Tuesday, 20 May 2014


By Dirk Helbing (ETH Zurich)

Never before were politicians, business leaders, and scientists more urgently needed to master the challenges ahead of us. We are in the middle of a third industrial revolution. While we see the symptoms, such as the financial and economic crisis, cybercrime and cyberwar, we haven't understood the implications well. But at the end of this socio-economic transformation, we will live in a digital society. This comes with breath-taking opportunities and challenges, as they occur only every 100 years.

Big Data: a magic wand. But do we know how to use it?

Let me start with Big Data. When the social messaging portal WhatsApp with its 450 million users was recently sold, 19 billion dollars were made -- almost half a billion dollars per staff member. Big Data is fundamentally changing our world. It is becoming the new oil of the 21st century, and we need to learn how to drill and refine it, i.e. how to produce data and turn them into information, knowledge and wisdom.

The potential of Big Data spans across all areas of society. It reaches from natural language processing over financial asset management, to smartly managing our cities and better balancing energy consumption and production, thereby saving energy. It allows for better protection of our environment, risk detection and reduction, and the discovery of opportunities, which would otherwise be missed. It will be possible to tailor medicine to patients, thereby increasing drug effectiveness while reducing side effects. Preventing diseases may become even more important than curing them. 

Big Data applications are now spreading like wildfire. They enable personalized offers, services and products. Big Data open up entirely new possibilities for process optimization and allow one to identify unexpected interdependencies. They also imply great potentials of evidence-based decision-making, but science will be crucial to ensure transparency, quality, and trust. Science will also be important to drive ethical ICT innovations and to avoid the pitfalls of Big Data applications. Therefore, science must become a fifth pillar of democracies, besides legislation, executive, jurisdiction, and the public media.

What's the next big thing after Big Data?

But we need to think a step ahead and realize that we are just at the beginning of a transformation process, which is about to change human history. The invention of the steam engine turned agricultural society ("economy 1.0") into industrial society ("economy 2.0"), and wide-spread education turned it into service society ("economy 3.0"). Now, the invention of computers, the Internet, the World Wide Web, and Social Media are transforming service societies into digital societies ("economy 4.0").

With computers reaching the level of human brainpower in about 10 years, with intelligent service robots, and the Big Data tsunami, 50 percent of jobs in the industrial and service sectors will probably be lost within the next 20 years. And most of our current ways of doing things will fundamentally change: the way we educate (MOOCS – Massively Open On-line Courses and personalized education), the way we do research (Big Data analytics), the way we move (self-driving Google cars) or transport goods (drones), the way we go shopping (take Amazon and eBay), the way we produce (3D printers), but also our health system (personalized medicine), and most likely politics (participation of citizens) and the entire economy as well (with the makers community, the emerging sharing economy, and prosumers, i.e. co-producing consumers). Financial business, which used to be the domain of banks, is increasingly replaced by algorithmic trading, Paypal, Bitcoin, and Google Wallet, etc. Moreover, the biggest share of the insurance business is now in financial products such as credit default swaps. Even wars may increasingly change from conventional wars to cyberwars.

Thus, how will the digital revolution transform our societies?

First of all, the transition will be challenging. Today's world is struggling with financial instabilities, and in many areas of the world, we are faced with social and political unrest -- sometimes framed as "Twitter revolutions". Thus, how can we handle this? Do we need more state power, based on armed police and mass surveillance? Could a giant supercomputer (or network or cloud of supercomputers), fueled with massive amounts of data about human activities and almost everything, simulate our globe? Could a supercomputing infrastructure like this optimize and plan our world? Could it avoid the traps of particular interests, irrationality, and emotional decision-making? Could it find ways to overcome coordination and market failures, breakdowns of cooperation, and conflict? Could it take better decisions than we could do? And should it determine our actions through personalized recommendations and selective information that smartphones or other gadgets deliver to us?

To some or even many of us, this seems plausible, but this concept, known as "benevolent dictator" or "big government" cannot work. While the processing power doubles every 1.8 years, the amount of data doubles only every 1.2 years. Unfortunately, the complexity of networked systems is growing even faster (see figure above). In other words, attempts to optimize systems in a top-down way will be less and less effective – and cannot be done in real time. Paradoxically, as economic diversification and cultural evolution progress, a big government approach would increasingly fail to lead to good decisions. However, neither is simplifying our world by homogenization and standardization a solution – since it reduces innovation, societal resilience, and the happiness of people in general. Today, everyone already complains about over-regulation, and we can no longer pay for the expensive institutions needed for it. Most industrialized countries have reached historical heights in public debt levels in the order of 100 to 200 percent of their annual productivity. Nobody knows how we should ever be able to pay for this – and for even more regulation.

But what alternatives do we have?

The logical answer is: distributed (self-)control, i.e. bottom-up self-regulation, as envisioned by Adam Smith's paradigm of the invisible hand. While this vision was often not working well in the past due to coordination and market failures, cybernetics (i.e. control theory) and complexity theory tell us that it is actually feasible to create resilient social and economic order by means of self-organization, self-regulation, and self-governance. The work of Nobel prize winner Elinor Ostrom and others has demonstrated this. By "guided self-organization" we can let things happen in a way that produces desirable outcomes in a flexible and efficient way. One should imagine this embedded in the framework of today's institutions and stakeholders which, however, will learn to interfere in minimally invasive ways.

How will such self-regulation work?

In a rapidly changing world, which is hard to predict and plan, we must create feedback loops that enable systems to flexibly adapt in real time to local conditions and needs. Now, 300 years after Adam Smith's historical vision, we can make it happen, fueled by real-time data. For example, my research team has invented self-regulating traffic lights, which are driven by the traffic flows and can outperform the classical top-down control by a conventional traffic center. Can we transfer and extend this principle to socio-economic systems? Indeed, we are now developing mechanisms to overcome coordination and cooperation failures, conflicts, and other age-old problems. This can be done with suitably designed social media and sensor networks for real-time measurements, which will eventually weave a Planetary Nervous System. Hence, we can finally realize the dream of self-regulating systems, and there is now a quickly increasing number of examples for them: Bitcoin, peer to peer lending, Google's self-driving car, Uber's limousine service, collaborative robot swarms, and social communities on the Web.

