access to the data needed to organize our survival. This appears pretty irresponsible to me!

Last but not least, I must stress that living in a thriving society, in an age of peace and prosperity, is not just about having access to material resources. There are also a lot of “immaterial things” that matter, for example, social capital such as trust, reputation, solidarity, etc. I would, therefore, like to promote the idea of creating a “Culturepedia” or, as some people would say, running a “cultural genome project”. The idea is as follows: Every culture is made up of all sorts of traditions and success principles, many of which have been invented to cope with particular problems. We should collect and document these specific practices and success principles, how they work, and what they are good for – namely, in a special Wikipedia.

By making these mechanisms explicit and by describing also the side effects and interaction effects (e.g. with solution approaches of other cultures), it would be possible to use them more consciously. Such a Culturepedia could certainly help us to solve current problems, by applying and combining the best solutions and success principles for the local setting at hand.

A Culturepedia would also enable us to build “social guides”, i.e. personal digital assistants that make other cultures better understandable and help us to deal with them (like a “cultural adapter”). Altogether, social and cultural diversity can be a great asset. A similar observation has been made for biological diversity, which we have learned to protect. So, why fight against other cultures? We should rather learn to make better use of the social and cultural diversity the world is offering us!

Open Source Urbanism

Cities are the places where the engagement of citizens can have the greatest impact. The most livable cities manage to create opportunities to unfold the talents of many different people and cultures and to catalyse fruitful interactions among them. Opportunities for participation and co-creation are key for success.

Alexandros Washburn8 said about the design process of New York City that he could not control anything, but influence everything; successful urban design requires the right combination of top-down and bottom-up involvement. It is therefore essential that urban development involves all stakeholders including citizens. Vauban, a quarter of the city of Freiburg, Germany, is a good example for this. The city council encouraged the citizens to actively participate in land-use planning and city budgeting.

Sustainability and new energy-saving technologies were a primary focus of the planning strategy. In two new districts (Rieselfeld and Vauban), self-built and community architecture was created, which led to urban environments conceived and designed by future inhabitants according to their own vision. Now, Freiburg counts as benchmark city. Its concepts of sustainable urban planning and community participation are widely used by other cities all over the world.

So far, most urban planning professionals do not pay much attention to a long-term involvement of citizens in urban development. With the ubiquity of information and communication technologies, our cities are getting smarter, but not automatically more inclusive, just, and democratic.

The application of open source principles to the co-creation of urban environments could overcome these problems by supporting active participation, technological pluralism and diversity. Thereby, it would also avoid technological lock-ins and dead-ends. The open source movement, which started with opening software (see the example of GitHub) now promotes the co-production of open content (Wikipedia, OpenStreetMap), open hardware (3D-printer RepRap), and even open architecture (WikiHouse). Open Source Urbanism would be the next logical step of this open source trend.

In 2011, Saskia Sassen wrote: “I see in Open Source a DNA that resonates strongly with how people make the city theirs or urbanize what might be an individual initiative. And yet, it stays so far away from the city. I think that it will require making. We need to push this urbanizing of technologies to strengthen horizontal practices and initiatives.”4

Yochai Benkler argues that open source projects indicate the beginning of a social, technological, organizational and economic transformation of the society towards a new mode of production.9 This new mode, called commons-based peer production, is a collective activity of volunteers, usually coordinated via the Internet, producing free-to-use knowledge. Open Source Urbanism, as a new way of urban development, would therefore build on concepts such as Open Innovation and Commons-Based Peer Production.

In fact, citizens are keen to be not just consumers, but co-producers of their urban habitats. Some of them already experiment with open-sourcing urban design by collecting, improving, and sharing their Do-It-Yourself design blueprints and manuals on the Internet. The maker movement as well promotes community-driven design, prototyping, and fabrication to solve local and global challenges by improving lives in local communities around the planet.

Such examples are presently still too dispersed, and, therefore, not yet able to shift cities effectively towards more inclusive urban development on a global scale. For this, one would need a socio-technical platform to consolidate and strengthen the nascent movement. Such a platform could promote the exchange of best practices and solutions to frequently occurring problems. The results would be a digital commons designed to satisfy the citizens’ needs10.

All in all, Open Source Urbanism could take our cities and societies to a new level. In particular, the approach could help to create better living conditions in developing countries, refugee camps, and regions suffering from war and disaster. It could, however, also help to improve the quality of living in local city quarters around the world.

References (to be complemented)

1. Sennett, R. Building and Dwelling: Ethics for the City. (Farrar, Straus and Giroux, 2018).

2. Hugel, S. & Hoare, T. Disrupting cities through technology, Wilton Park. (2016).

3. West, G. Scale: The Universal Laws of Growth, Innovation, Sustainability, and the Pace of Life in Organisms, Cities, Economies, and Companies. (Penguin, 2017).

4. Sassen, S. Open Source Urbanism. Domus (2011). Available at: http://www.domusweb.it/en/op-ed/2011/06/29/open-source-urbanism.html. (Accessed: 16th November 2016)

5. Bettencourt, L. M. A. & West, G. A unified theory of urban living. Nature 467, 912–913 (2010).

6. Batty, M. Cities and complexity: understanding cities with cellular automata, agent-based models, and fractals. (The MIT press, 2007).

7. Barber, B. R. If mayors ruled the world: Dysfunctional nations, rising cities. (Yale University Press, 2013).

8. Washburn, A. The nature of urban design: A New York perspective on resilience. (Island Press, 2013).

9. Benkler, Y. Freedom in the Commons: Towards a Political Economy of Information. Duke Law J. 52, 1245–1276 (2003).

10. Schrijver, L. in Handbook of Ethics, Values, and Technological Design: Sources, Theory, Values and Application Domains (eds. van den Hoven, J., Vermaas, P. E. & van de Poel, I.) 589–611 (Springer Netherlands, 2015). doi:10.1007/978-94-007-6970-0_22

[1] the data volume generated doubles in less than a year, i.e. in one year we are producing more data than in all the years before in human history

[2] This and the following sections contain materials from the joint manuscript “Open Source Urbanism: Beyond Smart Cities” that Sergei Zhilin and I have written some time ago, see https://futurict.blogspot.com/2018/11/open-source-urbanism-beyond-smart-cities.html