Seizing the X-events. The sixth K-wave and the shocks that may upend it

Seizing the X-events. The sixth K-wave and the shocksthat may upend it

Markku Wilenius, ,Author Vitae,

John Castib, cAuthor Vitae

a University of Turku, Turku School of Business, Finland Futures Research Centre Helsinki Office, Korkeavuorenkatu 25 A 2, FIN-00250 Helsinki, Finland

b The X-Center, Vienna, Austria

c The Center for Complex Systems and Enterprise, Stevens Institute of Technology, Hoboken, NJ, USA

Received 20 November 2013, Revised 24 September 2014, Accepted 12 December 2014, Available online 20 February 2015

Highlights

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Extreme events are a little understood part of long-term socio-economic waves.

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The upcoming 6th wave may contain surprises that are highly unlikelyto happen.

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By building alternative scenarios we help organisations to prepare and then to adapt to surprises.

Abstract

The article addresses the long-term patterns of societal change. In particular, it considers how certain high-impact, surprising events (“X-events”) can change existing trends and thus give rise to a

future that does not follow the “business-as-usual” default trend-following scenario. We look at the case of Kondratieff waves (“K-waves”), those socio-economic cycles by which dynamical societal patterns are often detected in futures studies. We postulate four hypothetical X-events and how they might fundamentally change the existing trend and thus take us to a very different kind of future. Finally, we recommend a set of principles through which organisations and countries can follow to deal with X-events should they occur.

Keywords

X-events;

Societal shocks;

Kondratieff cycles;

Scenarios;

Long-term futures;

Futures studies

1. Introduction: cycles, waves and patterns

Mathematicians have known for some time now that the long-term behaviour of any dynamical system is one of the two possible types: a periodic trajectory that repeats itself indefinitely in the same orbit over a finite period of time, or an aperiodic trajectory that never repeats itself but comes infinitesimally close to itself infinitely often. (Note: A seemingly third type of long-run behaviour, a fixed point at which the system settles down into a single state forever, is simply a degenerate version of the periodicorbit in which the period is 0.) So we see that two, and only two, behaviours are possible once the system settles down to a steady-state.

A mathematical world of perfect measurement, frictionless motion andthe like, however, is not the real world. And, in fact, in the real world of material particles and human approximations, it is the second type of long-term behaviour, the aperiodic trajectory, which is all we ever really observe. This empirical fact, together with a

second equally important fact that trends always end, gives rise to the observation that virtually all natural and human processes move in a wave-like manner that approximates, but never achieves, true periodic behaviour. So the ideal behaviour in mathematics with a definite, fixed period gives way in reality to behaviour with only an approximate period. As Gordon and Greenspan already showed already some decades back, systems that we think may be stable and behave in an orderly fashion in fact may later move to operate in a regime that is actually chaotic and unstable (Gordon and Greenspan, 1988).

With this mathematical and physical fact as background, let us turn to the primary focus of this article.

During the past few decades, a cottage industry of economists, technological forecasters, futurists and other seers has been occupied with exploring the idea of “long waves” of development. Themost famous of them, no doubt, is Alvin Toffler, with his best seller “third wave” (Toffler, 1980). Another idea of the waves or cycles was posited by the Russian economist Nikolai Kondratieff in the 1930s (Kondratieff, 1935). As outlined in the next section, “K-waves” of the type postulated by Kondratieff run on a cycle of about60 years. Each such wave is driven by a dominant technology, which in turn spawns economic, political and social changes of the forces put into play by the technology of the preceding wave. In the Kondratieff scheme of things, the first such wave unfolded in the latter part of the eighteenth century, and was driven by the steam engine. The most recent K-wave, the fifth in the sequence, began around 1970. Its game-changing technology was information processingand communication. According to some K-wavers, we are now in the early stages of the sixth K-wave (Kondratieff, 1935, Moody and Nogrady, 2010 and Nefiodow, 2006).

From an ontological point of view, one problem with this assignment of dominant technologies to these K-waves is that the length of a wave is so long that there has only been enough time for half a dozen such waves since the Industrial Revolution. Moreover, long-wave studies themselves have only been an action item in the intellectual landscape for fifty years (or less). Thus, the assignment of, say, the steam engine as the driver of the first K-wave is basically a just-so story, an ex post facto creation from

historical analysis, and in no way represented a prediction of what technology would drive the first wave. But now, futurists of all stripes are speculating about the upcoming sixth K-wave, making arguments that it will be driven by environmental technology, biotechnology, nanotechnology and the like. These are predictions, predictions made mostly by observing current trends and extrapolating them on a more-or-less straight line basis to 2050 or thereabouts.

But as we argue in this article, trends always end, to be replaced by new trends, and it is generally an extreme event (an “X-event”), like a major war, a pandemic, an asteroid impact or other such life-changing event, that prevents the current trend from continuing on its path. The goal of this paper is to examine several such possibleX-events and how they might occur, as a vehicle for questioning whether the picture painted by the conventional forecasters holds upto detailed scrutiny.

1.1. Trends and transitions

At a random moment in time, the generic behaviour of any social system is to be in a trending pattern. These special moments when the current trend is rolling over from one trend to another are the critical points. If that rolling over process involves great social damage in terms of lives lost, dollars spent and/or existential angst, we call the transition from the current trend to the new one an X-event. Here we focus solely on human-induced X-events, and ignore the ones that nature throws our way like hurricanes, earthquakes, asteroid impacts and the like.

A central question arising from the above scenario is: Can we predict where the critical points will occur? In situations where you have a large database of past observations about the process and/or a dynamical model that you believe in for the system's behaviour, then you can sometimes use tools of probability and statistics and/or dynamical system theory to identify these points with some degree of precision. This is often the case in the naturalsciences; but it's almost never the case in the social realm. In thehuman domain, we generally have too little data and/or no believablemodel, at least no data or model for the kinds of “shocks” that can send humankind back to a preindustrial way of life. In short, we aredealing with the “unknown unknowns.”

Before proceeding, it's worth taking a moment to contrast the ideas for anticipation of X-events outlined below with similar work. In particular, we note the studies by Sornette on what he terms “DragonKings” (Nefiodow, 2006) and the well-known books by Nassim Taleb on “black swans” (Casti, 2012a). Both authors properly focus attention on understanding the importance of our X-events as the agents of dramatic change, and offer insights into how to identify and even predict such life-changing events.

In the case of the dragon kings, Sornette takes a physicist's approach to develop a mathematical apparatus for ferreting out the impending appearance of an X-event from a database of past occurrences of phenomena, ranging from financial market gyrations tothe distribution of earthquake energies. Such techniques are of great value when such data is actually available. But when we speak of situations where the X-event of concern is something that has never taken place before or if there is simply too little data upon which to focus the mathematical techniques, then new ideas are needed. The old tools from dynamical system theory, probability theory and statistics are simply inapplicable.

