SMART DATA: Running the Internet of Things as a Citizen Web
by Dirk Helbing , ETH Zurich
originally published in FuturICT blog.
Moore’s law, describing the exponential explosion of processing power and data production, is currently driving a fundamental transformation of our economy and society. While processing power doubles every 18 months, data volumes double every 12 months, which means that we literally produce as much data in one year as in the entire history of humankind (i.e. all previous years). However, this is not the end of the digital revolution. More and more “things” are now equipped with communicating sensors – fridges, coffee machines, tooth brushes, smartphones and smart devices. In ten years, this will connect 150 billion “things” with each other – and with 10 billion people. This creates the “Internet of Everything” and data volumes that double every 12 hours rather than every 12 months. How will this impact our society?
First of all, we will have an abundance of data about our world. Data will be cheap, and Big Data analytics can reach entirely new levels. Can we soon know everything? Can we build a Crystal Ball depicting and perhaps even predicting the course of events? Can we build superintelligent systems to run the world in a better way, based on cybernetic control principles? Would humans be steered by information? It seems that such technologies may now be built. For example, Baidu has started to work on a China brain project, which will learn to predict peoples’ behaviors based on their Internet searches. China has further initiated a project that rates the behavior of its citizens. This will make loans and jobs dependent on personal scores, which also depend on the links clicked in the Web – and on political opinions. Is Orwell’s Big Brother coming? Or is this the technology we need? Can the state act like a “wise king”? Or is a state that determines, how its citizens should be happy, a despot, as Immanuel Kant concluded?
In fact, there is no scientific method to determine the ‘goal function of society’ that ought to be maximized: should it be GDP per capita, sustainability, average life span, peace, or happiness? This is not clear and, furthermore, people are not like ants. The concept of omni-benevolence can’t work, because people pursue different goals, have different conceptions of good life. On the one hand, their pluralism results from social specialization, economic differentiation and cultural development. On the other hand, such pluralism hedges the risks to society and increases its ability to master unexpected disruptions. Consequently, as the complexity of a society increases, pluralism needs to increase as well.
The concepts of top-down optimization and control are limited by a number of factors:
(1) Data volume grows faster than the processing power. A growing share of data will never be processed. This creates a “flashlight effect”: we may see anything we want, but we need to know what to pay attention to. However, some systems are irreducibly complex, so every little detail can matter
(2) Due to limited communication bandwidth, an even smaller fraction of data can be processed centrally, such that a lot of local information, which is needed to produce good solutions, is ignored by a centralized optimization attempt.
(3) Systemic complexity can prevent real-time optimization, such that decentralized control approaches may perform better. This has been shown for self-organized traffic lights, which are flexibly and efficiently controlled by local traffic flows, while traffic control centers often fail to control traffic flows well.
(4) Further problems may be caused by overfitting, spurious correlations, meaningless patterns, noise and related classification errors – problems which are quite common in Big Data analytics. Another concern is that powerful information systems are attractive to organized criminals, terrorists and extremists, so they would sooner or later be corrupted or hacked.
To unleash the value of Big Data, it often takes theoretical models to look at the data in a useful way, as it is done in experiments at CERN’s elementary particle accelerator (which just keeps the 0.1 percent of all measurement data – the data that are actually needed to test a particular theoretical prediction). A similar finding is made when trying to predict epidemic spread: amodel-based analysis with little data is more powerful than brute force Big Data analytics such as Flu Trends. Therefore, Michael Macy recently concluded: “Big Data is the beginning of theory, not the end”, and most experts agree. This is in sharp contrast to Chris Anderson’s earlier claim that “The data deluge makes the scientific method obsolete.”
Some might say that Singapore, which considers itself a “social laboratory”, is a good example for a country that has greatly benefited from data-driven decision-making. Western democracies envy the country for its quick development and economic growth rate, but we must also consider that Singapore has been a tax haven, and it largely profits from imported innovations originating in predominantly Western democracies. Moreover, the political party in power has steadily lost votes over the past years in spite of all its successes. This is irritating, and we should therefore listen to Geoffrey West, the former president of the Santa Fe Institute, who studied cities extensively. He points out that the country of Singapore is run like a company. However, 40-50 percent of the Top 500 companies disappear in a time period of just 10 years, while cities persist for hundreds of years due to their usually more inclusive governance approach. The reason for this is that even powerful decision-makers make mistakes, but when this happens, the mistakes tend to be big.