A new kind of economy is born

A largely self-regulating society isn't utopia. In fact, a new kind of economy is already on its way. Social media are networking people and, thereby, enable "collective intelligence." This paradigm is superior to the self-regarding optimization by the "homo economicus", the egoistic decision-maker assumed in mainstream economics ("economics 1.0"). While the bottom-up self-organization of the "homo economicus" can outperform top-down decision making in complex environments, highly competitive conditions can lead to coordination failures and poor outcomes (for example, "tragedies of the commons" such as environmental degradation). It has been theoretically and empirically shown, however, that a considerable fraction of people has other-regarding preferences -- I will call this type "homo socialis." To understand the decisions of this type, a new economic thinking ("economics 2.0") is needed compared to the purely selfish "homo economicus," which is the basis of the current mainstream economics (economics 1.0). Considering the impact of the own decisions on others enables self-regulation, which can overcome the above mentioned coordination failures and "tragedies of the commons." Interestingly, suitable institutions such as certain social media -- combined with suitable reputation systems -- can promote other-regarding decision-making. The quick spreading of social media and reputation systems, in fact, indicates the emergence of a superior organizational principle, which creates collective intelligence by harvesting the value of diversity. Properly designed social media allow diverse knowledge and skills to come together, thereby unleashing creativity, social capital and productive value.

Hence, in accordance with the paradigm of distributed control and self-regulation, a participatory market society is on the rise. While the 20th century was an era of democratization of consumption, the 21st century can become an era of democratization of production. Next to today’s companies, we see the emergence of an innovation ecosystem characterized by flexible, participatory forms of production, which I term "projects". Here, creative minds come together to realize joint project ideas. After completing a project, everyone looks for another one, and so on. Social media platforms such as Amazon Mechanical Turk make it possible to bring ideas and skilled workers together. As a consequence, this leads to a more direct participation of people in production processes ("prosumers"). Over time, there will be a much greater diversity of products, tailored to individual needs. Thus, while computers will increasingly replace our current types of routine and executive work, we will have an opportunity to replace these jobs by more creative activities. Production by large corporations will then be complemented by an innovation ecosystem made up of millions of projects. The huge range of smartphone apps that low-cost downloads from App stores have enabled, gives just a first idea of ​​the unlimited possibilities for new projects. Open access data and the Web2.0, Web3.0, etc. will further accelerate this development.

The new algebra of prosperity and leadership

The 21st century will be governed by fundamentally different principles than the 20th century, and that's why we need to change our way of thinking about the world. To understand this, it is important to recognize the following facts and trends: information is ubiquitous and everywhere instantly available, such that borders dissolve. The "second machine age" comes with extreme speed. Most of our knowledge is outdated, and we can't learn quickly enough to fully understand the changing world without the help of smart devices such as "social information technologies." Many systems become more variable, less predictable, and less controllable. Their increased connectivity implies a higher complexity. The increase in data volumes means we are overloaded by data that ultimately needs to be converted into information and then into actionable knowledge. Furthermore, the more data we produce, the less likely can we keep secrets and the cheaper will data become. This means that we will make less profits on data, but more on algorithms that turn data sets into useful information and knowledge. In such a world, ideas will become more powerful, and ethics more important. Digitally literate people will be better informed than experts used to be, therefore, classical hierarchies will dissolve. Moreover, data can be replicated as often as we like. It's a virtually unlimited resource, which may help to overcome conflicts that scarce resources used to imply. However, services and products will be more individualized, personalized, and user-centric. Finally, what used to be science fiction may become reality. The countries first recognizing these new principles and turning them into their advantage will be leading. Those failing to adapt to these trends in a timely manner will be in trouble. We may just have 20 years for this -- a very short time considering that planning and building a road often takes 30 years or more.

What does it take to master our future?

So far, no country in the world seems to be well prepared for the digital era. Therefore, we urgently need an Apollo-like program, and the equivalent of a Space Agency for ICT: an Innovation Alliance with the mission to develop the institutions and information infrastructures for the emerging digital society. This is crucial to master the challenges of the 21st century in a smart way and to unleash the full potential of information for our society. For illustration, it is helpful to recall the factors that enabled the success of the automobile age: the invention of cars and of systems of mass production; the construction of public roads, gas stations, and parking lots; the creation of driving schools and driver licenses; and last but not least, the establishment of traffic rules, traffic signs, speed controls, and traffic police. All of this required many billions each year. We invest a lot into the agricultural sector, the industrial sector, and also the service sector. But are we investing enough into the emerging digital sector?

What are the technological infrastructures and the legal, economic and societal institutions needed to make the digital age a big success? This question would set the agenda of the Innovation Alliance. A partial answer is already clear: we need trustworthy, transparent, open, and participatory ICT systems, which are compatible with our values. For example, it would make sense to establish the emergent "Internet of Things" as a Citizen Web. This would enable self-regulating systems through real-time measurements of the state of the world, which would be possible with a public information platform called the "Planetary Nervous System". It would also facilitate a real-time measurement and search engine: an open and participatory "Google 2.0."

To protect privacy, all data collected about individuals should be stored in a Personal Data Purse and, given informed consent, processed in a decentralized way by third-party Trustable Information Brokers, allowing everyone to control the use of their sensitive data. A Micro-Payment System would allow data providers, intellectual property right holders, and innovators to get rewards for their services. It would also encourage the exploration of new and timely intellectual property right paradigms ("Innovation Accelerator"). A pluralistic, User-centric Reputation System would promote responsible behavior in the virtual (and real) world. It would even enable the establishment of a new value exchange system called "Qualified Money," which would overcome weaknesses of the current financial system by providing additional adaptability.

A Global Participatory Platform would empower everyone to contribute data, computer algorithms and related ratings, and to benefit from the contributions of others (either free of charge or for a fee). It would also enable the generation of Social Capital such as trust and cooperativeness, using next-generation User-controlled Social Media. A Job and Project Platform would support crowdsourcing, collaboration, and socio-economic co-creation. Altogether, this would build a quickly growing Information and Innovation Ecosystem, unleashing the potential of data for everyone: business, politics, science, and citizens alike.

We could also create a Digital Mirror World to explore the likely risks and opportunities of prospective decisions. Finally, Interactive Virtual Worlds would realize the full creative potential within different socio-economic settings and intellectual property right approaches. Social Information Technologies would help us to cope with the diversity resulting from this and to benefit from it. Digital literacy and good education will be more important than ever. But with the emerging "Internet of Things" and participatory information platforms, we can unleash the power of information and turn the digital society into an opportunity for everyone. It just takes our will to establish the institutions required to make the digital age a great success.

Are we ready for this?

Monday, 28 April 2014


by Dirk Helbing (ETH Zurich)

Like many of us, I have been raised in a period of cold war. Military threats were serious and real, but the third world war did not happen – so far. This is generally considered to be a success of the “balance of threat” (or “balance of terror”): if one side were to attack the other, there would still be time to launch enough intercontinental nuclear warheads to eradicate the attacker. With no side crazy enough to risk eliminating itself, nobody would start such a war. 