The work by Taleb is focused primarily on emphasizing that X-events are simply not predictable using standard statistical tools, lookingfor outliers of probability distributions. He says such events are rare and have high impact, but then turns his attention to the psychology of event forecasting, outlining many examples of after-the-fact stories we humans tell ourselves in order to explain an X-event. He then goes on to advance the claim that prediction of X-events is flatly impossible. As we will discuss below, our position is midway between that of Sornette, who believes it is very possibleto forecast such events (if you have the data), and Taleb, who says that it's simply impossible.

In this X-events regime, it's unlikely that we'll ever be able to predict the location of the critical points with the same sort of accuracy and reliability that we're accustomed to in the natural sciences. This is due to the fact that events, X- or otherwise, are always a combination of context, which determines the space of possible events, and a random trigger that picks a particular event out of that spectrum of possibilities as being the one that's actually realised. In short, at any given time, the context, which

is always dynamically shifting, admits a variety of possible events that might be realised. The one event that is in fact actually observed/experienced at the next moment is determined by a random “shove” that sends the system into one “attractor” from the set of all possible events the context admits. Since by its very nature a random trigger has no pattern, it cannot be forecast. Hence, the specific event that turns up cannot be forecast either. Note that this does not mean that every possibility is equally likely. It simply means that while some possible events are more likely to be seen than others, the random factor can step in to give rise to a realised event that is a priori unlikely, thus surprising.

1.2. Complexity gaps and social mood

As all human systems are in fact a combination of two or more systems in interaction, not a single system in isolation, an important part of the answer to the question of measuring risk for unknown unknowns is to identify the level of complexity overload, or“complexity gap,” that emerges between the interacting systems. The size of that gap can then serve as a measure of the risk of a systemcollapse (Casti, 2012a).

To make the story as simple as possible, let's focus on the case of two systems in interaction, such as the financial services sector and the government regulators. The two systems each have their own level of complexity, usually associated in some way with the number of degrees of freedom the system has at its disposal to take independent actions at a given time. This complexity level is continually changing over the course of time, so that the complexitydifference between the two systems also rises and falls as time moves forward. This continually changing difference in complexity levels gives rise to what we can term a “complexity gap” between theinteracting systems.

As long as this gap doesn't grow too large, everything is fine and the two systems can co-exist in a comfortable level of harmonic balance. But as the gap widens, stresses emerge between the systems.And if the gap widens beyond a critical level, one or another (or both) system “crashes.” The only way to avoid this X-event is to narrow the gap. But human experience shows that voluntary downsizingalmost never happens, nor does “upsizing,” since the resources needed for upsizing generally have to be taken from the high-

complexity partner. So a systemic crash is the default outcome of a complexity gap extended beyond its sustainable limit (Tainter, 1988).

At the point of stress when the system is poised to crash, all it takes is an inherently unpredictable random shove on the system in one direction or another to push it over the edge into a new “phase”. Thus, where the system actually ends up after this X-event has taken place is inherently unpredictable. For human systems, the overall “social mood” of the population within which the system exists has a strong biasing effect on what event does or does not emerge as the “winner” from the spectrum of possible outcomes (Casti, 2010). This is because that mood, the belief a group has about its future, serves as a second element in shaping the landscape of events, the context within which the system carries outits activities.

The final question coming from this transition from trends to critical points to X-events and beyond is: what properties enable some systems to survive and possibly even prosper (i.e. be “reborn”)in the new environment that society faces after the X-event has run its course? The answer to this central question of long-range planning is tied up with the notion of system resilience. But beforediscussing that theme, it's worth a short intermezzo to re-examine the “fingerprints” of an X-event, and see just how it differs from what we might call a non-X, or an ordinary, event, compactly expressed as an “O-event.”

1.3. Shocks, O-events and X-events

First of all, the very rarity of an X-event means that we do not have a sufficiently rich database of past actions and behaviours to actually calculate a meaningful probability for an event Y to actually take place. While probability theorists and statisticians have developed an ingenious array of tools ranging from subjective probability theory to Bayesian analysis to extreme-event statistics to try to circumvent this obstacle, the fact remains that nailing down a probability you can believe in for a rare event to occur is just not possible. If it were, we would “probably” not have experienced things like the Great Recession of 2007–08, the 2003 East Coast power failure, and the damage to New Orleans from Hurricane Katrina. So when it comes to X-events, we need to invent

or discover ways to measure risk that captures what we mean when we say that this shock is more likely to take place here and now than it was previously. Here, our take on this problem is to advance the idea that the level of complexity mismatch between human infrastructure systems serves as just such a measure.

But rarity by itself is not enough for an X-event. It is more important that it be a surprise in the context within which the event takes place. Consider the action taken by the state of Cyprus to essentially confiscate money from large depositors in its banks in order to obtain a bailout loan from the European Central Bank in 2013. This action was a huge surprise to everyone, especially to those depositors, and definitely constitutes an X-event in our scheme of things. But if the action had been announced weeks or months ahead of time, rather than at 3 a.m. on a Sunday morning, andif it had involved closure of the banks so that a bank run were prevented, then the surprise factor of having upwards of 60% of youraccount disappear overnight would have been greatly reduced. The pain factor, of course, would have been largely unchanged, but depositors would have had some time to try to organise their affairsand work around the confiscation of their assets. But as it was, thesurprise and the pain were both huge.

The last ingredient involved in an X-event is the social damage the event inflicts on society when it takes place. Of course, if the shock is one that's never happened before, then it is problematic asto how to assess what the actual damage will be. To make such an evaluation we generally need to compare the shock with comparable shocks from the past. We look then at how the assumed situation differs from what's in the historical record, and build a fudge factor into our damage assessment to account for this difference. But how could this process work if there is no historical record to draw upon?

In summary, there are two very different regimes here. There's the normal regime, consisting of ordinary events (O-events) that have taken place many times in the past and for which there is a good setof data available upon which to base our tools for probabilities andpossible damages. Then there is the X-events regime for which those tools simply do not apply.

Generally, people like to take out insurance against an uncertain future. In everyday life, such insurance might be the normal type oflife, car and/or health insurance that most of us buy without thinking much about it. But large organisations like a corporation or a country cannot buy that kind of insurance to protect themselvesagainst the vagaries of the international currency markets or the fickleness of the electorate. Instead, these sorts of systems have to try to be resilient against shocks of such types. So the last ingredient in the saga of social dynamics is to consider the type ofproperties a system requires for it to really be able to cope with uncertainty.

