Populism ‘Fake News’, ‘Alternative Facts’ and Democracy

In early 2016 we predicted that the Leave voters would win the UK’s EU Referendum (BREXIT). Incidentally, we also predicted that Donald Trump would win. How did we know? Because we could see that social media realised the democracy of the ‘mob’ that the Greeks feared – where the ill-informed majority could be easily influenced.

As Jose Ortega y Gasset said in his visionary 1930s book ‘The Revolt of the Masses’:

The characteristic of the hour is that the commonplace mind, despite (maybe) knowing itself to be commonplace, has the assurance to proclaim the rights of the commonplace and to impose them wherever it will” …

What does this mean? As Thomas Jefferson said “The greatest threat to democracy is an uneducated citizenry“. Donald Trump, in his victory speech in February 2016, preened and affectionately recounted the numbers that added up to his huge victory:

We won the evangelicals. We won with young. We won with old. We won with highly educated. We won with poorly educated. I love the poorly educated.”, he said.

For Trump, the Fake News and Alternative Facts spread by social media were his key cards. Of course he loves the poorly educated, they don’t trust experts or academics or professionals in authority because some of those people have been found cheating or misleading the public at some time. Instead, they trust their online friends more.

The conclusion in the mind of the populus seems to be, via confirmation bias, that therefore all these people are liars. Social media accelerates this bias in ways that society in general does not understand (there are a few that warn about the risks but they are treated as Cassandras, or as ‘cyberoutlaws who dare to be different‘).

This is the new democracy at work – through social-media – where one ill-informed person’s vote is as good as any other and millions can say ‘”If this many of us think X, then X must be right – ours is an Alternative Fact! Anyone who disagrees with us can’t be trusted … they are telling us Fake News.”.

Some people might say that, in the UK in 2016, “The commonplace mind did not, and probably still does not, understand how the EU works, yet affirmed its misunderstanding of things in the BREXIT vote, and has imposed it on all.”

In the longer-term, the trend seems to be towards assuming that the mass view must be correct. Why? Because it’s a majority view and ‘That’s democracy, right?’. This may undermine humanity’s ability to take decisive, often unpopular decisions, in the face of existential challenges. Correction … it will undermine our ability.


Posted in Change, Influence, Learning, Possibilities, Prediction, Probability, Reflection, Relationships, Social Media, Unintended consequences | Leave a comment

Why are ‘unintended consequences’ almost inevitable?

We so often hear politicians, managers and those in positions of authority wailing about the ‘unintended consequences’ of their actions – or worse, excusing damaging outcomes with a shrug of the shoulders and saying “But they were unintended consequences …” as if that lets them ‘off the hook’ of their responsibilities.

But were these consequences in the real world really unintended? Maybe they were actually inevitable, even ‘normal’ given the actions taken. Could it be that if appropriate approaches and mindsets had been employed then the damaging consequences could have been avoided?

To which the answer is and emphatic “Yes!”.

If one is bringing about change in the real world, in the complex and largely unpredictable inter-connected world in which we live then it is no good merely following the ‘best practice’ taught on business administration courses. The real world cannot be treated as if it is a supermarket chain.

Instead, complexity thinking offers a clear set of principles that should be followed when intervening in wider policy, commercial, social, community, medical and environmental matters.

Avoiding those unintended consequences

I am sure you are now thinking “OK, if we can’t predict how can we see what the consequences will be?”. Good point! The answer is that, yes, we can’t predict specific instances ( x will happen in this place at 1256 on the 27th March to Fred Bloggs and Xioa Lui), but we can anticipate the future if we are forward-looking.

Indeed, complexity thinking can identify that certain classes of outcome are likely, even inevitable, if we go about a particular task in a certain way – or if we organise ourselves inappropriately.

[The rest of this post will give examples]

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Applying Complexity Thinking to the Real World


The eleven ‘Principles of Practice’ below have been derived from the experiences of practitioners (people who are responsible for bringing about real-world change) which are discussed in a companion book “Complexity Demystified – a Guide for Practitioners” (downloadable as a PDF from here).

An example of how these principles can be used is shown by the ‘Liveable Cities‘ project which, in 2017, published a series of short booklets illustrating complexity thinking at work.

