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Societal, Economic, Ethical and Legal Challenges of the Digital Revolution: From Big Data to Deep Learning, Artificial Intelligence, and Manipulative Technologies


In the wake of the on-going digital revolution, we will see a dramatic transformation of our economy and most of our societal institutions. While the benefits of this transformation can be massive, there are also tremendous risks to our society. After the automation of many production processes and the creation of self-driving vehicles, the automation of society is next. This is moving us to a tipping point and to a crossroads: we must decide between a society in which the actions are determined in a top-down way and then implemented by coercion or manipulative technologies (such as personalized ads and nudging) or a society, in which decisions are taken in a free and participatory way and mutually coordinated. Modern information and communication systems (ICT) enable both, but the latter has economic and strategic benefits. The fundaments of human dignity, autonomous decision-making, and democracies are shaking, but I believe that they need to be vigorously defended, as they are not only core principles of livable societies, but also the basis of greater efficiency and success.

“Those who surrender freedom for security (I would add “efficiency” or “performance” here as well) will not have, nor do they deserve, either one…”

Benjamin Franklin


  • Manipulative Technologies
  • Super-intelligent Machines
  • FuturICT
  • Planetary Nervous System
  • Informational Self-determination

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

This chapter by Dirk Helbing reprints the article Societal, Economic, Ethical and Legal Challenges of the Digital Revolution, published first on 21 May 2015 in Jusletter IT ( (reprinted with permission).

This document includes and reproduces some paragraphs of the following documents: “Big Data—Zauberstab und Rohstoff des 21. Jahrhunderts” published in Die Volkswirtschaft—Das Magazin für Wirtschaftspolitik (5/2014), see; for an English translation see chapter 7 of D. Helbing (2015) Thinking Ahead—Essays on Big Data, Digital Revolution, and Participatory Market Society (Springer, Berlin).

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    The point in time when this happens is sometimes called “singularity”, according to Ray Kurzweil.

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    Such movies often serve to familiarize the public with new technologies and realities, and to give them a positive touch (including “Big Brother”).

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    For example, the following approach seems superior to what Google Flu Trends can offer: D. Brockmann and D. Helbing, The hidden geometry of complex, network-driven contagion phenomena. Science 342, 1337–1342 (2013).

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    Remember that it takes about two decades for a human to be ready for responsible, self-determined behavior. Before, however, he/she may do a lot of stupid things (and this may actually happen later, too).

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    It’s quite insightful to have two phones talk to each other, using Apple’s Siri assistant, see e.g. this video:

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    For example, it recently became public that Facebook had run a huge experiment trying to manipulate people’s mood: This created a big “shit storm”: However, it was also attempted to influence people’s voting behavior: OkCupid even tried to manipulate people’s private emotions: It is also being said that each of our Web searches now triggers about 200 experiments.

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    M. Bloodgood and C. Callison-Burch, Using Mechanical Turk to build machine translation evaluation sets,

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    In an extreme case, this might even be a criminal act.

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    Interestingly, for IBM Watson (the intelligent cognitive computer) to work well, it must be fed with non-biased rather than with self-consistent information, i.e. pre-selecting inputs to get rid of contradictory information reduces Watson’s performance.

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    It seems, for example, that the attempts of the world’s superpower to extend its powers have rather weakened it: we are now living in a multi-polar world. Coercion works increasingly less. See the draft chapters of my book on the Digital Society at for more information.

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    even though one never knows before what kinds of ideas and social mechanisms might become important in the future—innovation always starts with minorities.

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    C.A. Hidalgo et al. The product space conditions the development of nations, Science 317, 482–487 (2007). According to Jürgen Mimkes, economic progress (which goes along with an increase in complexity) also drives a transition from autocratic to democratic governance above a certain gross domestic product per capita. In China, this transition is expected to happen soon.

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    This is the main reason why one should support pluralism.

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    See the draft chapters of D. Helbing’s book on the Digital Society at, particular the chapter on the Complexity Time Bomb.

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    One might distinguish these into two types: dictatorships based on surveillance (“Big Brother”) and manipulatorships (“Big Manipulator”).

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    As digital weapons, so-called D-weapons, are certainly not less dangerous than atomic, biological and chemical (ABC) weapons, they would require international regulation and control.

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    Note that the scientific field of complexity science has a large fundus of knowledge how to reach globally coordinated results based on local interactions.

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    After all, humans have to register, too.

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    Some problems are so hard that no government and no company in the world have solved them (e.g. how to counter climate change). Large multi-national companies are often surprisingly weak in delivering fundamental innovations (probably because they are too controlling). That’s why they keep buying small and medium-sized companies to compensate for this problem.

