This is part 1 of a 2 part post.

The question is whether our experience of ‘meaningful’ coincidences, such as Jung’s synchronicity, is actually meaningful or is it merely a meaningless symptom of the laws of probability. And if conclude that it is meaningful what do we mean by that?

I have long been fascinated by Jung’s concept of synchronicity , a term which has been almost wholly absorbed into the New Age Movement and is an expression in common usage in the world today.

It has become a modernised version of the word serendipity, although not, strictly speaking, what Jung meant by the term. Jung’s definition of synchronicity was an acausal meaningful coincidence, not exclusively serendipitous. It could just as easily invoke pathos, in the subject of the synchronicity, as joy.

Synchronicity in our Lives

I would hazard a guess that you, like most of us, have experienced synchronicity. It has become a very widespread experience.

You receive a phone call or an email the day after dreaming about a friend who has been out of contact for a while. You are thinking about someone and then ‘randomly’ bump into them. Or a very common experience is you become aware of a name, number or concept and then repeatedly encounter it over a few days, weeks or months. Even years, in some exceptional cases.

This type of experience, which was once the domain of the mystic or psychic, is something which is now the common property of everyman. However the question is, is it meaningful, does it denote something beyond its random or coincidental occurrence?

A Rational Perspective

The short answer from a rational perspective is quite simply no.

These strange (from the subjects’ perspective) coincidences, in common with much other intuitive or psychic phenomenon, falls under a branch of mathematics know as the mathematics of randomness.

A good book was published recently on this exact subject called The Drunkards Walk .

In it the author, Leonard Mlodinow, very eloquently and logically explains how mathematical randomness operates in the background of our lives. The effect of which is for us to mistakenly draw meaningful inferences where none exist.

This goes beyond the realms of synchronicity to streaks of all kinds. Apparently associated events, which lead us to draw conclusions about this or that, are in the final analysis, mathematical analysis, completely random.

Mlodinow provides some really interesting and entertaining examples. I recommend the book as a good read if you’re interested in the subject.

He provides many examples from the world of sport and business where we encounter extended winning or losing streaks. And from these streaks infer that the individual, or corporation, in question is hot or cold right now. That they have the insight in the magical touch that their competitors don’t or are the cutting edge of their field and so on. (Or not)

Mlodinow provides specific instances from baseball and Hollywood. Batters on record breaking seasons, Hollywood Production Houses who have produced a streak of box office bonanzas. As well as the inverse, where the player or organisation has gone stone cold. He also writes about market pundits and their ability to predict where the markets are going.

Very briefly what he says is these streaks are simply the result of random probability.

Analogous to a streak of reds on a roulette wheel spin. Probability states that the chances of red or black coming up (removing the 0 for the equation for the moment) are 50/50. However as anyone who has played roulette well knows red or black can come up in very long consequential sequences.

And it is the same with any property that is clearly in the domain of randomness. The error is to assume that because red has come up more than black over the last few spins of the wheel that it is hot- meaning the chances of it coming up again are somehow higher than it’s opposite.

Or if you are an inveterate gambler like me , who likes to be perverse and bet against the streak, you mistakenly believe that the preponderance of reds means that black is now overdue.

The exact details of how he uses random maths to draw his conclusions are too lengthy to elaborate on here, however trust me when I say his arguments are very convincing and well supported by the science of random mathematics.

What a can share with you about his argument is that the number of variables at play in any given situation are virtually infinite. Accordingly to assign the success or failure of a team or company or trader etc. to a single variable a player, CEO or trader is a fiction.

The net effect, following the argument, is that these streaks are simply random. That what we infer from them is an illusion.

That possibly Real Madrid who purchased Renaldo for the kingly sum of 80 million pounds sterling, recently, were the victims of the all too common misperception that a players future performance is most likely based on his past performance. And for those of us who watched the dismal performance of the so called stars at the 2010 Soccer World Cup may be inclined to agree with Leonard Mlodinow’s view in this instance.

Furthermore to understand these mathematical laws and to follow them be it in betting or trading the market produces the best possible result, a far better result than the illusory inferences which Mlodinow attempts to disinvest us of.

Simply put then randomness transcends causality in many, many instances of life, love and business, more than we would ever intuitively believe. It is human nature to want to assign a cause or a pattern even where none exist. We do this in order to feel as though we understand what is going on and that we can in some small way chart our own destiny.

Randomness is admittedly a bitter pill to swallow for any philosophy which seeks to elevate man; however it is one with a substantial basis in science.

In this world view it must be said that synchronicity is not only not causally linked but it is meaningless, at least rationally.

Taking the Laws of Probability a Step Further-How far down the Chain of Causality does Chance go?

I think though this Law of Randomness poses a few existential questions which Mlodinow does not address in his book. In fact, not to single Mlodinow out, which the laws of probability in toto do not address.
We all know fortunes change. Not only changes but take an opposite course, an Enantiodromia .

We have all lived through the recent crash in the global economy, as ample evidence of this. This has had the predictable fallout in the lives of individuals (myself included), who in have suffered an unfortunate turn of fate in their personal fortunes.

Let’s look at a specific example; it’s always easier to understand it that way.

What happened to Vodacom?

