2012 predictions (4)

Jennifer Mc Lean, What Will Happen In 2012? (video)

Various authors for beyondbrics: a series – 12 for 2012 – that beyondbrics is running on key emerging markets topics for the coming year, The Financial Times, starting Dec 27, 2011:

Louise Arbour, Next Year’s Wars: Ten conflicts to watch in 2012, Foreign Policy, Dec 27, 2011

Ross Dawson, Twelve tech trends to shape our future, Technology Spectator, 21 Dec 2011

Roert Reich, My Political Prediction for 2012: It’s Obama-Clinton, The Huffington Post, 12/28/11.

Things That Make You Go Hmmm – 28th December.

Gordon G. Chang, The Coming Collapse of China: 2012 Edition, Foreign Policy, Dec 29, 2011.

IFTF, A Multiverse of Exploration: The Future of Science 2021, Dec 5, 2011.

Bryan Lufkin, InnovationNewsDaily Contributor, Institute for the Future Unveils Its Future Predictions, IFTF, 29 December 2011.

Yadullah Hussain, Too many wild cards cloud 2012 oil price outlook, Financial Post, Dec 30, 2011.

The Red (team) Analysis Weekly No28, 29th December 2011

No28, 29th December 2011

The tension with Iran did not abate, while signs of spreading economic recession multiply. However, this end of year saw a boost in optimism in those focusing on high-tech and future technologies, however without questioning in which way resource depletion, economic and financial turmoil and related domestic impact as well as international rising tension – furthermore all interlinked – could affect technological development. Would we tend to be prey to technological determinism?

From Iran to global economic recession through technological determinism

2012 predictions (3)

2012 predictions (3)

Morgan Stanley, Global 2012 Outlook, Global economic Forum, December 15, 2011.

EconMatters, Debt Crisis 2012: Forget Europe, Check Out Japan, Zerohedge, 12/27/2011.

Council on Foreign Relations, The World Next Year: 2012 – A preview of world events in the coming year, (podcast), CFR multimedia, December 22, 2011.

Council on Foreign Relations, Preventive Priorities Survey: 2012, CFR.com, December 8, 2011.

Council on Foreign Relations, Five Economic Trends to Watch in 2012, CFR.com, December 28, 2011.

Sundeep Waslekar (), 12 Trends To Watch For 2012 – OpEd, Eurasia Review, December 27, 2011.

Lance Ulanoff, 5 Tech Trends to Watch in 2012, Mashable Social Media, December 28, 2011.

Zachary Karabell, 2012 Economic Outlook: Why Things Are Better Than We Think, the Daily Beast, Dec 27, 2011.

James Petras, A Doomsday View of 2012, The James Petras website, December 24,  2011.


2012 predictions (2)

2012 predictions (2)

ZeroHedge, Globalization, The Decade Ahead, And Asymmetric Returns, 12/26/2011

ZeroHedge, Jim Rogers 2012 Outlook: Pessimism With Scattered Crises, 12/26/2011

Derek Abma on 2012 predictions by Douglas Porter, deputy chief economist with BMO Capital Markets, “Canada to avoid recession next year despite Europe,” The Vancouver Sun, Financial Post, December 26, 2011

Ryan Mauro, Top 12 Threats to Watch in 2012, Family Security Matters, December 27, 2011

Tony Karon, “If 2011 Was a Turbulent Year for Obama’s Foreign Policy, 2012 Looks Set to Be Worse,” (Survey of the top ten global crisis issues facing the U.S. in the new year), Time.com Global Spin, December 27, 2011.

Moneycontrol bureau, “Keep your coats on! It’s going to be a stormy 2012,” (summary of financial and eco predictions by various financial firms/sources),  Moneycontrol.com, Dec 27, 2011.

Kurzweil AI, News, Cyber threats 2012: search poisoning, mobile Web attacks, selling social-media data, (through Futurist Foresight), October 12, 2011.

NASA, 2012: Beginning of the End or Why the World Won’t End?, 22 December, 2011.

Fiona Graham, Fantastic futures? Technology and business in 2012, BBC News Business, 27 December 2011.

2012 predictions for conventional and unconventional national security

2012 predictions for conventional and unconventional national security

Every year, a host of actors, from newspapers to magazines, from think tanks to futurists and other experts, publish predictions at the dawn of every New Year.

The aim here is to create a repository of all the predictions done for 2012 that are directly or indirectly related to national security, as primary material for all those who would like later on to sort them, analyse them and finally test them.