However, what if this calculus is fundamentally flawed? There were at least three instances within a 60 year period, where the world came dauntingly close to a third world war. The Cuban missile crisis is just the most well-known, but there were others that most of us did not hear about (see http://en.wikipedia.org/wiki/World_War_III). Perhaps, we survived the strategy of nuclear deterrence just by chance?

The worrisome misconception is that only shifts in relative power can destabilize a “balance of threat”. This falsely assumes that balanced situations, called equilibria, are inherently stable, which is actually often not the case. For illustration, consider the simple experiment of a circular vehicle flow (see http://www.youtube.com/watch?v=Suugn-p5C1M): although it is apparently not difficult to drive a car at constant speed together with other cars, the equilibrium traffic flow will break down sooner or later. If only the density on the traffic circle is higher than a certain value, a so-called "phantom traffic jam" will form without any particular reason – no accident, no obstacles, nothing. The lesson here is that dynamical systems can easily get out of control even if everyone has good information, the latest technology and best intentions.

What if this is similarly true for the balance of threat? What if this equilibrium is unstable? Then, it could suddenly and unexpectedly break down. I would content that, in fact, a global-scale war may start for two fundamentally different reasons. Consider, as a simple analogue from physics, a metal plate that is pushed from two opposite sides. In the first situation, if either of the two sides holding the plate becomes stronger than the other, the metal plate will move. Hence, the spheres of influence will shift. The second possibility is that both sides are pushing equally strong, but they are pushing so much that the metal plate suddenly bends and eventually breaks.

The current news on the Ukrainian crisis do not make me confident that we are faced with a stable equilibrium. We rather see the metal plate aching.

A push from one side triggers a counter-push from the other side. One sanction is answered by something else and vice versa. In this escalating chain of events, everyone is pushing harder and harder without any chance for either side to gain the upper hand. In the end, the metal plate may bend or break. In practical terms, the nerves of a political leader or army general, for example, may not be infinitely strong. Furthermore, not all events are under their control. Thus, under enormous pressure, things might keep escalating and suddenly get out of control, even if nobody wants this to happen, if everyone just wants to save face. And this is still the most optimistic scenario, one in which all actors act rationally, for which there is no guarantee.

In recent years, evidence has accumulated that, in human history, many wars happened due to either of the instabilities discussed above. Recent books about World War I have revealed that it resulted from an eventual loss of control, which was the outcome of a long chain of events – a domino effect that probably resulted from the second kind of instability. Let us not make the same mistake again[1] (see Information Box below). Conflict in the Middle East has lasted for many decades, and it taught us one thing: Winning every battle does not necessarily win a war. Similar lessons had to be learned from the wars in Afghanistan and Iraq. My question is, when do we finally start to change our thinking?

While sanctioning may create social order in some cases, it may cause instability and escalation in others. Punishing someone is only successful, if the punished accepts the punishment, which often requires one to share the same values and culture. If the punished doesn't accept the punishment and is strong enough, he will strike back. Hence, a cycle of escalation will ensue, where each side further drives the escalation while feeling to be right. In such a situation deterrence is clearly not an effective solution. In the Ukrainian crisis, we have seen that sanctions did not have the desired effect, and there is actually no reason to believe that ever more sanctions would. In the case of Iran, for example, sanctions took years to show a substantial effect. In fact, trying to weaken a strong adversary may not be wise at all. It may even lead to desperate efforts to overcome a threatening situation, and this by itself may quickly lead to further escalation and, possibly, to war. 

Therefore, in a situation where we are faced with a potentially unstable “balance of threat”, we would be well advised to consider other strategies. It is not worth risking a World War III just for the sake of maintaining a “balance of threat”. Given the finite probability that such a balance may become unstable, we must find ways for both opponents to get out of the current situation without losing face. In this context, it is good to remember that there are always bigger challenges than what any side can solve by itself. A jointly faced threat, for example, might unify opponents and justify for both sides to put their weapons down. It really does not matter whether this threat is called “global warming”, “global pandemics”, “global economic crisis”, “global energy crisis,” or "global war" – we are faced with enough such challenges, which can only be successfully addressed by a united global effort.

If we need a war, than we need a war on wars. It might be true that, in history, war accelerated cultural exchange and progress, but we must recognize that cultural diversity was always the true driver of innovation and cultural evolution, not war. In times of a multi-polar world with global conflicts, cyberthreats and nuclear weapon arsenals on the one hand, but global exchange of people, goods and ideas on the other hand, it is dangerous to consider war to be the mother of civilization – it could rather be the end of it.

In the past decades, we have made much progress in developing collaborative structures that allow for diversity. Falling back to a thinking that stresses a “balance of threat” rather than constructive, cooperative interactions is a very dangerous step in the wrong direction. In fact, creating a new security architecture to master (global) diversity without deadly conflict is a worthwhile challenge for us all.

INFORMATION BOX: War as a result of systemic instability

We must realize that many large-scale conflicts, revolutions, and wars must be interpreted as result of systemic instabilities. Interpreting them as deeds of historical figures personalizes these phenomena in a way that distracts from their true, systemic nature. It is important to recognize that complex systems such as our society or economy usually resist attempts to change them, namely when they are close to a stable equilibrium. This is also known as Goodhart's law, principle of Le Chatelier, or the "illusion of control." Individual factors and randomness can have a large impact on the path taken by the system only, when a complex system is driven to a tipping point. In other words, instability is a precondition for individuals to have a historical impact. For example, World War II was preceded by a financial crisis and recession, which had destabilized the economic, social, and political system. This eventually made it possible that an individual could become influential enough to drive the world to the edge.

Unfortunately, civilization is vulnerable, and large-scale wars may happen again. A typical evolutionary path towards war looks as follows: The resource situation deteriorates (e.g. because of a serious economic crisis). The fierce competition for insufficient resources lets violence, crime, and corruption rise, while solidarity and tolerance go down, so that society is fragmented into groups. This causes further dissatisfaction and social turmoil. People get frustrated about the system, calling for leadership and order. Political extremism emerges, scapegoats are searched, and minorities are suppressed. Socio-diversity gets lost, and the well-balanced social ecosystem collapses, such that the resource situation (the apparent "carrying capacity") deteriorates further. This destabilizes the situation further, such that an external enemy is needed for a stabilization of the country. As a consequence, nationalism rises, and war may seem to be the only 'solution'.

[1] At least since 2010, I am worried that the final outcome of the global financial and economic crisis might be political instabilities, the rise of nationalism, and war. Let us stop this domino effect before it is too late.