The principles below indicate that, in practice, integrative and iterative approaches are essential to bring about desired changes – and so doing minimises ‘unintended consequences‘:

• Principle 1: Dynamic, ongoing change can be influenced purposefully. This is because: a) the underlying ‘drivers of complexity’ have been identified, and b) practical techniques are available to purposefully engage with and shape the underlying drivers.

• Principle 2: Context understanding and perceptions are diverse – there is no ‘single view of the truth’. The experienced complexities of stakeholders are necessarily different, as are their knowledge and information needs.

• Principle 3: Change is ongoing, dynamic and multi-level – there may be no end. This means that trends, flows, gradients, potentials and other ‘energy metrics’ are appropriate dynamic indicators of the progress of practice.

• Principle 4: There are many qualities of power and influence to accommodate. These affect people’s ability to adapt and may arise from individuals, their beliefs and vulnerabilities, or from community values, from gender issues, institutional structures and the political economy, and from the changing environment and so on.

• Principle 5: It is necessary to appreciate who is / what are best placed to bring about change. Given the inevitable natural complexity of practice, those tasked with achieving change may not be the ones best placed in a situation to be drivers of change. Given the time horizons, practitioners should work adaptively through those who are best placed.

• Principle 6: Interventions must have the necessary requisite variety, i.e. have appropriate complexity-worthiness given the desired changes. This insight arises from Ashby’s ‘Law of Requisite Variety’ (1957) which states, in essence, that to influence something your practical behaviours must be equivalent to, and preferably exceed, the repertoire of behaviours of that which you are trying to influence – i.e. to deal with innovation by innovating.

• Principle 7: Practice is not just about adapting, but is also about being able to adapt the adapting and learn. This is because people are in continual co-evolution with the environment and, as there will never be a ‘steady-state’ balance or equilibrium, anticipatory innovation will always be required. One cannot adapt once and then stop.

• Principle 8: Different decision-making and problem-solving styles are required for different situations. Because practice involves inevitable novelty and change over time, there can never be a ‘one-size-fits-all’ solution, nor can ‘optimized’ processes be used as ‘best practice’ in all situations. Indeed, many modelling tools are just not fit for purpose in the face of real-world complexity.

• Principle 9: When reasoning about change, past evidence does not guarantee future prediction. This means that, though we may have evidence of a past train of events, there is no guarantee that we can extrapolate a reliable prediction from this into the future. As there are limits to what we can know and observe, there will always be uncertainties and unknowns, and that we must accept this as a given. A key skill for practice and risk management is envisioning, and being prepared to act on possible, not probable, futures.

• Principle 10: When innovating, transition to new forms may be the only valid option. Because of the inevitable novelty already mentioned, the transformation from non-adaptive capabilities to being appropriately complexity-worthy will require purposeful, ongoing, innovation and adaptation. Gradual, superficial, incremental transition is just not an option in some unsettling circumstances.

• Principle 11: Change will be impeded unless appropriate degrees of freedom and ‘wiggle room’ are available. Being open to change means appreciating where the ‘spaces of possibilities’ are, and how to maximize and exploit them. A misplaced drive for control, repeatability and certainty may clamp down on the very space that is needed for adaptive behaviour to flourish.

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Posted in Adaptation, Agility, Appropriateness, Change, Complexity Demystified, Complexity-worthiness, Contextual complexity, Experienced complexity, Influence, Liveable cities, Natural complexity, Opportunities, Possibilities, Practice, Prediction, Purposeful, Reflection, Transformation, Transition, Unintended consequences | Leave a comment

ISIS Ascendant – Because the West gave up its Winning Strategy in 2001?

A Winning Strategy Lost?

The UK’s ‘Bin Laden Dossier‘ of 2001 reports that Bin Laden’s motivation was to wage jihad against countries (such as the USA and UK) engaging in ‘un-Islamic behaviour’.

In his speeches, Bin Laden cited examples of this, such as: the westernised mode of dress of young people; their liking of pop music and consumer goods; and their lack of respect for their elders and leaders for example.
In other words, the West was (unwittingly) already winning a ‘hearts and minds’ campaign though the spread of consumer capitalism and western goods, media, film, entertainments and comfortable lifestyle.