The section will be populated as forecasts and webpages are published and identified. You are most welcome to post a link to 2012 predictions you found or did in the comments. Please mention the origin, date, title and hyperlink.

And to start with:

The Economist, The World in 2012, with a twitter feed: @EconWorldin

The Economist, A year of living pigheadedly: America will be a tad cheerier than Europe in 2012—but it should be so much better still, Dec 17th 2011 | from the print edition

Michael Schrage, Innovative Ideas to Watch in 2012, Harvard Business Review blog, December 21, 2011

Michell Zappa, Envisioning emerging technology for 2012 and beyond, 2011?


The Red (team) Analysis Weekly No27, 22d December 2011

No27, 22d December 2011

Weak signals of polarisation are emerging regarding the interactions between the new opposition nexus and political authorities, and prospects for further and more widespread instability rise, notably in India – no need to mention Europe anymore. In the meantime, international tension does not abate with Iran, and now a transition going on in North Korea. Meanwhile cybersecurity was very much spotted as being increasingly a concern, but nothing new here.

Nevertheless, a Merry Christmas or Season’s Greetings to all!

Creating Evertime

As underlined in Everstate’s characteristics, time in strategic foresight and warning is a crucial problem that still needs much effort and research before we obtain proper and actionable timelines – and this without even considering timeliness.

For the Chronicles of Everstate, I have been struggling with the best way to present time in our very imperfect knowledge and understanding context.

One of the solutions was to locate the Chronicles in a very distant time, which is what I suggested in Everstate’s characteristics. However, considering the unconscious or conscious mental associations that will be made by readers for years so far away as 5230, this was unsatisfactory. To use a less precise timeline such as the Near Future and the Far Future was also disappointing as we would then lose a temporal outline – however imperfect – that is crucial in terms of policies and responses.

The solution* that seems to be the best is to remain true to our methodology. As we created an imaginary modern nation-state, let us create the corresponding imaginary time, Evertime: a time that mirrors our own as if in a parallel dimension. We shall thus starts the Chronicles of Everstate in 2011 EVT (EVT being the acronym for Evertime).

Using years mirroring ours will also help us identifying, in the future, and thus with hindsight, what needs to be improved and why in terms of methodology and research, and thus will contribute to improve our analysis.


*This solution was found during a brainstorming with a graphic designer, artist, author and game designer, Jean-Dominique Lavoix-Carli, to whom I am truly indebted for helping this idea to emerge. This underlines, once more, the value of brainstorming involving people coming from very different and diverse backgrounds.


Everstate’s characteristics

(Modified on December 19, 2010, 17:40 EST)

The initial variables chosen to start building our scenario are the five most important variables according to Eigenvector centrality, as explained in Revisiting influence analysis.

We shall now choose values for each criterion.

Consistency is then checked, but only for the variables that are linked (see the consistency matrix).

As we aim at finding a plausible and average, mild set of initial criteria, we shall start from the following set, which is also intuitively representative of the situation, real or perceived, in which many real world countries have found themselves for a couple of years.

We then verify that the chosen scenarios are consistent with the consistency matrix.

Even if the aim is to obtain timelines that are as precise as possible, as explained in Creating the model, considering the need for further funding – and, ideally, institutional backing – to be able to do so, achievement of this objective is still remote. Thus, to underline this fact, I have chosen to set the scenarios in a time mirroring our own, Evertime – the initial post read “in a very distant future (starting c.5230)” and has been modified by the post “Creating Evertime” – where years are creating a temporal outline. This choice emphasises dynamics to the detriment of specific dates. However unsatisfactory when we want to depict our very real near future and be easily actionable, this approach allows isolating the time component and each reader or user will be free to adapt the temporal outline according to its convictions or methodology, waiting for something more scientific to exist.

We now have all the necessary material, as well as all the methodological background explanations to begin telling the story of Everstate, starting with setting the stage.

Variables, values and consistency in dynamic networks

In this post we shall explain and discuss the methodological background that allows us to set the criteria for Everstate – or for any country or issue chosen for foresight analysis – as exemplified in the post “Everstate’s characteristics.”

Variables, Values and initial criteria

Values must now be attributed to each selected initial criterion, as would be done with Morphological Analysis. However, here, those values will be those corresponding to the present and not to the future (as in Morphological Analysis).

If the foresight were done about a specific known country, then it would be (relatively) easy to attribute real values for the selected criteria. In our case, those values will help us creating Everstate, putting flesh on our ideal-type and starting making it look real. A similar approach could be used for any issue. It is not limited to the future of the nation-state.

