Irrationality: The Enemy Within by Stuart Sutherland (1992)

The only way to substantiate a belief is to try to disprove it. (p.48)

Sutherland was 65 when he wrote this book, nearing the end of a prestigious career in psychology research. His aim was to lay out, in 23 themed chapters, all the psychological and sociological research data  from hundreds of experiments, which show just how prey the human mind is to a plethora of unconscious biases, prejudices, errors, mistakes, misinterpretations and so on – the whole panoply of ways in which the supposedly rational human beings can end up making grotesque mistakes. By the end he claims to have defined and demonstrated over 100 distinct cognitive errors humans are prone to (p.309).

I first read it in 2000 and it made a big impact on me because I didn’t really know that this entire area of study existed, and had certainly never read such a compendium of sociology and psychology experiments before.

I found the naming of the various errors particularly powerful. They reminded me of the lists of weird and wonderful Christian heresies I was familiar with from years of reading medieval history. And, after all, the two have a lot in common, both being lists of ‘errors’ which the human mind can make as it falls short of a) orthodox theology and b) optimally rational thinking, the great shibboleths of the Middle Ages and of the Modern World, respectively.

 

Reading it now, 20 years later, having brought up a couple of children and worked for a while in big government departments, I am a lot less shocked and amazed. I have witnessed at first hand the utter irrationality of small and medium-sized children – and then so many examples of the corporate conformity, avoidance of embarrassment, unwillingness to speak up, deferral to authority, and general mismanagement to be found in the civil service that, upon rereading the book, hardly any of it came as a surprise, more a confirmation of what I’ve witnessed at first hand.

But to have the errors so carefully named and defined and worked through in a structured way, with so many experiments giving such vivid proof of how useless humans are at even basic logic was still very enjoyable.

What is rationality?

You can’t define irrationality without first defining what you mean by rationality:

Rational thinking is most likely to lead to the conclusion that is correct, given the information available at the time (with the obvious rider that, as new information comes to light, you should be prepared to change your mind).

Rational action is that which is most likely to achieve your goals. But in order to achieve this, you have to have clearly defined goals. Not only that but, since most people have multiple goals, you must clearly prioritise your goals.

Few people think hard about their goals and even fewer think hard about the many possible consequences of their actions. (p.129)

Cognitive biases contrasted with logical fallacies

Before proceeding it’s important to point out that there is a wholly separate subject of logical fallacies. As part of his Philosophy A-Level my son was given a useful handout with a list of about fifty of these. But logical fallacies are not the same as cognitive biases.

A logical fallacy stems from an error in a logical argument; it is specific and easy to identify and correct. Cognitive bias derives from deep-rooted, thought-processing errors which themselves stem from problems with memory, attention, self-awareness, mental strategy and other mental mistakes. Far harder to acknowledge, in many cases, very hard to correct.

Fundamentals of irrationality

1. Innumeracy One of the largest causes of all irrational behaviour is that people by and large don’t understand statistics or maths. Thus most people are not intellectually equipped to understand the most reliable type of information available to human beings – data in the form of numbers. Instead they tend to make decisions based on a wide range of faulty and irrational psychological biases.

2. Physiology People are often influenced by physiological factors. Apart from obvious ones like tiredness or hunger, which are universally known to affect people’s cognitive abilities, there are also a) drives (direct and primal) like hunger, thirst, sex, and b) emotions (powerful but sometimes controllable) like love, jealousy, fear and – especially relevant – embarrassment: acute reluctance to acknowledge limits to your own knowledge or that you’ve made a mistake.

More seriously people can be alcoholics, drug addicts, and prey to a wide range of other obsessive behaviours, not to mention suffering from a wide range of mental illnesses or conditions which undermine any attempt at rational decision-making, such as stress, anxiety or, at the other end of the spectrum, depression and loss of interest.

3. The functional limits of consciousness Numerous experiments have shown that human beings have a limited capacity to process information. Given that people rarely have a) a sufficient understanding of the relevant statistical data, and b) the RAM capacity to process all the data required to make the optimum decision, it is no surprise that most of us fall back on all manner of more limited, non-statistical biases and prejudices when it comes to making decisions.