1.4. Resilience and creative destruction

Contrary to popular belief, the notion of a system's “resilience” isnot just jargon terminology for stability. System resilience is a much deeper and more nuanced concept than the mere ability of a system to return to its former structure and mode of operation following a disturbance of some sort (Walker and Salt, 2006). In point of fact, returning to “doing what you were doing before” is never possible. The world moves on and you either move with it or you go out of business. So any idea of “stability”, at least in the way that term is used in both mathematics and everyday life, is a non-starter. But resilience is not about remaining stable in the face of uncertain disturbances (usually thought to be from outside the system itself, but not necessarily). Rather, it is about being able to assimilate the shock and continue to function, to be agile enough to recognise new opportunities created by the shock, and finally to be able to adapt to those new circumstances and even change your mode of operation in order to benefit from the shock. Inshort, a resilient system not only survives the initial shock, but may actually benefit from it.

Note also that the notion of resilience is not absolute; a system may be resilient to a particular shock, say a financial crisis, but totally vulnerable to collapse from another shock, like an Internet failure. So, in fact, resilience is a “package deal,” in the sense that it is totally intertwined with a particular type of shock. Thus, we cannot say that a system is resilient without specifying, or at least tacitly understanding, the shock that it is able to absorb and end up benefiting from.

A resilient system must be able to absorb or “assimilate” a shock and continue to function. It should also be “agile” enough to recognise new opportunities when faced with new circumstances created by the shock. And, finally, the resilient system should be ready to act on those opportunities in the sense of “adapting” to the changed environment if an adaptation will serve to enhance the system's survivability. Note here that agility and adaptability are two different things. The first refers to the system's ability to recognise changed circumstances, while adaptability means that the system is willing and ready to act upon that recognition so as to actually benefit from the shock, not simply survive it.

The idea of benefiting from an X-event raises an important question of time scale. When an X-event occurs, almost without fail it's seenas something negative, an occurrence to be avoided, since it usuallyinvolves a major change to the status quo. And that's just the sort of change most people like least. So in the short-term, the X-event is generally perceived as being a disaster of one type or another. Agood example is the meltdown of the Japanese nuclear power plant at Fukushima. It may well turn out that Fukushima was not the worst thing that ever happened to Japan; rather, it may well be the best thing that ever happened! Why? Simply because that mega X-event opened up a huge number of degrees of freedom for action in the social, political, economic and technology sectors in Japan that could never have been created by smooth, gradual, evolutionary change. It took a Fukushima-level revolutionary change to blast the country out of an orbit that it had been stuck in for the last fiftyyears. Only a major shock of the Fukushima type could shake up the relationship between society, government and industry needed to givethe country an opportunity to be “reborn.”

The story told above about the Japanese reaction to Fukushima is a variant of the famous idea of “creative destruction” originally proposed by the Austrian-American economist Joseph Schumpeter in the1930s (Schumpeter, 1939a). The type of X-events described here must take place in order for “eco-niches” to be created in the social landscape for new ideas, new products, and new ways of doing business to emerge. The dinosaurs were not resilient enough to survive the Yucatan asteroid impact 65 Ma ago, which opened up the niches for today's humans to emerge. The point here is that we should not regard X-events as something to be avoided; that cannot

usually happen, anyway. Rather, they should be seen as being as muchan opportunity as a problem. In the short term, they are a problem; in the longer-term perspective, they are an opportunity. The resilient organisation will recognise this duality and take steps today to capitalise on it for tomorrow.

Let's close this section by summarising the overall relationship between social mood, complexity gaps, critical points and system resilience by encapsulating them into the diagram below. Note that the term “resilience” does not appear in the diagram, but is an amalgam of the last two boxes, together with the last arrow in the diagram (Fig. 1).

<img class="figure large" border="0" alt="The Fundamental Diagram of Human Social Processes." src="http://origin-ars.els-cdn.com/content/image/1-s2.0-S0040162514003783-gr1.jpg" data-thumbEID="1-s2.0-S0040162514003783-gr1.sml" data-imgEIDs="1-s2.0-S0040162514003783-gr1.jpg" data-fullEID="1-s2.0-S0040162514003783-gr1.jpg">

Fig. 1.

The Fundamental Diagram of Human Social Processes.

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2. What constitutes “the future”?

Currently, future is looked and perceived with wildly diverse views.There are some schools of thought that insist – usually with some evidence from the trends of the past – our future will be defined byscarcity. At the other end, there are powerful visions — again

http://www.sciencedirect.com/science/article/pii/S0040162514003783?np=y#gr1

backed by evidence like the increasing speed of innovation that we are heading towards a world of abundance. Still others may point to the increasing fragility of the emerging system that may be on the brink of collapse at any given time, while some others point out that we are just at the doorstep of the greatest period of evolutionever experienced by the human mind (Randers, 2012, Diamandis and Kotler, 2012, Casti, 2012b, Costa, 2010 and Kurzweil, 2012).

Whatever we happen to believe in, there seems to be consensus on onething: never before in the history of humanity have we faced such demanding if interesting circumstances as we face today. Life on theplanet Earth seems to have come to a point we need to become much more careful about how we interact with natural systems. Scarcity ofresources such as water, food and energy, enormous waste problems, the death of ocean fisheries, the deforestation of tropical forests and loss of biodiversity are but a few of the pressing environmentalconcerns that have made the gap between the exploitation of natural resources and their availability increasingly clear, especially for the future. Population bomb is still ticking: not only the world population is still growing but simultaneously millions of people the world over are being lifted out of poverty to a higher standard of living, which put increasing pressure on precious natural resources. These factors taken together appear to lead to a Malthusian conclusion that once we have all had our piece of an already overeaten pie, there will not be enough left to sustain humanity on earth. In the end, the same processes that have providedunprecedented prosperity to humanity during the past two hundred years are now threatening us with the fate that normally faces an unusually successful species in nature: extinction.

Postulating a revolutionary paradigm shift as the only option for survival may feel like a small consolation. Yet, there are quite a few historical precedents of revolutionary change going through entire societies in a matter of just a few decades. Indeed, not onlyhas such change happened before, it seems to follow a temporal pattern.

2.1. Kondratieff waves

A theory of such structural socio-technical change in terms of cycles of development was created by the Russian economist Nikolai Kondratieff in the 1930s. Kondratieff argued that modern economies

fluctuate in cycles of 40–60 years (known as Kondratieff waves), always starting with technological innovations that penetrate economic and social systems, effecting a prolonged economic upturn and a steady increase in productivity (Wilenius and Kurki, 2012). This development is then coupled with new value systems, social practices and organisational cultures. However, at a certain point the new technology networks begin to offer diminishing returns on investment. This results in stagnation of credit demand, with the real interest rate dropping to zero, before the cycle begins again. This pattern is demonstrated by every major economic crisis in the past 200 years, the last financial crisis included. There is therefore an observable structural and temporal pattern that definesour economies, as illustrated in Fig. 2.