Even if we are working with an ideal-type, we nevertheless must remain in the realm of the plausible and thus values must not be far-fetched. However, we must also make sure that we are not prey to our various biases when choosing values.

High, medium and low values can be selected to cover a broad spectrum. Our variables are most of the time continuous variables, i.e. they can take an infinite number of values. However, borrowing from Bayesian Networks, we discretise variables, i.e. we transform continuous variables into discrete ones by using ranges, or intervals (e.g. rather than use for oil prices o to +∞, we use intervals such as x≤30, 30<x<70, etc.) (Fenton and Neil, 2007). The use of notions such as high, medium, low, for example, corresponds to the discretisation of variables that are not typically quantitative.

Consistency and dynamic networks

Now, and again as with Morphological Analysis, consistency must be checked, i.e. we verify that a variable can take value x while another can take value y. For example, in our case, one could not have at the same time a very high level of domestic escalation (Everstate is on the brink of civil war) and a geopolitical position of strong power rising (at least in terms of country; if we talk about factions or political movements, then the conclusion would not be the same).

Compared with Morphological Analysis that systematically checks all pairs (or rather half of all pairs), because its variables are not linked, our task is greatly simplified. We only have to check all pairs of values for variables that are linked. This considerably reduces the task, at least for the variables chosen as initial criteria.

Typically, inconsistent scenarios are discarded and consistent sets chosen. Then narratives are developed for those specific scenarios, attributing one fixed value to each variable.

This approach cannot be used here, except when setting initial criteria, as we have introduced a dynamic element. Indeed, because we deal with living systems that are by nature always evolving, the value for one variable will most probably change with time, considering the interactions of all the other variables’ values. Furthermore, new unexpected values may appear. Ideally, if values have been properly entered this novel occurrence should not be possible, but, remember, we deal here most of the time with qualitative variables and it will be extremely difficult to cover the whole range of potential values, considering often limited imagination as well as biases.

Part of the interest of the method developed here is to ber able to follow the very evolution of the variables’ values, which will help us determine impact and, ideally, timelines, evaluate alternative policy options and thus will lead to a fully actionable foresight.

We should nevertheless pay attention to the imperative of cross-consistency. We encounter here a formidable obstacle. As seen in “Revisiting influence analysis,” other methodologies reduce the number of variables. Thus, they only look at specific values and their cross-consistency for a very limited number of variables. On the contrary, we keep all variables. Thus, logically, we should systematically enter values for each and every variable and then check the consistency across values for each variable, and if a value appears over time, recheck the consistency.

The task is enormous and cannot be done systematically – except with very large resources. The imperfect solution chosen here, but that should be “good enough,” (Fein, 1994) will be to attribute values and pay attention to consistency while constructing the narrative using ego networks, as we shall see in a next post. Consistency will thus not be ignored but checked progressively. This heightens the role and responsibility of the analysts who will develop the scenarios, as they will need to have the related training and inner qualities.

Fixing values for the initial criteria

As we start here with present criteria and not future ones, we are not confronted, at this stage, with the difficult task of selecting sets of values and determining how many scenarios should be prepared. This will come later on as we shall see in the course of the scenario telling.

As Everstate is an ideal-type that aims at being as representative as possible of existing countries, a plausible medium range set of values will be selected.

Readers interested in other specific conditions will be able to run the whole process again, changing values where necessary.

This selected set of values will allow constructing the first narrative that will set the stage for the scenarios on the future.


Fein, Helen, ‘Tools and Alarms: Uses of Models for Explanation and Anticipation”, Journal of Ethno-Development, Vol. 4, No. 1, 1994.

Fenton, Norman and Neil, Martin, Managing Risk in the Modern World Applications of Bayesian Networks, A Knowledge Transfer Report from the London Mathematical Society and the Knowledge Transfer Network for Industrial Mathematics, (London: London Mathematical Society, Nov 2007).

The Red (team) Analysis Weekly No26, 15th December 2011

No26, 15th December 2011

Rising tension with Iran, Syria, disaster in Durban and more largely on the ecosystem front, China’s multi-dependency and the continuing financial Armageddon. Meanwhile, the paradigm slowly changes: in the U.S. higher taxes for the richest are discussed and …applied (not really on the agenda in ultra-liberal Europe?), while the structure of understanding/knowledge production is being reworked. Interesting times, not for the faint-hearted!