Tuesday, 11 March 2014


by Dirk Helbing
Our society is fundamentally changing. These days, almost nothing works without a computer chip. Processing power doubles every 18 months and will exceed the capabilities of human brains in about ten years from now. Some time ago, IBM's Big Blue computer already beat the best chess player. Meanwhile, computers perform about 70 percent of all financial transactions, and IBM's Watson advises customers better than human telephone hotlines. Will computers and robots soon replace skilled labour? In many European countries, unemployment is reaching historical heights. The forthcoming economic and social impact of future information and communication technologies (ICT) will be huge - probably more significant than that caused by the steam engine, or by nano- or biotechnology.

The storage capacity for data is growing even faster than computational capacity. Within just a year we will soon generate more data than in the entire history of humankind. The "Internet of Things" will network trillions of sensors. Unimaginable amounts of data will be collected. Big Data is already being praised as the “oil of the 21st century”. What opportunities and risks does this create for our society, economy, and environment?

From "homo economicus" to "homo socialis", the networked decision-maker

Let's start by analysing the situation today. Probably, the most widespread economic paradigm is that of "homo economicus", who merely tries to maximize personal benefits. It is often believed that such behaviour balances and coordinates the interests of individuals, as if controlled by an "invisible hand" and automatically maximizes social welfare.

If one believes in this neoclassical credo, then, economic problems arise mainly from the fact that there are too many regulations, or that some people do not adhere to the principle of self-regarding optimization. But why are there so many regulations, and why do many people have fairness preferences?
It was long believed that the merciless forces of evolution and natural selection could not have created man other than as a selfish being. However, recent scientific insights teach us something else. It has been demonstrated that the very same evolutionary forces that create "homo economicus" may also produce a different kind of people under very realistic circumstances: "homo socialis". "Homo socialis" tries to reach favourable outcomes as well, but considers the impact on others when taking decisions. As a consequence, "homo socialis" does not decide in an independent, but rather in an interdependent, "networked" fashion. This has surprising consequences: while "homo economicus" often runs into "tragedies of the commons", for example, the exploitation and pollution of the environment, overfishing and/or global warming, "homo socialis" can overcome such problems and reach a higher success by conditional cooperativeness. 

Reputation systems to master social dilemmas 

The above tragedies of the commons result from social dilemmas. These are situations, in which it would be good for everyone, if everybody behaved cooperatively, but where there is also a temptation to take advantage of the cooperativeness of others. Under such conditions, cooperation is likely to erode. To avoid this, it is common to establish regulations and enforce compliance with them by means of monitoring and punishment strategies. However, over time, the costs of such strategies have created enormous public debts, and in some cases de facto state bankruptcy.

But there are also alternatives. The root problem is that we have created an institutional framework for "homo economicus", for which cooperation in social dilemma situations cannot thrive. But it would also be possible to create institutions for "homo socialis"; i.e. institutions which provide a suitable framework to support self-regulation. With such institutions for "homo socialis", the principle of Adam Smith's "invisible hand", i.e. the favourable self-organization of a complex (market) system to the benefit of everyone would work much better than with institutions for "homo economicus".

The difference between “homo economicus” and “homo socialis” is that the latter takes into account the interests of others when making decisions, which implies interdependent decisions or “networked minds.” The different nature of “homo socialis” leads to a complex dynamics and another macroscopic outcome than expected for “homo economicus.” In the case of public goods problems, for example, interactions of agents with strictly self-regarding preferences will lead to “tragedies of the commons,” while the self-regulation of “homo socialis” can overcome this undesirable state and foster cooperation, leading to higher individual and social benefits. Due to the different system dynamics and different systemic outcomes, both types of agents cannot be described by the same body of theory. They require separate sets of literature and different institutions. 
 How to envisage a self-regulating market system? The transfer of the principle of Swiss-style bottom-up democracy to the business world would probably be a good way to imagine this. 

What would be suitable institutions for "homo socialis"? It is known that social dilemmas can be overcome by various social mechanisms, such as genetic favouritism, direct reciprocity ("you help me, I help you"), or punishment of uncooperative behaviour. Genetic favouritism tends to create ethnic conflicts between tribes, while direct reciprocity may promote corruption. The punishment of non-cooperative behaviour corresponds to our current approach, but this seems to have reached the limits of feasibility and affordability. Note, however, that there is a further approach, which transfers the success principle of social communities to the context of the "global village", namely reputation.

"Prosumers" and "qualified money"

Reputation systems in the internet spread very quickly. Nowadays, customers evaluate products and sellers, news, comments, politicians, institutions and companies. Reputation creates the opportunity to sell good quality for a higher price. Scientific studies of eBay and other electronic platforms show that customers prefer sellers who have good reputations, and that these sellers can charge more. When quality competition complements price competition, this can also create incentives to improve social and environmental production conditions, i.e. sustainability. Based on reputation principles, it would even be possible to establish a new kind of money, "qualified money" or "social money", which could overcome some of the problems of the current financial system.
The Information Age will transform markets fundamentally. In the following, I will outline just some aspects of the now emerging "democratic, participatory market societies." Flexible self-organization will play a much bigger role than today. The emergence of "Prosumers" illustrates this. These are consumers who participate in the production of the products they buy. Instead of just selecting existing products from a catalogue or choosing the special features of a personalized car, consumers will be able to create new components of products, new designs, or even entirely new products. For example, they could use a 3D printer to produce their own cell phone cover and distribute it to others. Or they could come up with their own fashion and upload it to a company webpage to produce it for them, their family, friends, and colleagues, or indeed customers all over the world. People could also distribute their own books, their own music and their own movies. Or they could put a team together to construct more sophisticated products. 

An "innovation ecosystem" of flexible "projects"

While the 20th century was an era of democratization of consumption, the 21st century can become an era of democratization of production. Next to today’s companies, flexible, participatory forms of production will emerge, which I term "projects". Creative minds will come together to realize joint project ideas. After completing a project, everyone will be looking for another project or two, and so on. Social media platforms such as Amazon Mechanical Turk will make it possible to bring ideas and skilled workers together. As a consequence, this will lead to a more direct participation of people in production processes. There will also be a much greater diversity of products, tailored to individual needs. Thus, while computers will increasingly replace our current types of routine and executive work, we will have an opportunity to replace these jobs by more creative activities. Production by large corporations will then be complemented by an innovation ecosystem made up of thousands of projects. The huge range of smartphone apps, which platforms such as app stores have enabled, gives just a first idea of the unlimited possibilities for new projects. Open Data and the Web2.0, Web3.0, etc. will further accelerate this development.
However, Europe has not found its place in this new innovation universe, yet. Suitable institutions must first be established: the aforementioned reputation system is just one of them. Furthermore, open platforms are needed to enable participation and cooperation. In order to encourage an open exchange of information and the emergence of an innovation ecosystem, new incentive systems are required, which reward creative contributions. For this, the relevance of innovations must be made measureable, and inventors must be compensated for the use their ideas, e.g. with micropayments. Last but not least, we need a new science, which helps us to understand and create the participatory market society. While current economics ("economics 1.0") is tailored to "homo economicus", the emerging "economics 2.0" must be tailored to "homo socialis", the networked decision-maker. These and further institutions should be part of a far-reaching strategy to create an "innovation accelerator".
An age of creativity and participation is ahead of us. We just have to use the opportunities that modern information and communication technologies offer. Reputation systems and social media can promote awareness of the risks and benefits of our available decision alternatives. In particular, they can help us to address challenges such as global warming and other problems in a more cooperative and sustainable way. 