<img class="figure large" border="0" alt="Projected population growth in different regions of the world." src="http://origin-ars.els-cdn.com/content/image/1-s2.0-S0040162514003783-gr2.jpg" data-thumbEID="1-s2.0-S0040162514003783-gr2.sml" data-imgEIDs="1-s2.0-S0040162514003783-gr2.jpg" data-fullEID="1-s2.0-S0040162514003783-gr2.jpg">

Fig. 2.

Projected population growth in different regions of the world.

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Modern economies fluctuate in cycles of 40–60 years. Rolling 10-yearyields of the Standard &Poors 500 equity index and Kondratieff's waves. Source: Datastream, Bloomberg. Illustration: Helsinki CapitalPartners, Markku Wilenius

There is no consensus about the timing of the waves: different authors rely on slightly different chronologies. Likewise, the key drivers vary somewhat as well, particularly when it comes to identifying the driver for the sixth wave (Nefiodow, 2006).

One of the most popular explanations to the existence of the K-waveshas been that of looking at the clusters of technological innovation. This causal hypothesis comes originally from Joseph Schumpeter, whose main question was how innovation and technology influence economic growth. In his early work Schumpeter approached this by investigating the long-term economic growth patterns and their relationship to innovation. The Schumpeterian framework becamethus based on the idea that temporal clusters of major innovations create new opportunities that in turn accelerate economic growth (Schumpeter, 1939b). Later, many of the interesting K-wave theories have built on this by trying to explain historical growth patterns by changes in key areas, such as communications, energy, production,or transport technologies.

To complement Schumpeter's original theory, Gerhard Mensch has addedthe idea that the reason major innovations occur during recessions relates to investment behaviour: Mensch argues that during prosperity investors tend to invest in less risky ventures, and in stagnation or recession fewer low-risk investment opportunities are available. Together the Schumpeter–Mensch theory of technological innovation as the key to the waves has inspired the main body of literature related to the Kondratieff waves.

Robert U. Ayres examined critically the Schumpeter–Mensch hypothesesin his massive article, published in two parts in the Technological Forecasting and Social Change (Ayres, 1990a and Ayres, 1990b). Whileremaining supportive of the general idea that the timing of the waves is dependent on technological developments, Ayres neverthelesscame to the conclusion that clustering of innovation can be best explained by the dynamics of technological opportunity:

technological breakthroughs on one hand push back the limits of existing technology, and on the other hand offer possibilities for “convergence” or “fusion” of developments in different fields. Interestingly Ayres suggests – relying on historical evidence – thatan important innovation contributes economically quite little to thenext upswing of the wave, but instead the effect lags on to the subsequent ones.

Ayres continued that discussion in his article in 2006 – published in a larger compilation organised by NATO — Program for Security through Science – where he asserted that K-Wave phenomenon is best understood as a capital-replacement cycle, where capital is connected to dominant energy power networks. In addition, each of these capital-intensive phases is preceded by the period of radical innovation, this timing coinciding with downswing phase of K-wave. In the end, Ayres casted serious doubts on whether K-wave assumptionholds now that globalisation (i.e. capital free of moving from country to country) has taken a very different intensity (Ayres, 2006).

Also Gerhard Mensch, who has developed earlier idea that during prosperity investors tend to invest in less risky ventures whereas in case of downturn the attraction of high-risk ventures arises, hadthe contribution in the above-mentioned NATO-publication, where he essentially considered the possibility of long-waves breaking as theunderlying trends change. He was envisaging the break from a rather stiff macro-economic set-up organised by Kondratieff and fortified by Schumpeter with his notion of technological mega-drivers and thought that in order for Lisbon Agenda 2010 to be met, that would need a new notion of structural instability (Mensch, 2006). Well, history shows that in spite of reaching the goals of Lisbon Agenda, EU-countries fell into a huge debt crisis propelled by rather reckless behaviour of some European banks.

It is quite remarkable in that volume edited by T.C. Devezas that none of the authors – and all the most esteemed Kondratieff experts were represented – even hinted the possibility of having a crash similar to that of the Great Depression only a couple of years downstream. On the contrary, renowned futurist Harold Linstone expected the upswing part of 5th Kondratieff wave to last until 2024– driven by nano- and biotechnology – at which time he expected a

change of the curve to the downswing phase of the sixth wave. As we can now clearly observe, the shift to the next wave has already begun, even since the turmoil of financial crisis in 2008 (Linstone,2006).

Similarly Jim Dator, one of the best futurist ever, did not assume the fourth or fifth wave (he does not take a definite stand as to which wave economies we were riding in 2006) coming to an end with the crash occurring some years later. However, in his article, he does point out the long trend of increasing consumer spending sparked by the inauguration of credit cards for masses, and thinks this development should have already caused the existing wave to crash. But his real point is that K-Waves might be altogether a thing of the past, and that we should actually look for alternativesto guide us on our trembling road towards a hazy future (Dator, 2006). In similar fashion, futurist Jordi Serra also expressed his doubt as to whether K-Wave theory is too rigid and deterministicallyloaded to fit into the world of increasing risks and thus growing instabilities. Now, with the obvious benefit of hindsight we are able to state that it was indeed the mounting risks that eventually materialized as the financial crisis took off by 2008. In Serra's otherwise reflective article there was no clear predictive statementabout a lurking financial meltdown (Serra, 2006).

2.2. The sixth wave

The next K-wave, which will now be truly global for the first time in human history, will eventually be about raising the level of awareness concerning key human predicaments and then searching for and implementing measures that can really make a difference. We envision here things like new smart and decentralised power grids, and new welfare models that stand up to scrutiny. This is a massive learning challenge for societies, which need to wake up and recognise that they are in great trouble unless old attitudes and policies change.

In this emerging sixth wave, the next big race to which the principal thrust of our technological development, economic growth, social cohesion, and even our cultural and spiritual activities willbe devoted, has to do with making our systems more intelligent. A lot of this intelligence must come from understanding how we can useour natural resources more efficiently. As social and individual

awareness concerning the limits of our fragile planet grows, new innovations will be forced to create a technological and social infrastructure that helps us live more meaningful lives.

As always, human intention is what will lead the way. The information revolution has occurred in two ways. First, scientific evidence abounds that the present industrial model of development will not take us to the kind of future we want. Second, we now have novel channels for networking. There are over six billion mobile phones in the world. A whole new digitised space has been created, and the number of active Facebook users has hit the magical one billion mark.