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    Similar problems are known for software products that are used by billions of people: a single software bug can cause large-scale problems—and the worrying vulnerability to cyber attacks is further increasing.

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    We have demonstrated such an approach in the Virtual Journal platform (

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    In fact, to avoid mistakes, the more we are flooded with information the more must we be able to rely on it, as we have increasingly less time to judge its quality.

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    This could end up in a way of organizing our society that one could characterize as “Big Manipulator” (to be distinguished from “Big Brother”).

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    The following recent newspaper articles support this conclusion:,, In fact, based on a statistical analysis of Jürgen Mimkes and own observations, I expect that China will now undergo a major transformation towards a more democratic state in the coming years. First signs of instability of the current autocratic system are visible already, such as the increased attempts to control information flows.

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    See D. Helbing, Globally networked risks and how to respond. Nature 497, 51–59 (2013). Due to the problem of the Complexity Time Bomb ( abstract_id=2502559), we must either decentralize our world, or it will most likely fragment, i.e. break into pieces, sooner or later.

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    Having a greater haystack does not make it easier to find a needle in it.

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    This is particularly well-known for the problem of ambiguity. For example, a lot of jokes are based on this principle.

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    We know this also from so-called “phantom traffic jams”, which appear with no reason, when the car density exceeds a certain critical value beyond which traffic flow becomes unstable. Such phantom traffic jams could not be predicted at all by knowing all drivers thoughts and feelings in detail. However, they can be understood for example with macro-level models that do not require micro-level knowledge. These models also show how traffic congestion can be avoided: by using driver assistance systems that change the interactions between cars, using real-time information about local traffic conditions. Note that this is a distributed control strategy.

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    Assume one knows the psychology of two persons, but then they accidentally meet and fall in love with each other. This incident will change their entire lives, and in some cases it will change history too (think of Julius Caesar and Cleopatra, for example, but there are many similar cases). A similar problem is known from car electronics: even if all electronic components have been well tested, their interaction often produces unexpected outcomes. In complex systems, such unexpected, “emergent” system properties are quite common.

  75. 75.

    In case of cascade effects, a local problem will cause other problems before the system recovers from the initial disruption. Those problems trigger further ones, etc. Even hundreds of policemen could not avoid phantom traffic jams from happening, and in the past even large numbers of security forces have often failed to prevent crowd disasters (they have sometimes even triggered or deteriorated them while trying to avoid them), see D. Helbing and P. Mukerji, Crowd disasters as systemic failures: Analysis of the Love Parade disaster, EPJ Data Science 1:7 (2012).

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    I am personally convinced that the level of randomness and unpredictability in a society is relatively high, because it creates a lot of personal and societal benefits, such as creativity and innovation. Also think of the success principle of serendipity.

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    D. Helbing et al. FuturICT: Participatory computing to understand and manage our complex world in a more sustainable and resilient way. Eur. Phys. J. Special Topics 214, 11–39 (2012).

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    As we know, intellectual discourse can be a very effective way of producing new insights and knowledge.

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    Due to the data deluge, the existing amounts of data increasingly exceed the processing capacities, which creates a “flashlight effect”: while we might look at anything, we need to decide what data to look at, and other data will be ignored. As a consequence, we often overlook things that matter. While the world was busy fighting terrorism in the aftermath of September 11, it did not see the financial crisis coming. While it was focused on this, it did not see the Arab Spring coming. The crisis in Ukraine came also as a surprise, and the response to Ebola came half a year late. Of course, the possibility or likelihood of all these events was reflected by some existing data, but we failed to pay attention to them.

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    The classical telematics solutions based on a control center approach haven’t improved traffic much. Today’s solutions to improve traffic flows are mainly based on distributed control approaches: self-driving cars, intervehicle communication, car-to-infrastructure communication etc.

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    This approach corresponds exactly how Big Data are used at the elementary particle accelerator CERN; 99.9% of measured data are deleted immediately. One only keeps data that are required to answer a certain question, e.g. to validate or falsify implications of a certain theory.

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    J. van den Hoven et al. FuturICT—The road towards ethical ICT, Eur. Phys. J. Special Topics 214, 153–181 (2012).

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    This probably requires different levels of access depending on qualification, reputation, and merit.

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Helbing, D. (2019). Societal, Economic, Ethical and Legal Challenges of the Digital Revolution: From Big Data to Deep Learning, Artificial Intelligence, and Manipulative Technologies. In: Helbing, D. (eds) Towards Digital Enlightenment. Springer, Cham.

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