Dirk Helbing, Economics 2.0: The natural step towards a self-regulating, participatory market society., Evolutionary and Institutional Economics Review 10(1), 3-41 (2013), see http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2267697; A new kind of economy is born – Social decision-makers beat the “homo economicus”, see http://arxiv.org/abs/1309.7453; for related videos search youtube.com for “economics 2.0” and the TEDx talk at http://www.youtube.com/watch?v=nsrRo9x0j80; also see "Countering climate change with climate olympics" at http://www.youtube.com/watch?v=TaRghSuzBYM.    

Wednesday, 11 December 2013


Guest Post By Vincenzo Pavone [1] (IPP-CSIC) and Elvira Santiago (IPP-CSIC)

Big Brother 2.0?

No doubt, after the Snowden revelations and the recent confrontation between Germany and the US, several citizens will be asking themselves whether their private communications are under surveillance, and to what extent. This very event has triggered intensive debate in the media and in the political arenas of several European countries not only about the extent and purpose of the surveillance programs, but also about one of the technologies that are being used to arrange such surveillance: that is Big Data. Big data is high-volume, high-velocity and high-variety information assets that demand cost-effective, innovative forms of information processing for enhanced insight and decision-making.[2]

It must be acknowledged that there are different ways of using Big Data, and that the application of this set of technologies does not necessarily need to be oriented towards the surveillance of individual citizens. For instance, data can be anonymised, which allows research to be conducted and data to be extracted and analyzed without preserving any link between the data and the citizens to whom these data are related.

Is technology neutral?

However, this is not equal to saying that Big Data is a neutral technology. Any technology, regardless of how many uses it may have, is never neutral. Technologies, or rather sociotechnical practices, can never be understood as stand alone pieces of human art crafts because they only work and make sense in a network of socially constructed meanings, practices, organizational protocols and tailor-made jargons. They come with their own ethics, their own values. These values reflect the dominant political priorities and ethical values of the societal stakeholders producing and using such technologies. They may indeed change over time, but they will do so along with the changes occurring in the society adopting, sustaining and implementing such sociotechnical practices.   

This is, in a few words, the basic assumption proposed by what is known as a co-production approach in science and technology studies [3]: science and social order are co-produced and they live in a mutually constitutive relationship. Producing new scientific knowledge, as well as the new technological tools stemming from such knowledge, produces new forms of social order, and the opposite is also true: in order to produce new forms of social order, new knowledge and technical tools are constantly fabricated.

Of cars and Big Data

An example, perhaps, may illustrate this better. If asked about the cost of a specific car, we would normally answer by pointing at the price of that car. But that is hardly the actual cost… or better that is the cost only if seen from a specific point of view, which externalizes all the real costs of a car and narrows the question down to the transaction between the car dealer and the potential customer. However, cars, as a technology, only make sense as part of a sophisticated network of sociotechnical practices that needs to be constantly maintained to ensure that cars can fully operate across a given space. Cars need roads, police, laws, speed cameras, hospital, doctors, insurance companies, mechanics, gasoline pumps, etc. Without these sociotechnical infrastructures and practices, a car is simply a meaningless, useless box with five seats and four wheels. All these infrastructures have a cost and we accept that most of these costs are to be paid collectively by the citizens, often via the public system of tax collection. And why do we do so? Because we believe that cars are a socially legitimate way to move around.

If that is true for cars, it is even more so for Big Data. The latter, as a sociotechnical practice of security, only can be understood in a society that understands security as a function of surveillance. This is why, in so far as security is concerned, Big Data could never be anonymised as it would not make sense to have millions of data proceeding from harmless citizens’ communication without having name and surname (and much more) on it. The question, thus, is not whether we are spied or not, but rather: how did we come to pursue a concept of security, where many seem to believe that the latter can only be increased through massive surveillance programs operated through Big Data technologies?

A paradigm shift concept of security?

While in the 1990s, human security was associated with human development, human rights and multilateralism, in the aftermath of the Twin Towers attack it has evolved into a new, encompassing term that questions the separation between internal and external security: religious fundamentalism, ethnic conflicts and guerrilla-type wars are sources of threats that can well come from inside the state borders [4]. As a result, internal and external security agendas have eventually merged together [5].  Drug-trafficking, undocumented migration, and economic crimes cease to be an issue of justice or social integration and, overloaded with urgency and exceptionality, get subject to a new security approach emphasizing threat anticipation.

In a regime of threat anticipation, risk assessment and risk management become the cornerstone of a comprehensive approach that is geared to constant detection and prevention of the threats and risks. In this new approach, security is expanded well beyond the criminal domain in order to cope with any sort of suspicious behavior, information or action that could potentially constitute a threat. The resulting securitization of people’s movements and actions cannot be confined to migrants: under the new concept of security, controlling and integrating all sorts of information about ordinary citizens is nothing but inexorable.

The constitutive role of security technologies

In this approach to security, surveillance-oriented security technologies, and the analysis of Big Data is one of them, play a constitutive role: they are part of a new social order. As it has become impossible to conceive security without technology, we are permanently exposed to a technological fix approach to the problem of security: the focus constantly shifts from the search for a (complex) variety of causes and factors that has produced the on-going transformation of security threats to (simple) series of technological remedies that could be conceived, developed and implemented to keep these challenges under control.

Inevitably, the successful deployment of new security technologies under this new holistic concept of security comes at a cost: a restriction of civil liberties and individual privacy. Security and liberty get framed as two interchangeable goods that could be traded against each other: any increase in security requires an equivalent contraction of civil liberties. As the increase of security levels is intrinsically associated with an ever-increasing implementation of surveillance technologies, it does not consider the possibility of increasing security levels through either non-surveillance-oriented technologies or through non-technological actions and interventions.

Without freedom, we are no longer citizens

This is how we got to the point where millions of citizens around the world are spied indiscriminately. However, once we have lost our privacy, we can no longer act, meet, communicate, share or express ourselves freely. Under surveillance, regardless of whether we have something to hide or not, we cannot enjoy our basic civil and political rights. It is in this context that we have to understand Big Data. They are key to the development and implementation to a specific vision of what needs to be promoted as social order. Needless to say, this specific view of a desirable social order is at the same time promoting and fostering the development and implementation of Big Data.