The wish to feel good The world is threatening, dangerous and competitive. Humans want to feel safe, secure, calm, in control. This is fair enough, but it does mean that people have a way of blocking out any kind of information which threatens them. People irrationally believe they are cleverer than they in fact are, are qualified in areas of activity of knowledge where they aren’t, people stick to bad decisions for fear of being embarrassed or humiliated, and for the same reason reject new evidence which contradicts their position.

Named types of error and bias

Jumping to conclusions Sutherland tricks the reader no page one by asking a series of questions and then pointing out, that if you tried to answer about half of them, you are a fool since they don’t contain enough information to arrive at any sort of solution. Jumping to conclusions before we have enough evidence is a basic and universal error. One way round this is to habitually use a pen and paper to set out the pros and cons of any decision, which also helps highlight areas where you realise you don’t have enough information.

The availability error All the evidence is that the conscious mind can only hold a small number of data or impressions at any one time (near the end of the book, Sutherland claims the maximum is seven items, p.319). Many errors are due to people reaching for the most available explanation, using the first thing that comes to mind, and not taking the time to investigate further and make a proper, rational survey of the information.

Many experiments show that you can unconsciously bias people by planting ideas, words or images in their minds which then directly affect decisions they take hours later about supposedly unconnected issues.

Studies show that doctors who have seen a run of a certain condition among their patients become more likely to diagnose it in patients who don’t have it. The diagnosis is more ‘available’.

The news media is hard-wired to publicise shocking and startling stories which leads to the permanent misleading of the reading public. One tourist eaten by a shark in Australia eclipses the fact that you are far more likely to die in a car crash than be eaten by a shark.

Thus ‘availability’ is also affected by impact or prominence. Experimenters read out a list of men and women to two groups without telling them that there are exactly 25 men and 25 women, and asked them to guess the ratio of the sexes. If the list included some famous men, the group was influenced to think there were more men, if the list included famous women, the group thought there are more women than men.

The entire advertising industry is based on the availability error in the way it invents straplines, catchphrases and jingles designed to pop to the front of your mind when you consider any type of product, to be – in other words – super available.

I liked the attribution of the well-known fact that retailers price goods at just under the nearest pound, to the availability error. Most of us find £5.95 much more attractive than £6. It’s because we only process the initial 5, the first digit, it is more available.

Numerous studies have shown that the effect is hugely increased under stress. Under stressful situations – in an accident – people fixate on the first solution that comes to mind and refuse to budge.

The primacy effect First impressions. Interviewers make up their minds in the first minute of an interview and then spend the rest of the time collecting data to confirm that first impression.

The anchor effect In picking a number people tend to choose one close to any number they were presented with. Two groups were asked to estimate whether the population of Turkey was a) bigger than 5 million b) less than 65 million, and what it was. The group who’d had 5 million planted in their mind hovered around 15 million, the group who’d had 65 million hovered around 35 million. They were both wrong. It is 80 million.

The halo effect People extrapolate the nature of the whole from just one quality e.g. in tests, people think attractive people must be above average in personality and intelligence although of course there is no reason why they should be. Hence this error’s alternative name, the ‘physical attractiveness stereotype’. The halo effect is fundamental to advertising which seeks to associate images of beautiful men, women, smiling children, sunlit countryside etc with the product.

The existence of the halo effect and primacy effect are both reasons why interviews are a poor way to assess candidates for jobs or places.

The devil effect Opposite of the above: extrapolating from negative appearances to the whole. This is why it’s important to dress smartly for an interview or court appearance, it really does influence. In an experiment examiners were given identical answers, but some in terrible handwriting, some in beautifully clear handwriting. Clear handwriting consistently scored higher marks despite identical factual content of the scripts.