Moreover, there are new technologies, such as nano- and biotechnologies, moving on to the stage. Nanoparticles are used everywhere, from helping to filter fresh water to providing self-cleaning windows. Biomaterials will eliminate the excessive use of non-renewable materials in many fields, such as in the construction,insulation and packaging industries, as new products based on natural woven products will begin to substitute for existing products. In terms of price and industrial scale, new renewable energy technologies are fast approaching market entry.

There are thus two fundamental factors at work here: first, needs arising from the observed limitations of existing ways of producing and consuming, and second, a new awareness concerning the innovativeways by which we can make society smarter and more human through theuse of various technologies. Today we are in a situation in which new breakthroughs are taking us onto a new level in the interaction between humanity and technology. Futurist Ray Kurzweil, who with an astonishing rate of success has forecast the rise of a new high-techparadigm, recently pointed out how the operations of the human mind and brain can be tracked and this knowledge can be “ported” into vastly intelligent human machines (Kurzweil, 2012). Not only are we seeing the birth of new super-intelligence through the application of our know-how of technology, we are also witnessing totally new possibilities for extending the powers of our own minds.

To summarise, thus far we have claimed that the world is increasingly becoming a place where surprises can lurk around any corner. At the same time, we know that certain developments in our societies unfold in patterns. We also know that bio-, nano- and ICT

technologies will play a role in the future, probably converging into something totally new and unexpected. In what follows, we shallexplore four different disruptions; developments that can take a radically different direction from what is now taking place. We callthis de-trending, as the idea is to show how various triggers can push the trend off its current course, resulting in a major shift inour perception about the future.

3. Four shocks to shake the world

At first glance, a reader seeing the shocks we present below that could undo the trend of the Sixth K-wave might well say that these shocks themselves are trends. So how can they be a “shock” or “X-event”? The answer is simply a question of timescale. Every event, X- or otherwise, has a certain unfolding time. Maybe it's very shorton an absolute scale like an asteroid impact or an earthquake. But generally the unfolding time is much longer, as with a pandemic or atechnological innovation. The point is that the unfolding time of the event is still much shorter than that of the process/trend that the X-event changes. So the four “shocks” presented below should be seen in this light. From the viewpoint of the timescale of the K-wave, they are short, in essence “points”. But they are still trendson their own timescale. With this point in mind, let's now turn to the shocks.

3.1. Shock #1: the decline and fall of populations

3.1.1. Current trend

Driven by the fact that the global population increased by nearly 140% during the second half of the twentieth century, seers of the future envision population levels soaring onward and upward for the next 50–100 years along a similar, although not necessarily identical trajectory. Conventional wisdom has it that this population growth will be concentrated in Africa and Asia, as shown in the graphic below from the UN Population Division. Here we see the population (measured in billions) at three points in time. The picture that emerges from this projection is one of population decline in Europe, along with fairly moderate growth in Latin America and North America. The action, though, resides in Asia and especially Africa, where the growth rate exceeds 100% in Africa and over 40% in Asia. The overall picture here is clear: a global

population increase of about 2 billion people, almost all of it concentrated in Africa and Asia (Fig. 3).

<img class="figure large" border="0" alt="Fertility rates in some countries." src="http://origin-ars.els-cdn.com/content/image/1-s2.0-S0040162514003783-gr3.jpg" data-thumbEID="1-s2.0-S0040162514003783-gr3.sml" data-imgEIDs="1-s2.0-S0040162514003783-gr3.jpg" data-fullEID="1-s2.0-S0040162514003783-gr3.jpg">

Fig. 3.

Fertility rates in some countries.

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3.1.2. Implications

The picture just painted above has it that extrapolation of the above population picture suggests a world of 2050 involving a dramatically increased focus on financial services for pensions and healthcare services and facilities for the aged world, accompanied by major shifts in biotechnology and pharmaceuticals in the developed world. Let us look at an X-event whose occurrence would cast serious doubt upon parts of the standard picture.

3.1.3. X-event


To begin this story, consider the chart below showing the fifty-yearpercentage change in the total global population. This chart should be read as follows: Pick a year, say 2000, and read the percentage change from the chart, which in this instance is 140%. This means that in the half century preceding the chosen year, global population increased by 140%, which happens to be the largest half-century change on the entire chart. What's immensely revealing aboutthis figure is that in the year 2050, the global population will have increased by only about 20% from its level in 2000 (a nominal increase of around 1.4 billion), and should actually begin to decline in about 2070 from its level in 2020. So the enormous increase seen in the second half of the twentieth century was not the beginning of a trend, but rather the end of one, an anomaly, andin the second part of this century, the population will actually start falling dramatically ( Fig. 4).

<img class="figure large" border="0" alt="Decline of fertility rate in developing countries." src="http://origin-ars.els-cdn.com/content/image/1-s2.0-S0040162514003783-gr4.jpg" data-thumbEID="1-s2.0-S0040162514003783-gr4.sml" data-imgEIDs="1-s2.0-S0040162514003783-gr4.jpg" data-fullEID="1-s2.0-S0040162514003783-gr4.jpg">

Fig. 4.

Decline of fertility rate in developing countries.

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It is well worth asking the question: Why can we expect to see a worldwide population decline in the second part of this century, at an even faster rate than it rose during the last century? The primary driving force is decreased fertility rates. This phenomenon has already been taking place in most of the developed world for at least the past couple of decades or more, most prominently in the countries of Western Europe. Prime examples include Italy and Germany at a rate of 1.4, the Netherlands, with a rate of 1.8, and arate of 1.9 in the UK, all well below the replacement level of 2.1. The graph below shows the global situation, along with the fact thatthe rapid decline infertility is not something confined to developedcountries — it is now being seen in many Muslim countries around theworld as well, with the fertility decline in Iran, Turkey and Pakistan even exceeding the global rate. Many reasons have been put forward for this fertility decline, ranging from family planning policies in China and India to the widespread availability of contraceptives and even partnership instability. No doubt all these things make their contribution, but by far the most convincing explanation is the dramatic worldwide increase in literacy ( Fig. 5).

<img class="figure large" border="0" alt="Negative correlation between fertility rate and literacy." src="http://origin-ars.els-cdn.com/content/image/1-s2.0-S0040162514003783-gr5.jpg" data-thumbEID="1-s2.0-S0040162514003783-gr5.sml" data-imgEIDs="1-s2.0-S0040162514003783-gr5.jpg" data-fullEID="1-s2.0-S0040162514003783-gr5.jpg">

Fig. 5.

Negative correlation between fertility rate and literacy.


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On the surface, it seems totally uncontroversial to say that literacy is a good thing. Knowing how to read and write is an essential step in moving upwards in an increasingly knowledge-based world. But seeking an educated, literate population has much more profound and unintended consequences than one might initially imagine—consequences that are not always for the better (Goldman, 2011).