This is why developing such powerful technologies and then hope that a few parliamentary bills will prevent their full implementation is wishful thinking. Rather, we need to learn to conceive security in different terms, as a shared responsibility and not only a function of repressive and preventive surveillance. Social and economic factors such as social and cultural integration, welfare supports, rule of law, fair redistribution of resources and citizens’ participation are at least as important. We often hear that without security, citizens cannot be free. Sure, this is true. However, without freedom, no matter how safe, we are no longer citizens.

[1] Corresponding author: Vincenzo Pavone, Institute of Public Goods and Policies (IPP), Consejo Superior Investigaciones Científicas, Madrid, SPAIN. Vincenzo.pavone@csic.es
[3] Jasanoff, S. 2004. States of knowledge: the co-production of science and social order: Psychology Press
[4] Lutterbeck, D. (2005) "Blurring the dividing line: The convergence of internal and external security in Western Europe," European Security 14(2): 231-53.
[5] Bigo, D. (2000) "Internal and external securitisations in Europe," International Relations Theory and European Integration: Power, Security and Community: 154.

Tuesday, 15 October 2013



The recent revelation that the National Security Agency collects the personal data of United States citizens, allies and enemies alike has broken the traditional model governing the bond between science and society.

Most breakthrough technologies have dual uses. Think of atomic energy and the nuclear bomb or genetic engineering and biological weapons. This tension never gives way. Our only hope to overcoming it is to stop all research.

But that is unrealistic. Instead, the model we scientists follow is simple: We need to be transparent about the potential use and misuse of our trade. We publish our results, making them accessible to everyone. And when we do see the potential for abuse, we speak up, urging society to reach a consensus on how to keep the good but outlaw the bad.

As the NSA secretly developed its unparalleled surveillance program, relying on a mixture of tools rooted in computer and social sciences, this model failed. Scientists whose work fueled these advances failed to forcefully articulate the collateral dangers their tools pose. And a political leadership, intoxicated by the power of these tools, failed to keep their use within the strict limits of the Constitution.

It’s easy to see why this happened. After all, the benefits of Big Data and the science behind it are hard to overlook. Beyond the many digital applications that make our life increasingly easy today, data science holds promise for emergency response and for stopping the next virus from turning into a deadly pandemic. It also holds the key to our personal health, since our activity patterns and disease history are more predictive of our future disease than our genes.

For researchers involved in basic science, like myself, Big Data is the Holy Grail: It promises to unearth the mathematical laws that govern society at large. Motivated by this challenge, my lab has spent much of the past decade studying the activity patterns of millions of mobile phone consumers, relying on call patterns provided by mobile phone companies. This data was identical to what NSA muscled away from providers, except that ours was anonymized, processed to help research without harming the participants. In a series of research papers published in the journals Science and Nature, my team confirmed the promise of Big Data by quantifying the predictability of our daily patterns, the threat digital viruses pose to mobile phones and even the reaction people have when a bomb goes off beside them.

We also learned that when it comes to our behavior, we can’t use only two scales — one for good and the other for bad. Rather, our activity patterns are remarkably diverse: For any act labeled “unusual” or “anomalous,” such as calling people at odd hours or visiting sensitive locations outside our predictable daily routine, we will find millions of individuals who do just that as part of their normal routine. Hence identifying terrorist intent is more difficult than finding a needle in a haystack — it’s more like spotting a particular blade of hay.

Let’s face it: Powered by the right type of Big Data, data mining is a weapon. It can be just as harmful, with long-term toxicity, as an atomic bomb. It poisons trust, straining everything from human relations to political alliances and free trade. It may target combatants, but it cannot succeed without sifting through billions of data points scraped from innocent civilians. And when it is a weapon, it should be treated like a weapon.

To repair the damage already done, we researchers, with a keen understanding of the promise and the limits of our trade, must work for a world that uses science in an ethical manner. We can look at the three pillars of nuclear nonproliferation as a model for going forward.

The good news is that the first pillar, the act of nonproliferation itself, is less pertinent in this context: Many of the technologies behind NSA’s spying are already in the public domain, a legacy of the openness of the scientific enterprise. Yet the other two pillars, disarmament and peaceful use, are just as important here as they were for nuclear disarmament. We must inspect and limit the use of this new science for military purposes and, to restore trust, we must promote the peaceful use of these technologies.

We can achieve this only in alliance with the society at large, together amending universal human rights with the right to data ownership and the right of safe passage.

Data ownership states that the data pertaining to my activity, like my browsing pattern, shopping habits or reading history, belongs to me, and only I control its use. Safe passage is the expectation that the information I choose to transfer will reach its intended beneficiaries without being tapped by countless electronic ears along the way. The NSA, by indiscriminately tapping all communication pipelines, has degraded both principles.

Science can counteract spying overreach by developing tools and technologies that, by design, lock in these principles. A good example of such a design is the Internet itself, built to be an open system to which anyone could connect without vetting by a central authority. It took decades for governments around the world to learn to censor its openness.

This summer, while visiting my hometown in Transylvania, I had the opportunity to talk with a neighbor who spent years as a political prisoner. Once freed, for decades to come, he knew that everything he uttered was listened to and recorded. He received transcripts of his own communications after the fall of communism. They spanned seven volumes. It was toxic and dehumanizing, a way of life that America has repeatedly denounced and fought against. 

So why are we beginning to spread communism 2.0 around the world, a quarter-century after the Iron Curtain’s collapse? This is effectively what NSA surveillance has become. If we scientists stay silent, we all risk becoming digitally enslaved. 

Posted with permission.

Albert-László Barabási is a physicist and network scientist at Northeastern University and Harvard Medical School, and the author of “Bursts: The Hidden Patterns Behind Everything We Do.”

Wednesday, 11 September 2013

A New Kind of Economy is Born

Social Decision-Makers Beat the "Homo Economicus"
by Dirk Helbing (ETH Zurich)

The Internet and Social Media change our way of decision-making. We are no longer the independent decision makers we used to be. Instead, we have become networked minds, social decision-makers, more than ever before. This has several fundamental implications. First of all, our economic theories must change, and second, our economic institutions must be adapted to support the social decision-maker, the "homo socialis", rather be tailored to the perfect egoist, known as "homo economicus".

The financial, economic and public debt crisis has seriously damaged our trust in mainstream economic theory. Can it really offer an adequate description of economic reality? Laboratory experiments keep questioning one of the main pillars of economic theory, the "homo economicus". They show that the perfectly self-regarding decision-maker is not the rule, but rather the exception [1,2]. And they show that markets, as they are organized today, are undermining ethical behavior [3].