After 9/11, it could be reasoned that the West’s best course of action was to continue, and intensify, these so-called ‘soft power’ activities – not to attack anyone with hard power.

But this is not what happened and the War on Terror (always unwinable by definition) went ahead. The situation in 2015 continues to ramp up conflict, into what now seems inevitable – World War Three (WWIII).

World War Three (WWIII) – The War of Ideologies

Conflict in the Middle East is not new. It goes back at least as far as Egyptian times (Ostler 2006).  And then, with Islam, it had the Shia / Sunni schism at its root. From the time of The Crusaders onwards, so-called Western forces and governments have had little success in changing outcomes (Stewart 2006,  Tanner 2002, Wallach 2005).

Recent experiences in the region (Iraq, Afghanistan – even for the Russians) are not encouraging for the coalition that the UK and US governments are hoping to put together in 2016.

Also, analysis of the capabilities of Western coalitions (Lwin 1997, Mackay and Tatham 2011, Smith 2005, Treverton 2003) show up a series of endemic weaknesses in mindset, approach, capabilities and strategy and tactics.

With these in mind it is worth while trying to analyse what possible futures we may face. With certainty an impossibility, a sound approach is to develop a range of hypotheses (as in this example high-level scenario involving tactical nuclear weapons) and, using judgement (not just computer modelling), evaluate their relative merits.

Of prime importance is being realistic about what can and can’t be achieved practically. Especially in a situation where hundreds of factions vie for power, where allegiences are endlessly changing and loyalty cannot be relied upon. At the heart of WWIII is a clash of unreconcilable ideologies which, as the Cold War showed, may take generations to resolve. Negotiation (Howard 1999) is not an option – yet.

Till then, as Lawrence noted following his experiences of the ‘Arab Revolt’ of 1916-18 – and of the subsequent negotiations (including the betrayal of the Sykes-Picot agreement, which still rankles in the Middle East today) – nothing and no one can be trusted and nothing can be relied upon.

In 2016, little has changed from his time. Money, mercenaries and mediocrity mean that the chances of ‘success’ for the West’s new coalition are slim. And in a situation where it is not even possible to say unequivocally what constitutes ‘winning’, then we are all in for a long haul.

What has changed is that this time the consequences are global – and fanaticism,  ruthless death and suicide are ISIS’ most potent weapons of coercion. No one is ‘safe’ and, currently, every possibility may happen.

We live in interesting times.


– Lwin, M. R. (1997) ‘General Tzu’s Army: OPFOR of the Future’. JFQ, USA.
– Howard, N. (1999) ‘Confrontation Analysis: How to Win Operations Other than War. CCRP, DoD.
– Lawrence, T. E. (1922) ‘Seven Pillars of Wisdom’. Various editions.
– Mackay, A. Tatham, S. (2011) ‘Behavioural Conflict: Why understanding people and their motivations will prove decisive in future conflict’. Military Studies Press. Saffron Walden, UK.
– Ostler, N. (2006) ‘Empires of the Word: A Language History of the World’. Harper Collins.
– Smith, R. (2005) ‘The Utility of Force’, p323-331. Published by Allen Lane, London.
– Stewart, R. (2006) Occupational Hazards, pp360-361. Picador, London.
– Tanner, S. (2002) ‘Afghanistan: A Military History from Alexander the Great to the war against the Taliban.
– Treverton, G.F. (2003) ‘Reshaping National Intelligence for an Age of Information’. Cambridge University Press. New York.
– Wallach, J. (2005) ‘Desert Queen. The Extraordinary Life of Gertrude Bell: Adventurer, Adviser to Kings, Ally of Lawrence of Arabia’. Phoenix, London.

Posted in Agility, Appropriateness, Change, Federation, Influence, Interoperability, Opportunities, Possibilities, Practice, Prediction, Probability, Relationships, Risk, Transformation, Transition | Leave a comment

War on Terror – always unwinnable?

The so-called ‘War on Terror‘ has a rather silly name – as daft as a ‘war on democracy’ or a ‘war on happiness’.