It is often argued that another driver of reduced fertility is urbanisation, with the massive shift of population from the countryside to urban megalopolises à la Tokyo, Mexico City, Seoul, Sao Paulo and the like. Equally likely, if not more so, is that increased literacy is a principal driver of not only reduced fertility but also of urbanisation. The line of reasoning is as follows: literacy in agrarian communities widens the horizons of those who are educated, not to mention the fact that it widens the gap between the educated and those who are not. The newly-created lifestyle opportunities opened up by education, in particular through reading, can and does motivate the newly-literate to imaginea future for themselves that is very different from that of their parents and grandparents, one residing outside the scope of farming and a traditional rural life.

To realise this vision, a move to an urban area with its broad spectrum of alternative lives and lifestyles is the obvious next step. This urge for a change in lifestyle is especially true for women, who once they can read and write begin to consider a life that does not involve having half a dozen children (or more!), whileat the same time managing a household in the countryside.

Compelling evidence for the strong negative correlation between fertility rates and literacy is shown in the figure below, which shows these two variables for almost all the countries in the world,together with the correlation line displaying a strongly negative slope. This picture opens up the issue of the implications of the huge decline in global fertility as mass education takes hold in highly populated regions in Africa and Asia (Fig. 6).

<img class="figure large" border="0" alt="Fertility versus Literacy." src="http://origin-ars.els-cdn.com/content/image/1-s2.0-S0040162514003783-gr6.jpg" data-thumbEID="1-s2.0-S0040162514003783-gr6.sml" data-imgEIDs="1-s2.0-S0040162514003783-gr6.jpg" data-fullEID="1-s2.0-S0040162514003783-gr6.jpg">

Fig. 6.

Fertility versus Literacy.

Source: CIA Fact Book.

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3.1.4. Implications

The demographic story that emerges from these pictures is not pretty. Especially grim are the figures for the population of currently large nations that are due to get smaller, a lot smaller, before the end of the current century. Assuming that the fertility rates do not change from their current levels, by the end of this century the economically active segment of the population (those between 15 and 59 years of age) will shrink by 40% in Western Europeand by about two-thirds in Eastern Europe and East Asia. At the sametime, the working-age population in the United States will grow by about 25%. To give some perspective to these figures, the total


population of the low-fertility countries like Germany and Italy will fall by 40–60%. Thus, today's 80-million strong Germany will shrink to a country of fewer than 40 million people by the year 2100. In Japan the situation is even worse. There we can expect halfthe total population to be 65 or older by the middle of this century, not the end.

The ongoing population collapse across virtually the whole of the industrial world as described by these facts and figures will disrupt the entire global economy and threaten political stability everywhere. Already, countries like Russia are in a demographic death spiral, and as ageing and population decline becomes progressively worse, economies and tax revenues will implode across Europe and East Asia. At the same time, we will have the problems ofpensions and healthcare described earlier in the conventional scenario. Only the United States seems in a position to weather thisparticular storm, as the country will still have enough workers to support the elderly.

Even more remarkable than what is happening demographically in the developed countries of Europe and East Asia is the rapid rate at which the Muslim countries are nipping at their demographic heels. In the last 50 years, fertility in the Muslim world has dropped at arate more than double that of the world as a whole. Muslims in the Arab world, Iran, Turkey, Malaysia and South Asia are all experiencing this decline, with Iran's fertility having fallen by almost six children per woman, as seen in the chart shown earlier.

It's also a point worthy of note that for the most part, the Muslim world has no public pension or healthcare programmes. The elderly rely upon their children to take care of them instead. Today, most Muslims have several working-age children to serve this role. By 2050, most aged Muslims will have only one or two children, echoing a situation already pressing upon Europe. Over the next half century, the average age in Europe will increase only from 40 years to about 46; in the Muslim world, the average age today is in the early 20s. But it will increase to 40 or more by 2050, and by 2070 these countries will have a higher fraction of aged dependents than Western Europe. So the relative economic burden will be far heavier in the ageing Muslim countries than almost anywhere else in the world. This fact leads to a very dark aspect of the ageing problem

that may eclipse the serious, but rather modest, stress induced in Western societies as outlined in the conventional wisdom scenario stated at the beginning of this story.

3.2. Shock #2: disappearance of trust in government and institutions


In the article “Turning Points,” historian Niall Ferguson lists six drivers of historical change (Ferguson, 2012). The one that Fergusonclaims is almost always overlooked by political scientists is what he terms, “The tendency of even good political systems to degenerate”. The argument is that as a successful political system ages, it acquires an ever-increasing number of special interests lobbying for a bigger share of the society's resources. This is an example of the process of “complexity overload”. The unrelenting pursuit of these special interests leads to an erosion of civic virtue and the ultimate demise of the once-successful but now erodedpolitical system. Ferguson discusses this process at great lengths in the volume The Great Degeneration, where he argues that the degeneration of the political order helps explain the slowdown in growth and productivity we have witnessed in the West in the past decade.

Another observer of this phenomenon of political degeneration is Richard Edelman, president of the world's largest independent publicrelations firm. He notes that “from the sovereign debt crisis in Europe, to the government's response to the earthquake in Japan, from the high-speed rail crash in China, to the debt ceiling fight in Washington, people around the world are losing faith in their governments” (Edelman, 2013). The chart below taken from the 2012 report by Edelman's firm on trust in governments and institutions makes this point graphically clear. A question that immediately arises from the growing public mistrust of governments in particularand institutions, in general, is how will angry citizens translate their anger into action?

3.2.2. Implications

One answer to this question was offered by the late economist AlbertO. Hirschman. While at Harvard in 1970, Hirschman wrote about how people respond to the erosion of institutions ranging from firms to states (Hirschman, 1970). His analysis showed that people choose one

of the two options: exit or complain. In other words, either abandonthe institution or try to change it. Put another way, quit your job or speak to your boss.

In his seminal paper, Hirschman argued that in earlier times in the USA, people voted with their feet and exited, since there was alwaysmore room to leave the existing disorder behind. The exit option is no longer available, especially if you believe you already live in the best country on earth (Fig. 7).

<img class="figure large" border="0" alt="Changing Levels of Trust Globally and in Various Countries, 2011–2012." src="http://origin-ars.els-cdn.com/content/image/1-s2.0-S0040162514003783-gr7.jpg" data-thumbEID="1-s2.0-S0040162514003783-gr7.sml" data-imgEIDs="1-s2.0-S0040162514003783-gr7.jpg" data-fullEID="1-s2.0-S0040162514003783-gr7.jpg">

Fig. 7.

Changing Levels of Trust Globally and in Various Countries, 2011–2012.

Source Edelman, R. 2012 Edelman Trust Barometer, http://trust.edelman.com/.