Where do we stand today? Big Data analytics is far from being able to understand the complexity of human behavior, but it is advanced enough to manipulate our decisions by individualized information such as personalized ads or nudging. Such approaches use a few thousand metadata that have been collected about every one of us. However, manipulating our decision doesn’t seem to be a good idea, because it undermines the “wisdom of crowds” – an effect on which the functionality of democracies and financial markets is based. Moreover, manipulating our decisions is likely to narrow down the variance of our choices, i.e. socio-economic diversity. On the one hand, this can foster political and societal polarization (or fragmentation). On the other hand, diversity is key for innovation, economic development, societal resilience, and collective intelligence. Losing socio-economic diversity is equally bad as losing bio-diversity. It can cause systemic malfunction or collapse.,
Moreover, given that about 50 percent of today’s jobs in the industrial and service sectors will be lost in the next 10-20 years, our societies are under pressure to come up with many new jobs in the emerging digital sector (or at least with sufficient income and meaningful activities to give our lives a meaning).
All of this calls for a fundamentally different strategy and an entirely new approach, particularly as we are faced with an increasing number of existential problems: an economic and public spending crisis, financial and political instability, increasing dangers of large-scale international conflicts or cyber wars, climate change with a mass extinction of species, and growing antibiotic resistance, to mention just a few of our global threats. We need to have more innovation capacity, and this means we need to unleash the creativity of people. Diversity can help trigger innovation, while information platforms and digital assistants can support coordination in a diverse and culturally rich world. A participatory approach, which allows everyone to contribute with his/her skills, ideas, and resources (as in citizen science, for example) can mobilize the full socio-economic potential and capacity of society. If many people are unemployed, have to do jobs that don’t fit their skills, or if they are excluded from socio-economic engagement, the competitiveness and well-being of a country is significantly reduced.
To unleash the good side of the digital revolution and new opportunities for everyone, we must provide useful and trustworthy information to everyone. In the same way as we have built public roads to promote the industrial age and public schools to fuel the service society, we need powerful public information systems and digital literacy to promote the digital era to come. Therefore, I propose to build a Planetary Nervous System that creates possibilities for pluralistic data use and opportunities for everyone to contribute to society and pursue flourishing lives.The Planetary Nervous System would use the sensor networks behind the Internet of Things and potentially also the sensors in our smartphones (currently about 15) to measure the world around us and build a data commons together. The critical question is how this can be done in a way that respects our privacy and minimizes misuse as compared to the benefits the system would create. It is time to learn how to do this.
The Nervousnet project has started to work on this. It aims to create an open and participatory information platform such as Wikipedia or OpenStreetMap, but for real-time data. In favor of security, scalability and fault tolerance, Nervousnet is based on distributed data and control. It will be run as a Citizen Web, i.e. built and managed by the users. This gives us maximum control over the data traces we produce. Each sensor can separately be turned on or off. External sensors (e.g. for smart home applications) can be added. Users can also decide what data to share and how frequently to record them. The shared data are anonymized, and they are deleted after a short period of time.
Nervousnet invites everyone to contribute to the creation of this powerful, but distributed and trustworthy information platform for the age of the “Internet of Everything”. It is an open platform that will allow developers to add own measurement procedures and Apps on top. These can be scientific applications, games, or business applications. This will allow everyone to provide data-driven services or products and establish own companies. In other words, Nervousnet could once be a global catalyst to create an information, innovation and production ecosystem that will produce new jobs and societal benefits. There is still a lot to be done though. We are currently working on end-to-end data encryption. We need to add multi-dimensional reputation, incentive and payment systems. We also plan to add a personal data store, as it was proposed by Sandy Pentland and others.