Illusory correlation People find links between disparate phenomena which simply don’t exist, thus:

  • people exaggerate the qualities of people or things which stand out from their environments
  • people associate rare qualities with rare things

This explains a good deal of racial prejudice: a) immigrants stand out b) a handful of immigrants commit egregious behaviour – therefore it is a classic example of illusory correlation to associate the two. What is missing is taking into account all the negative examples i.e. the millions of immigrants who make no egregious behaviour and whose inclusion would give you a more accurate statistical picture. Pay attention to negative cases.

Stereotypes 1. People tend to notice anything which supports their existing opinions. 2. We notice the actions of ‘minorities’ much more than the actions of the invisible majority.

Projection People project onto neutral phenomena patterns and meanings they are familiar with or which bolster their beliefs. Compounded by –

Obstinacy Sticking to personal opinions (often made in haste / first impressions / despite all evidence to the contrary) aka The boomerang effect When someone’s opinions are challenged, they just become more obstinate about it. Aka Belief persistence. Aka pig-headedness. Exacerbated by –

Group think People associate with others like themselves, which makes them feel safe by a) confirming their beliefs and b) letting them hide in a crowd. Experiments have shown how people in self-supporting groups are liable to become more extreme in their views. Also – and I’ve seen this myself – groups will take decisions that almost everyone in the group, as individuals, know to be wrong – but no-one is prepared to risk the embarrassment or humiliation of pointing it out. The Emperor’s New Clothes. Groups are more likely to make irrational decisions than individuals are.

Confirmation bias The tendency to search for, interpret, favour, and recall information in a way that confirms one’s pre-existing beliefs or hypotheses. In an experiment people were read out a series of statements about a named person, who had a stated profession and then two adjectives describing them, one what you’d expect, the other less predictable. ‘Carol, a librarian, is attractive and serious’. When asked to do a quiz at the end of the session, participants showed a marked tendency to remember the expected adjective, and forget the unexpected one. Everyone remembered that the air stewardess was ‘attractive’ but remembered the librarian for being ‘serious’.

We remember what we expect to hear. (p.76)

Or: we remember what we remember in line with pre-existing habits of thought, values etc.

We marry people who share our opinions, we have friends with people who share our opinions, we agree with everyone in our circle on Facebook.

Self-serving biases When things go well, people take the credit, when things go badly, people blame external circumstances.

Avoiding embarrassment People obey, especially in a group situation, bad orders because they don’t want to stick out. People go along with bad decisions because they don’t want to stick out. People don’t want to admit they’ve made a mistake, in front of others, or even to themselves.

Avoiding humiliation People are reluctant to admit mistakes in front of others. And rather than make a mistake in front of others, people would rather keep quiet and say nothing (in a meeting situation) or do nothing, if everyone else is doing nothing (in an action situation). Both of these avoidances feed into –

Obedience The Milgram experiment proved that people will do any kind of atrocity for an authoritative man in a white coat. All of his students agreed to inflict life-threatening levels of electric shock on the victim, supposedly wired up in the next door room and emitting blood curdling (faked) screams of pain. 72% of Senior House Officers wouldn’t question the decision of a consultant, even if they thought he was wrong.

Conformity Everyone else is saying or doing it, so you say or do it so as not to stick out / risk ridicule.

Obedience is behaving in a way ordered by an authority figure. Conformity is behaving in a way dictated by your peers.

The wrong length lines experiment. You’re put in a room with half a dozen stooges, and shown a piece of card with a line on it and then another piece of card with three lines of different length on it, and asked which of the lines on card B is the same length as the line on card A. To your amazement, everyone else in the room chooses a line which is obviously wildly wrong. In experiments up to 75%! of people in this situation go along with the crowd and choose the line which they are sure, can see, know is wrong – because people are that easily swayed.

Sunk costs fallacy The belief that you have to continue wasting time and money on a project because you’ve invested x amount of time and money to date. Or ‘throwing good money after bad’.

Sutherland keeps cycling round the same nexus of issues, which is that people jump to conclusions – based on availability, stereotypes, the halo and anchor effects – and then refuse to change their minds, twisting existing evidence to suit them, ignoring contradictory evidence.