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If you believe in the complaint option the alternative is not to reform government, but to get rid of it. On both sides of the Atlantic, this has taken the form of the creation of competing, private-sector alternatives to services previously the prerogative of the state. Witness the emergence of private schools and private health provision as a reaction to disenchantment with the socialist state, especially in Western Europe.

An even more ominous picture of the growing mistrust of government is given by a survey carried out by the Pew Research Center in the United States, which aims to document public attitudes towards the US government from 1958 to the present (Pew Research Center, 2013). The survey accounts for people who say they trust the government in Washington, DC, either “just about always” or “most of the time.” The picture that surveys leads to is shown below.

The survey says that historically, public mistrust in government wasassociated with specific events: the Watergate investigation in the 1970s and the House Bank scandal in the early 1990s being good illustrations of these phenomena. But today's disenchantment with government is difficult to trace to any specific event. Rather, whatseems to be happening is a steady and growing belief that politicians simply cannot be trusted.

If this is really a political death by a thousand cuts with no specific events to blame, then one must conclude that there is no clear-cut cure for the malady that ails the government. It may well be that we are simply in an age when trust in institutions will never again approach the levels it attained in the past (Fig. 8).

<img class="figure large" border="0" alt="Trust in US Presidents, 1960–2010." src="http://origin-ars.els-cdn.com/content/image/1-s2.0-S0040162514003783-gr8.jpg" data-thumbEID="1-s2.0-S0040162514003783-gr8.sml" data-imgEIDs="1-s2.0-S0040162514003783-gr8.jpg" data-fullEID="1-s2.0-S0040162514003783-gr8.jpg">

Fig. 8.

Trust in US Presidents, 1960–2010.

Source: PEW Research Center at http://www.pewresearch.org/key-data-points/views-of-government-key-data-points/.

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But this conventional wisdom of creeping dissatisfaction with the body politic regarding trust in government and institutions is a rather benign implication. Let us look at others which may well turnout to be much worse.

3.2.3. X-event

The general collapse of trust in government as noted above is even worse when it comes to other institutions. For example, David Edelman's 2013 survey shows that 50% of the respondents trusted business firms to generally do what is right, only 18% trusted business leaders to tell the truth — a gap of 32% between the institution itself and those leading the institution. As Edelman


expressed it, leaders' truthfulness was “pretty pathetic”. So what does this “truth gap” between institutions and their leaders imply?

3.2.4. Implications

It should come as no surprise to see that people are now placing their trust in non-government, non-business institutions. Now trust moves to experts, such as academics or peers, like a friend on Facebook. So the leadership crisis at the institutional level gives rise to people developing a very different view to that in the past about who they take seriously and turn to for facts rather than platitudes.

To illustrate this shift, Edelman's survey showed that among the “informed public” of university-educated, higher income people, 69% saw an academic or an acknowledged expert as being a credible sourceof information. Similarly, 61% viewed “someone like themselves as a reliable source”. By way of contrast, only 43% of those in the informed public regarded a corporate CEO as credible (Edelman, 2013).

More ominously, this shift in confidence from traditional leaders ingovernment and industry has also given rise to a worldwide belief ofgrowing corruption on the part of business and government leaders. The chart below shows a global map of corruption from the organisation Transparency International, followed by a similar chartfocusing on just the G20 countries (the “developed world”) (Fig. 9 and Fig. 10).

<img class="figure large" border="0" alt="Corruptions Perception Index in G20 Countries, 2012." src="http://origin-ars.els-cdn.com/content/image/1-s2.0-S0040162514003783-gr9.jpg" data-thumbEID="1-s2.0-S0040162514003783-gr9.sml" data-imgEIDs="1-s2.0-S0040162514003783-gr9.jpg" data-fullEID="1-s2.0-S0040162514003783-gr9.jpg">

Fig. 9.

Corruptions Perception Index in G20 Countries, 2012.

Source http://cpi.transparency.org/cpi2012/.

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<img class="figure large" border="0" alt="The long-term trend of relative price of commodities." src="http://origin-ars.els-cdn.com/content/image/1-s2.0-S0040162514003783-gr10.jpg" data-thumbEID="1-s2.0-S0040162514003783-gr10.sml" data-imgEIDs="1-s2.0-S0040162514003783-gr10.jpg" data-fullEID="1-s2.0-S0040162514003783-gr10.jpg">

Fig. 10.

The long-term trend of relative price of commodities.

Source http://cpi.transparency.org/cpi2012/.

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The picture that emerges from these stories and graphics suggests anever-increasing slide into the kind of stress (“complexity gaps”) between citizens and their leaders in government and industry that often portends major social disruptions (think of the so-called ArabSpring uprisings or social unrest in India, Russia and China as examples). This consequence of a growing lack of trust in society would make the conventional picture of slowdowns in growth and productivity look positively attractive by way of comparison.

3.3. Shock #3: falling price of commodities


It looks as if the communication revolution, which marked development during the decades of the fifth Kondratieff wave from the 1970s onwards, is transforming into a material and resource revolution. Moore's law, according to which the number of transistors on integrated circuits doubles approximately every 18 months, means in practice that computers double their productivity over a fixed, and rather short, period of time. Now thesame may take place in the way we use other critical resources, likeenergy, materials, food and water.


All our earthly resources have been massively consumed in recent decades. Between 1980 and 2008, global resource extraction and use increased by 78%, from 38 billion tonnes to more than 68 billion tonnes. The number could rise to 100 billion tonnes in just 20 years. Simultaneously, there is an estimate that the bio-capacity of the earth (including both extraction and absorptive capacity for waste and emission) has already been exceeded by 50% (EIO, 2012).

3.3.2. Implications

Ever since the latest phase of globalisation that took effect by theturn of the millennium, when China and India fully entered the global markets, there has been a very strong increase in demand (Fig. 11).

<img class="figure large" border="0" alt="The increase of global shippingcapacity between 1980–2010." src="http://origin-ars.els-cdn.com/content/image/1-s2.0-S0040162514003783-gr11.jpg" data-thumbEID="1-s2.0-S0040162514003783-gr11.sml" data-imgEIDs="1-s2.0-S0040162514003783-gr11.jpg" data-fullEID="1-s2.0-S0040162514003783-gr11.jpg">

Fig. 11.


The increase of global shipping capacity between 1980–2010.

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It is remarkable that during the course of the 20th century, the price of commodities dropped by almost 50% (McKinsey Global Institute, 2011). This happened at the same time that world economicoutput went through the roof, increasing 20-fold. The reason why resource prices fell was quite obvious: new supplies were discoveredin abundance and new techniques developed that increased productivity. Moreover, prices did not always reflect the full cost of materials. The last ten years have been dramatically different: prices have been trending upwards. This is primarily because the huge Chinese demand has pushed prices higher. When the financial crisis hit the global economy in 2008, the price surge of raw materials stopped temporarily, only to continue after the most difficult phase of the crisis ended.