Terrorism has been part of the human condition for millenia. As history shows, one person’s terrorist is another person’s freedom fighter (think of Israel, South Africa and Northern Ireland for example). One cannot destroy it, any more than you can destroy the human emotions.

So ‘terror’ can never be eradicated. There will always be those who dissent, feel oppressed or disenfranchised (often with good cause). Indeed, complexity science would say that dissent is a necessary condition for the stability of society – in that otherwise society would be totalitarian.

As our post on types of organisational form and the work by Michael Thompson on ‘organising and disorganising’ indicates, diversity in human society (and in nature in general) is very complicated and the differences of viewpoint and motivation are the source of the rich interactions seen in the world (at over fifty-eight levels from micro to macro and from instant to eons).

A trite, soundbite ‘war on terror’ is not, and was never, going to change that – something much deeper was required.

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Prediction in the face of Deep Uncertainty

So what about prediction? What is the difference between a backward-looking approaches to decision-making and an anticipatory forward-looking ones (discussed here)? It’s partly about the difference between probability (and risk) and possibility (and deep uncertainty) and partly about people’s assumptions about what causes the future to come about. And it’s not just about the ability to model either – there are limits to that.

And, anyway, why is prediction such a challenge? I think it was Dan Quayle who is supposed to have said “The trouble with the future is that you don’t know what is going to happen!”. He’s so right …

It’s easy to assume that if we know the past, we can predict the future. But the natures of the past and of the future are not the same. The past is like a puzzle, things happen and provide facts which are like pieces of a jigsaw puzzle. If some are missing, we probably know they are the red ones with wiggly edges and we can go and look for them. What we have candidate pieces we can apply a matching algorithm against the known need. When the right piece comes up we have the solution. Certainty and predictability seem self-evident, but are they?

The diagram below illustrates this. If we have evidence (green circle) it implies an event and the presence of other evidence waiting to be discovered. Our assumptions can be based on what we know or might know. But the limits on prediction are set by the ‘Prediction Horizon’. With puzzling, we can only predict a short way ahead about, for example,  people’s intentions (shown by the top of the curve, probably only seconds); but we can predict quite a long way ahead about geographical matters (the lower part of the curve). Why is that?Past-Analysis-not-Future-Prediction-01Well. when we try to look into the future we are actually considering, not puzzles, but mysteries. A mystery is ill-formed, it has no pieces, there is no right answer or final outcome and we cannot be sure we have solved it – this is the essence of deep uncertainty. What we can do is form hypotheses about possible futures and seek indicators that support or refute the various possibilities. By ‘competing’ the hypotheses we can anticipate futures and put in place adaptive contingencies. Succesful outcomes are, therefore, practical and feasible. Look at the next chart.

Past-Analysis-not-Future-Prediction-02Some of the possible futures take us beyond the prediction horizon because we are not relying on past evidence – instead we are using our imaginations to ‘think the unthinkable’ – to think not what is probable, but what is possible. The trick, as the third chart shows, is the way that you analyse possibilities and compete the hypotheses. This requires leadership, professionalism, intellect, imagination and courage to buck the trends – and people are doing it effectively and succeeding where others struggle.

Past-Analysis-not-Future-Prediction-03But I’m not going to give those secrets away here!

References: The discussion of puzzles and mysteries has been adapted from Treverton, Gregory F. “Reshaping National Intelligence for an Age of Information“. Cambridge University Press (2003).


Posted in Agent-based modelling, Change, Contextual complexity, Experienced complexity, Possibilities, Prediction, Transformation | Leave a comment

Limits to modelling – Godel’s Incompleteness theorem

Agent-based modelling is often hailed as a way of modelling the future, predicting outcomes in social situations. But there are both hard limitations on what you can predict with modelling, and a lack of understanding of those limitations.This post examines those limitations and shows which models are appropriate for which tasks,

But first, the baselines. As Professor Michael Batty said in 2009 …


Posted in Academic complexity, Adaptation, Agent-based modelling, Appropriateness, Complexity-worthiness, Godel's Incompleteness Theorem, Modelling, Prediction, Probability, Risk, Transformation, Transition | Leave a comment