Misplaced consistency & distorting the evidence Nobody likes to admit (especially to themselves) that they are wrong. Nobody likes to admit (especially to themselves) that they are useless at taking decisions.

Our inability to acknowledge our own errors even to ourselves is one of the most fundamental causes of irrationality. (p.100)

And so:

  • people consistently avoid exposing themselves to evidence that might disprove their beliefs
  • on being faced with evidence that disproves their beliefs, they ignore it
  • or they twist new evidence so as to confirm their existing beliefs
  • people selectively remember their own experiences, or misremember the evidence they were using at the time, in order to validate their current decisions and beliefs
  • people will go to great lengths to protect their self-esteem

Sutherland says the best cleanser / solution / strategy to fixed and obstinate ideas is to make the time to gather as much evidence as possible and to try to disprove your own position. The best solution will be the one you have tried to demolish with all the evidence you have and still remains standing.

People tend to seek confirmation of their current hypothesis, whereas they should be trying to disconfirm it. (p.138)

Fundamental attribution error Ascribing other people’s behaviour to their character or disposition rather than to their situation. Subjects in an experiment watched two people holding an informal quiz: the first person made up questions (based on what he knew) and asked the second person who, naturally enough, hardly got any of them right. Observers consistently credited the quizzer with higher intelligence than the answerer, completely ignoring the in-built bias of the situation, and instead ascribing the difference to character.

We are quick to personalise and blame in a bid to turn others into monolithic entities which we can then define and control – this saves time and effort, and makes us feel safer and secure – whereas the evidence is that all people are capable of a wide range of behaviours depending on the context and situation.

Once you’ve pigeon-holed someone, you will tend to notice aspects of their behaviour which confirm your view – confirmation bias and/or illusory correlation and a version of the halo/devil effect. One attribute colours your view of a more complex whole.

Actor -Observer Bias Variation on the above: when we screw up we find all kinds of reasons in the situation to exonerate ourselves, we performed badly because we’re ill, jet-lagged, grandma died, reasons that are external to us. If someone else screws up, it is because they just are thick, lazy, useless. I.e. we think of ourselves as complex entities subject to multiple influences, and others as monolithic types.

False Consensus Effect Over-confidence that other people think and feel like us, that our beliefs and values are the norm – in my view one of the greatest errors of our time.

It is a variation of the ever-present Availability Error because when we stop to think about any value or belief we will tend to conjure up images of our family and friends, maybe workmates, the guys we went to college with, and so on: in other words, the people available to memory – simply ignoring the fact that these people are a drop in the ocean of the 65 million people in the UK. See Facebubble.

The False Consensus Effect reassures us that we are normal, our values are the values, we’re the normal ones: it’s everyone else who is wrong, deluded, racist, sexist, whatever we don’t approve of.

Not in Sutherland’s book, I’ve discovered some commentators naming this the Liberal fallacy:

For liberals, the correctness of their opinions – on universal health care, on Sarah Palin, on gay marriage – is self-evident. Anyone who has tried to argue the merits of such issues with liberals will surely recognize this attitude. Liberals are pleased with themselves for thinking the way they do. In their view, the way they think is the way all right-thinking people should think. Thus, “the liberal fallacy”: Liberals imagine that everyone should share their opinions, and if others do not, there is something wrong with them. On matters of books and movies, they may give an inch, but if people have contrary opinions on political and social matters, it follows that the fault is with the others. (Commentary magazine)

Self-Serving Bias People tend to give themselves credit for successes but lay the blame for failures on outside causes. If the project is a success, it was all due to my hard work and leadership. If it’s a failure, it’s due to circumstances beyond my control, other people not pulling their weight etc.

Preserving one’s self-esteem These three errors are all aspects of preserving our self-esteem. You can see why this has an important evolutionary and psychological purpose. In order to live, we must believe in ourselves, our purposes and capacities, believe our values are normal and correct, believe we make a difference, that our efforts bring results. No doubt it is a necessary belief and a collapse of confidence and self-belief can lead to depression and possibly despair. But that doesn’t make it true. People should learn the difference between having self-belief to motivate themselves, and developing the techniques to gather the full range of evidence – including the evidence against your own opinions and beliefs – which will enable them to make correct decisions.