For many years the cellular giant in South Africa Vodacom was the blue eyed boy not only of the mobile industry but of the South African business world across all sectors. Their growth was exponential and they could simply not put a foot wrong.

In recent years though they have lost some of that wonder-dust. Their major competitor MTN who for close to a decade lived in their shadow has or seems to have eclipsed them in many key areas, including revenues, public image and brand recognition.

What happened?

An argument based on rational causality or rather intuitive causality

Four very significant things happened, which are in the public domain:

1. Their leader Alan Knott-Craig resigned. For most of Vodacom’s life Alan Knott-Craig was seen as the Vodacom’ equivalent of Steve Jobs.
2. They were obliged to withdraw from Nigeria. MTN must cite Nigeria as their most significant stepping stone to their current African dominance.
3. Vodaphone acquired the majority shareholding of Vodacom and implemented operational control suffocating Vodacom’s previous entrepreneurial flair.
4. They have been hurt by the global recession.

The above four issues, admittedly along with other smaller or unknown variables are largely responsible for Vodacom’s downturn. The point being that we can assign a cause to what has occurred; we believe we know why, either definitely or at least with a very high degree of probability.

The above is the way a business analyst would typically make sense of what happened.

An argument based on pure Random Probability

Leonard Mlodinow would say something very different. To be fair he hasn’t spoken on the above topic, but I believe I am correctly inferring what he may reasonably be thought to say.

He would say no, the reason Vodacom has lost much of its shine is not because of the above, it is rather subject to pure probability. Over any spread of variables such as time and multiple corporations, at any given time some will fare better than others. For a time anyway and then at a different time they will not fare as well.

Another more accurate way to say this would be to say not that there are not causes, but simply that the number of variables of those causes is too great to measure accurately. Hence probability mathematics is our best tool of analysis.

The causes, which we now assign in retrospect, are a fallacy. It is a slight of mind, if you will which tricks us into, or lulls us into, believing we know why something has occurred. When in truth we do not know why other than this event along with the whole of our lives is governed purely by the laws of mathematical probability.

Let’s assume hypothetically that the inverse had occurred. Vodacom had risen in the period in question to even greater heights in terms of revenues and status. We may equally, and just as mistakenly, attribute this to the same variables, but contextualise them differently.

For example:
1. Allan Knott-Craig stepped out of the way allowing a long awaited change of guard, with a new improved and more modern orientation.
2. They had the foresight to withdraw from a situation in Nigeria that may well have seen them face serious fiduciary charges had they remained.
3. Vodaphone took operational control which saw Vodacom benefit from their massive global infrastructure and experience.
4. Vodacom bucked the trend in the economic downturn through very efficient cost saving methods.

Now I don’t mean for the above to be taken too seriously. Only for it to illustrate a significant point, we frequently assign causes in hindsight which may not be as perfect as we think. We may very well be assigning causes to fit the result when those are not objectively the actual reasons for the result we are seeking to explain.

The Issue of Attributing Cause

The above might at first seem a little farfetched. That possibly I am taking the law of random probability too far, or at least that Leonard Mlodinow is in his book. But that is not necessarily the case, at least not scientifically speaking.

We see the randomness of events as counter intuitive, and are innately inclined to assign causes. However this is a very human centred way of looking at things. As people we naturally want to assign credit or criticism to someone or something. What caused this to happen (?) is frequently underpinned in our minds as who caused this to happen?

In science however the issue of cause is a complex and challenging issue. Science tends to speak of certain conditions being prevalent when something happens rather than this caused that. Naturally nothing can ever be assigned to a single cause.

Take a very simple example a billiard ball striking another stationary billiard ball and ‘causing’ it to move. Now there are at least three fundamental challenges in this interpretation.

1. It is not only the first billiard ball that causes the second to move. There have to be a number of variables converging in space and time to allow that to happen.
a. Laws of motion.
b. Laws of gravity.
c. Laws governing space and time.
d. There needs to an observer.
e. Laws of power and energy transmission, and so on.

2. This event is only a single link in a chain of causality which has (for all practical purposes) an infinite sequence e.g. what caused the first ball to move and the one before that etc. in an infinite recursive sequence.

3. A fundamental challenge with empirical science is that it is empirically rather than rationally deductive. I won’t go into this at length except to say the reason we know the second ball will move is because it always has. However that does not mean absolutely that the next ball being struck will move. Empirical deduction can change at the first instance of a counter example- which does occur.

The reason we didn’t fall off the earth once was because it was flat and we were fortunately on the upside?, until it wasn’t, turns out it is spherical and we actually don’t fall of because of gravity.

So empirical science is always as if. That is how it seems from our current perspective.

So why do we Attribute Causes?

Because we want to believe we have an element of control and understanding.
If we accept that fact that we don’t know what caused anything it makes it very hard to chart a life for ourselves. We become epiphenomenon i.e. we are not at the fulcrum of our existence we are rather at the periphery and are just along for the ride.
Not being able to accept this we assign causes, to make ourselves believe that can affect our reality and we know why things are happening.

Noble and human as that may be it does not regrettably make it true.

To read on Is it Meaningful or Random? Part 2 An irrational Perspective (in defence of synchronicity)