Latest scientific results have shown that a "homo socialis" with other-regarding preferences will eventually result from the merciless forces of evolution, even if people optimize their utility, if offspring tend to stay close to their parents [4]. 1 

Another, independent study was recently summarized by the statement "evolution will punish you, if you're selfish and mean" [5]. Is this really true? And what implications would this have for our economic theory and institutions?

In fact, the success of the human species as compared to others results mainly from its social nature. There is much evidence that evolution has created different incentive systems, not just one: besides the desire to possess (in order to survive in times of crises), this includes sexual satisfaction (to ensure reproduction), curiosity and creativity (to explore opportunities and risks), emotional satisfaction (based on empathy), and social recognition (reputation, power). Already Adam Smith noted: "How ever selfish man may be supposed, there are evidently some principles in his nature, which interest him in the fortune of others, and render their happiness necessary to him, though he derives nothing from it." 2

Dirk Helbing, professor of sociology at ETH Zurich and complexity scientist concludes: "The social nature of man has dramatic implications, both for economic theory and for the way we need to organize our economy." As we are more and more connected with others, the "homo economicus", i.e. the independent decision-maker and perfect egoist, is no longer an adequate representation or good approximation of human decision-makers. "Reality has changed. We are applying an outdated theory, and that's what makes economic crises more severe," says Helbing.

Outdated theory, outdated institutions

In fact, recent experimental results suggest that the majority of decision-makers are of the type of a "homo socials" with equity- or equality-oriented fairness preferences [1,6]. The "homo socialis" is characterized by two features: interdependent decision-making that takes into account the impact on others and conditional cooperativeness. However, the "homo socialis" takes self-determined, free decisions. He is not ripping off others, afterwards giving back some of the benefits to others through taxes or philanthropy. The "homo socialis" decides rather differently, more considerately, recognizing that friendly and fair behavior can generate better outcomes for everybody.

"But social behavior is vulnerable to exploitation by the 'homo economicus'," continues Helbing. In a selfish environment, the 'homo socialis' cannot thrive. In other words, if the settings are not right, the 'homo socialis' behaves the same as the 'homo economicus'. "That's probably why we haven't noticed its existence for a long time," believes Helbing. "Our theories and institutions were tailored to the 'homo economicus', not to the 'homo socialis'." 

In fact, many of today's institutions, such as homogeneous markets with anonymous exchange, undermine cooperation in social dilemma situations, i.e. situations in which cooperation would be favorable for everyone, but non-cooperative behavior promises additional benefits [7, Fig. 2].

New institutions for a global information society
In the past we have built public roads, parks and museums, schools, libraries, universities, and homogeneous markets on a global scale. What would be suitable institutions for the 21st century? "Reputation systems can transfer the success principles of social communities to our globalized society, the global village", suggests Helbing. Most people and companies care about reputation. Therefore, reputation systems could support socially oriented decision-making and cooperation, with better outcomes for everyone [8]. In fact, reputation systems spread on the Web 2.0 like wildfire. People rate products, sellers, news, everything, be it at amazon, ebay, or trip adviser. We have become a "like it" generation, because we listen to what our friends like.

Importantly, recommender systems should not narrow down socio-diversity, as this is the basis of happiness, innovation and societal resilience. "We don't want to live in a filter bubble, where we don't get an objective picture of the world anymore," says Helbing with reference to Eli Pariser [9]. Therefore, reputation systems should be pluralistic, open, and user-centric. "Pluralistic reputation systems are oriented at the values and quality criteria of individuals," explains Helbing, "rather than recommending what a company's reputation filter thinks is best. Self-determination of the user is central. We must be able to use different filters, choose the filters ourselves, and modify them." The diverse filters would mine the ratings and comments that people leave on the Web, but also consider how much one trusts in certain information sources.

"Reputation creates benefits for buyers and sellers," says Helbing. A recent study shows that good reputation allows sellers to take a higher price, while customers can expect a better service [10]. Reputation systems may also promote better quality as well as socially and environmentally friendly production, suggests Helbing. "This could be a new approach to reach more sustainable production, based on self-regulation rather than enforcement by laws." One day, reputation systems may also be used to create a new kind of money, speculates Helbing. The value of "qualified money" would depend on it's reputation and thereby create incentives to invest in ways that increase a money unit's reputation. It might create a more adaptive financial system and help to mitigate the recurrent crises we are facing since hundreds of years. But the details still have to be worked out.

Benefits of a self-regulating economy

Reputation systems could overcome some of the unwanted side effects of anonymous exchange thanks to pseudonymous or personal interactions. Thereby, they could potentially counter "tragedies of the commons" such as global warming, environmental exploitation and degradation, overfishing, .. - constituting some of our major unsolved global problems. We can witness such kinds of "social dilemma problems" everywhere. So far, governments try to fix them with top-down regulations and punitive institutions. However, these are very expensive, and often quite ineffective. "Basically all industrialized countries suffer from exploding debts," says Helbing. "I believe we cannot pay for this much longer, we are at the limit. We need a new approach." As Albert Einstein pointed out: "We cannot solve our problems with the same kind of thinking that created them."

Institutions supporting the "homo socialis" such as suitably designed reputation systems would enable a self-regulation of socio-economic systems. "But self-regulation does not mean that everyone can choose the rules he likes," explains Helbing. "It only works with an other-regarding element. The self-regulation rules must be able to achieve a balance between the interests of everyone, who is affected by the externalities of a decision."

Helbing explains the benefits: "Other-regarding decisions can overcome the classical conflict between economic and social motives. Self-regulation could also overcome the struggle between the bottom-up organization of markets and the top-down regulation by politics. This would remove a lot of friction from our current system, making it much more efficient - in the same way as the transition from centrally planned economies to self-organized markets has often created huge efficiency gains."

This can be illustrated with an example from urban traffic management. "Traffic control is a problem where not everybody's desires can be satisfied immediately and at the same time, like in economic systems. It is a so-called NP-hard optimization problem - the computational effort explodes with system size, as for many economic optimization problems, e.g. in production and logistics." The study compares three kinds of control: A centralized top-down regulation by a traffic center, the classical control approach, and two decentralized control approaches. The first one assumes that each intersection independently minimizes the waiting times of approaching vehicles, as a "homo economicus" would do. The second one decides in an other-regarding way: it interrupts the minimization of waiting times, when this is needed to avoid spill-over effects at neighboring intersections. Helbing summarizes: "The 'homo economicus' approach works well up to a moderate utilization of intersections, but queue lengths get out of control long before the intersection capacity is reached. The bottom-up self-regulation based on the principle of the 'homo socialis' approach beats both, the centralized top-down regulation and the bottom-up self-organization based on principles of the 'homo economicus'. Other-regarding behavior improves the coordination among neighboring intersections. It makes Adam Smith principle of the 'invisible hand' work even at high utilizations."