3.3.3. X-event

As always, the pressure of surging prices will trigger the industry to search for substitutes. Indeed, a lot of new investment has been shifted into the domain of renewable energy technologies, as well asinto new material to replace the non-renewable raw-materials. This might create momentum for the next major turn, where the prices of the new technologies will start to fall rapidly. This could happen if large investments in bio-based materials and renewable energies make a breakthrough in the markets, meaning that their price starts to decrease as a result of mature technologies and economies of scale.

3.3.4. Implications

New substitutes in terms of materials, technologies and services would spread rapidly throughout the world. This spur of new innovations will have a huge impact on markets. Eco-innovations havealready grown more than any other industry in recent years (EIO, 2012). These innovations hold great promise, particularly for Europe. The European Union has already adopted a sustainability

strategy to increase resource productivity through improved efficiency in material and energy production, along with the development of new goods and services.

According to the Renewables 2012 global status report, modern renewable energy (hydropower, geothermal power, biofuels, solar and wind energy) can substitute for fossil fuels in four distinct markets: power generation, heating and cooling, transport fuels and rural/off-grid energy services. Moreover, it has been estimated thatsome 39 countries have the potential to meet 100% of their electricity needs through domestic geothermal resources ( Holm et al., 2010).

And what about new, bio-based materials? “Bio-economy” refers to three different aspects of bio-based raw-materials: a) bio-based products, b) the use of biological processes in production, and c) cycles of material and energy as a part of the biosphere (Kuisma, 2011). Bio-economy products are based on biomaterials that are by definition biodegradable, so they are fundamentally renewable both in the beginning and as end products. The properties of these products may be manipulated using various biotechnologies.

The development of biochemistry has brought biological processes into industrial production. The novelty in bio-economy is that it takes all the possible impacts on ecosystems and natural cycles intoaccount. We can then talk about industrial ecology in terms of production plants and their dynamic interaction with natural systems. In bio-economy, all material and energy flows are either inuse or are returned to the natural cycle. It is, in effect, a mergerof industrial and natural economies.

3.4. Shock #4: localising the global


It is rather common to think that globalisation is a powerful megatrend that appears to be leading to a world in which the nation-state becomes an obsolete unit. This argument can be supported with a number of facts. For instance, let us look at the development in world trade in terms of global shipping capacity (Fig. 12).

<img class="figure large" border="0" alt="The development of global shipping capacity.Source: UNCTAD." src="http://origin-ars.els-cdn.com/content/image/1-s2.0-S0040162514003783-gr12.jpg" data-thumbEID="1-s2.0-S0040162514003783-gr12.sml" data-imgEIDs="1-s2.0-S0040162514003783-gr12.jpg" data-fullEID="1-s2.0-S0040162514003783-gr12.jpg">

Fig. 12.

The development of global shipping capacity.

Source: UNCTAD.

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In a similar fashion, the volume of world merchandise exports has risen rapidly since the turn of the millennium, only to drop sharplyand finally stop altogether when the financial crisis hit home. The idea of the “flat earth” has penetrated into our minds ever since digital platforms began to dominate the communication space. By almost any measure you consider, globalisation has been our economicframework for the past several decades.


At the same time, technology is advancing in leaps and bounds: new, efficient energy technologies will gain ground and gradually supersede the current fossil fuel-based energy economy. New developments in biotechnology will enable us to replace synthetic products with organic materials. Nanotechnology already allows us tomodify the properties of products so as to make them more durable. This is leading to the development of such innovations as new methods for diagnosis in health care. Today, it might take less thana month for a company to achieve 50 million customers around the world, as seen in the gaming industry. Previously, it took decades.

Meanwhile, we know that the world has become increasingly complex, and the struggle for political and economic power has continually escalated. The enormous progress in ICT has in no way neutralised the driving force of the preceding wave of development, which saw the rise of the petrochemical and automotive industries. The world economy is still dominated by the alliance between oil and money.

Up until now, globalisation has shown tendencies that might make us believe that the world is becoming one big market place. In many ways we have numbers to support this case. But the rising scarcity of food and increasing prices for precious raw-materials might change this picture completely. We may well retreat from globalisation back to localisation (Katz and Bradley, 2013 and Linstone, 2011).

3.4.2. X-event

In the next five years (or less) we may experience a global food crisis. That would result in a severe political crisis globally and generate many international conflicts. The deep underlying reason for the crisis is relentless population growth (even though the rateof growth is actually declining). Together with the formation of a large new middle class in the developing world, it will force us to find ways to increase food production. The measures used in the past“green revolution” will not help, as heavy use of fertilisers can nolonger add to agricultural productivity. In addition, the changing climate creates droughts and other instabilities in weather patterns.

3.4.3. Implications

The result of the global food crisis is clear: governments turn to more protectionist policies, and all major international agreements become more “stuck” than they already are today. Governments then again become very focused on self-sufficiency, whether for food, oilor talent.

There will then be a new era of localisation, powered by the fear oflosing the battle for resources. In many areas, but particularly in food production, countries will begin to look for ways to achieve self-sufficiency at any price. This will in turn create a general atmosphere in which immigration, investments and other kinds of flows will be weakened. In the end, localisation will overtake globalisation.

In summary, there are three major factors at play behind the upcoming 2019 global food crisis: first, a population growth in which the current world population of well over 7 billion inhabitants is still rapidly increasing. Secondly, a steady trend inthe increase of food prices. Finally, changing weather patterns as aresult of human-induced climate change will create a less benign world for agriculture, in general. All this will add greatly to global political instability, tearing down many past victories of international diplomacy.

4. Conclusions

Our goal in this article is not so much to critique mainline arguments about the way the sixth Kondratieff wave will unfold and why, but to point out that surprises always occur and that such surprises may well get in the way of the picture for this wave as painted by conventional wisdom. We have presented four such surprises and explored their implications should they take place. There is no implication here that any of these surprises will necessarily occur; in fact, the likelihood of the occurrence of any one of them is small, since otherwise they would not be surprises. Instead, the point is to show that unexpected events can and do intrude on the “most likely” scenario presented in the standard viewof the sixth K-wave.

In summary, then, our message to government decision-makers, strategic planners in industry and even individuals concerned with their future is to follow the three As: Maintain the capability to

assimilate shocks and surprises so as not to be destroyed by them, keep an open mind and be agile enough to recognise the new opportunities presented by a surprise, and finally, maintain the capability to adapt to those changed circumstances if you feel your resources can be better deployed by doing something different than what you've done before. This is the only general way for prosperingin the face of an uncertain future.

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