In perspective, Nervousnet will allow everyone to make better-informed decisions. It will offer five main functionalities. First, it will configure the sensor network to answer specific questions based on real-time measurements. For example, it will allow us to quantify the externalities of the interactions around us, which will make it possible to improve economic systems. Second, these measurements will be able to reveal the hidden forces underlying socio-economic change and other important intangible factors such as reputation and trust. This will fuel a better understanding of our complex, interdependent world, as it is now studied by Global Systems Science. Third, the Planetary Nervous System will create awareness about the problems and opportunities around us. Fourth, it will enable self-organizing systems through real-time feedbacks such as self-organized traffic light controls, industry-4.0-kind-of production systems, or new solutions to socio-economic problems based on locally applied interaction mechanisms. So, 300 years after the invention of the invisible hand, we can finally make it work for us, by combining real-time measurements with suitable feedbacks, as advised by complexity science and enabled by multi-dimensional incentive and exchange systems. Finally, Nervousnet will allow one to build digital assistants supporting collective intelligence. This is needed to master the combinatorial complexity of our increasingly interdependent world. So, an entirely new age with amazing new possibilities is ahead of us, fueled by information.
It is now within reach to build an information system that finally brings everything together: science, politics, business, and society. We can create self-organizing and self-improving systems with massively increased efficiency. The approach I propose is based on participation and compatible with democratic principles. It respects the autonomy of decision-making and supports free entrepreneurship, while considering externalities. Therefore, I also expect benefits for our environment and society. In particular, the information age may allow us to reduce the level of conflict, because information is an unlimited resource that offers endless creative possibilities. The digital economy is everything but a zero-sum game. Information can be reproduced as often as we like. To get more of it for us, we don’t have to take it away from others. Furthermore, considering that money is just a coordination mechanism to organize the distribution of scarce resources, we can now build a better, multi-dimensional money and incentive system that rewards digital co-creation.
So, what are we waiting for? Let’s build the digital society together! 
 D. Helbing, Thinking Ahead (Springer, Berlin, 2015)
 N. Wiener, The Human Use of Human Beings: Cybernetics and Society (Da Capo Press, Boston, 1954); E. Medina, Cybernetic Revolutionaries (MIT Press, 2011)
 A.D.I. Kramer, J.E. Guillory, and J.T. Hancock, Experimental evidence of massive-scale emotional contagion through social networks. Proceedings of the National Academy of Sciences of the United States of America 111, 8788-8790. This experiment was highly controversial, see here.
 see here.
 I. Kondor et al. Strong random correlations in networks of heterogeneous agents, J. Econ. Interact. Coord. 9, 203-232 (2014).
 S. Lämmer and D. Helbing (2008) Self-control of traffic lights and vehicle flows in urban road networks. JSTAT P04019; D. Helbing (2013) Economics 2.0: The natural step towards a self-regulating, participatory market society. Evolutionary and Institutional Economics Review 10, 3-41; see also http://www.stefanlaemmer.de/
 D. Lazer, R. Kennedy, G. King and A. Vespignani, The Parable of Google Flu: Traps in Big Data Analysis. Science 343, 1203-1205 (2014).
 see here.
 Foreign Policy, The Social Laboratory (July 29, 2014), see http://foreignpolicy.com/2014/07/29/the-social-laboratory/
 J. Lorenz, H. Rauhut, F. Schweitzer, and D. Helbing (2011) How social influence can undermine the wisdom of crowd effect. Proceedings of the National Academy of Sciences USA (PNAS) 108(28), 9020-9025
 S.E. Page, The Difference: How the Power of Diversity Creates Better Groups, Firms, Schools, and Societies (Princeton University, 2008)
 R.M. May, S.A. Levin, and G. Sugihara, Complex systems: Ecology for bankers, Nature 451, 893-895 (2008)
 J. Diamond, Collapse: How Societies Choose to Fail or Succeed (Penguin 2011); J.A. Tainter, The Collapse of Complex Societies (Cambridge University, 1990)
 F. Gianotti et al., A planetary nervous system for social mining and collective awareness, Eur. Phys. J. Special Topics 214, 49-75 (2012)
 see here.
 The Nervousnet app can be downloaded via Apple’s app store and Google’s play store. You can contact us at email@example.com
 D. Helbing, The Automation of Society Is Next ( 2015); You may also want to watch this related movie list