Economics 2.0: Emergence of a participatory market society

But will such a self-regulating system ever be implemented? Helbing is convinced: "It's already on its way. The Web 2.0, in particular reputation systems and social media are driving the transition towards a new economy, the economy 2.0. We see already a new trend towards decentralized, local production and personalized products, enabled by 3D printers, app stores, and other technologies."

Such developments will eventually create a participatory market society. "Prosumers", i.e. co-producing consumers, the new "makers" movement, and the sharing economy are some examples illustrating this. "Just think of the success of Wikipedia, Open Streetmap or Github. Open Streetmap now provides the most up-to-date maps of the world, thanks to more than 1 million volunteers." Helbing stresses: "This is just the beginning of a new era. A new intellectual framework is emerging, and a creative and participatory era is ahead. The paradigm shift towards participatory bottom-up self-regulation may be bigger than the paradigm shift from a geocentric to a heliocentric worldview. If we build the right institutions for the information society of the 21st century, we will finally be able to mitigate some very old problems of humanity. 'Tragedies of the commons' are just one of them. After so many centuries, they are still plaguing us, but this needn't be."

[1] Experts should note that there has been research on so-called "altruistic behavior" in social dilemma situations such as the prisoner's dilemma since more than 3 decades. However, if scientists would have understood the "homo socialis" with other-regarding preferences already before, the key concept of the "homo economicus" should have disappeared from the economic literature since a long time, but it didn't for a reason. In fact, the increasing empirical and experimental evidence for fairness preferences and unexpectedly high levels of cooperation in one-shot prisoner's dilemma, dictator and ultimatum games have been waiting for a convincing theoretical explanation until very recently. It is important here to distinguish between other-regarding preferences and cooperative ("altruistic") behavior. Other-regarding preferences means that people intentionally do not maximize their payoffs, but try to consider and improve the benefits of others. Most game theoretical work is strictly compatible with the concept of "homo economicus", identifying mechanisms that make it advantageous in one way or another to cooperate. For example, if the "shadow of the future" in repeated prisoner's dilemma interactions is long enough, it creates a higher payoff when people cooperate, and that's why they do it. In other words, some mechanisms such as repeated interactions, punishment, transfer payments, and others change the payoff structure of a prisoner's dilemma game such that there is no dilemma anymore. Martin Nowak has mathematically shown that many such mechanisms can be understood with Hamilton's rule, according to which people cooperate when the benefits of cooperation exceed the costs. Other work shows that cooperation in prisoner's dilemma games may survive if people imitate more successful behavior of neighbors, but if one believes in rational choice, why should people imitate, if they can reach a higher payoff by another behavior? In fact, all such cooperation in spatial prisoner's dilemma games disappears, if imitation is replaced by a "best response" rule, which assumes a strict maximization of utility, based on the previous decision of the interaction partners. In Ref. [4], Grund et al. have combined such a "best response" rule with standard evolutionary rules of mutation and selection, when people reproduce. The unexpected outcome was a "homo socialis", if offspring stay close to their parents, which they often do. But the transition is not smooth. It requires the population to go through a phase where unconditionally "friendly" behavior is dysfunctional, which happens only by "mistake" (due to mutations). Random spatio-temporal coincidence of people with friendly traits is equally important for other-regarding preferences to emerge. However, conditionally cooperative behavior resulting from other-regarding preferences may also occur between strangers, i.e. they do not require genetic relatedness, as the following movie shows: http://vimeo.com/65376719. In any case, spatio-temporal correlations (here: the co-evolution of individual preferences and behavior) can promote cooperation more than expected for a payoff-maximizing "homo economicus". These new discoveries mean that key concepts of both, the theory of evolution and of economics, must be reconsidered.

[2] Smith, A., The Theory of Moral Sentiments (A. Millar, London, 1759).

Further Reading:

[0] D. Helbing, Economics 2.0: The Natural step towards a self-regulating, participatory market society, Evolutionary and Institutional Economics Review (2013), see

[1] Henrich, J., R.Boyd, S. Bowles, C. Camerer, E. Fehr, H. Gintis, and R. McElreath, "In search of homo economicus: behavioral experiments in 15 small-scale societies," Am. Econom. Rev. 91, 73-78 (2001).

[2] Murphy, R. O., K. A. Ackermann, and M. J. J. Handgraaf, "Measuring social value orientation," Judgment and Decision Making 6(8), 771-781 (2011).

[3] Falk, A. and N. Szech, "Morals and Markets," Science 340, 707-711 (2013).

[4] Grund, T., C. Waloszek, and D. Helbing, "How Natural Selection Can Create Both Self-and Other-Regarding Preferences, and Networked Minds," Scientific Reports 3:1480 (2013), see

[5] Adami, C. and A. Hintze, "Evolutionary instability of zero-determinant strategies demonstrates that winning is not everything," Nature Communications 4:2193 (2013); Evolution will punish you, if you're selfish and mean, see

[6] Berger, R., H. Rauhut, S. Prade, and D. Helbing, "Bargaining over waiting time in ultimatum game experiments," Social Science Research 41, 372-379 (2012).

[7] Helbing, D. "Globally networked risks and how to respond," Nature 497, 51-59 (2013).

[8] Milinski, M., D. Semmann, and H. J. Krambeck, "Reputation helps solve the tragedy of the commons," Nature 415, 424-426 (2002).

[9] Pariser, E., Filter Bubble (Carl Hanser, 2012).

[10] Przepiorka, W., "Buyers pay for and sellers invest in a good reputation: More evidence from eBay,'' The Journal of Socio-Economics 42, 31-42 (2013).

Dirk Helbing is Professor of Sociology, in particular of Modeling and Simulation, and member of the Computer Science Department at ETH Zurich. He earned a PhD in physics and was Managing Director of the Institute of Transport & Economics at Dresden University of Technology in Germany. He is internationally known for his work on pedestrian crowds, vehicle traffic, and agent-based models of social systems. Furthermore, he coordinates the FuturICT Initiative (http://www.futurict.eu), which focuses on the understanding of techno-socio-economic systems, using Big Data. His work is documented by hundreds of scientific articles, keynote lectures and media reports worldwide. Helbing is elected member of the World Economic Forum’s Global Agenda Council on Complex Systems and of the German Academy of Sciences “Leopoldina”. He is also Chairman of the Physics of Socio-Economic Systems Division of the German Physical Society and co-founder of ETH Zurich’s Risk Center.