Representative error People estimate the likelihood of an event by comparing it to an existing prototype / stereotype that already exists in our minds. Our prototype is what we think is the most relevant or typical example of a particular event or object. This often happens around notions of randomness: people have a notion of what randomness should look like i.e. utterly scrambled. But in fact plenty of random events or sequences arrange themselves into patterns we find meaningful. So we dismiss them as not really random.  I.e. we have judged them against our preconception of what random ought to look like.

Ask a selection of people which of these three sets of six coin tosses where H stands for heads, T for tails is random.

  1. TTTTTT
  2. TTTHHH
  3. THHTTH

Most people will choose 3 because it feels random. But of course all three are equally likely or unlikely.

Hindsight In numerous experiments people have been asked to predict the outcome of an event, then after the event questioned about their predictions. Most people forget their inaccurate predictions and misremember that they were accurate.

Overconfidence Most professionals have been shown to overvalue their expertise i.e. exaggerate their success rates.


Statistics

The trouble with this and Paulos’s books is that the entire area of statistics is separate and distinct from errors of thought and cognitive biases. I.e. you can imagine someone who avoids all of the cognitive and psychological errors named above, but still makes howlers when it comes to statistics simply because they’re not very good at it.

This is because the twin areas of Probability and Statistics are absolutely fraught with difficulty. Either you have been taught the correct techniques, and understand them, and practice them regularly (and both books demonstrate that even experts make howling mistakes in the handling of statistics and probability) or, like most of us, you have not.

As Sutherland points out, most people’s knowledge of statistics is non-existent. Since we live in a society whose public discourse i.e. politics, is ever more dominated by statistics, there is a simple conclusion: most of us have little or no understanding of the principles and values which underpin modern society.

Errors in estimating probability or misunderstanding samples, opinion polls and so on are probably a big part of irrationality, but I felt that they’re so distinct from the psychological biases discussed above, that they almost require a separate volume, or a separate ‘part’ of this volume. Briefly, common mistakes are:

  • too small a sample size
  • biased sample
  • not understanding that any combination of probabilities is less likely than either on their own, which requires an understanding of base rate or a priori probability
  • the law of large numbers – the more a probabilistic event takes place, the more likely the result will move towards the theoretical probability
  • be aware of the law of regression to the mean
  • be aware of the law of large numbers

Gambling

This is even more true of gambling. It is a highly specialised and advanced form of probability applied to games which have been pored over by very clever people for centuries. It’s not a question of a few general principles, this is a vast, book-length subject in its own right. Some points that emerge:

  • always work out the expected value of a bet i.e. the amount to be won times the probability of winning it

The two-by-two box

It’s taken me some time to understand this principle which is given in both Paulos and Sutherland.

When two elements with a yes/no result are combined, people tend to look at the most striking correlation and fixate on it. The only way to avoid the false conclusions that follow from that is to draw a 2 x 2 box and work through the figures.

Here is a table of 1,000 women who had a mammogram because their doctors thought they had symptoms of breast cancer.

Women with cancer Women with no cancer Total
Women with positive mammography 74 110 184
Women with negative mammography 6 810 816
80 920 1000

Bearing in mind that a conditional probability is saying that if X and Y are linked, then the chances of X, if Y, are so and so – i.e. the probability of X is conditional on the probability of Y – this table allows us to work out the following conditional probabilities:

1. The probability of getting a positive mammogram or test result, if you do actually have cancer, is 74 out of 80 = .92 (out of the 80 women with cancer, 74 were picked up by the test)

2. The probability of getting a negative mammogram or test result and not having cancer, is 810 out of 920 = .88

3. The probability of having cancer if you test positive, is 74 out of 184 = .40

4. The probability of having cancer if you test negative, is 6 out of 816 = .01

So 92% of women of women with cancer were picked up by the test. BUT Sutherland quotes a study which showed that a shocking 95% of doctors thought that this figure – 92% – was also the probability of a patient who tested positive having the disease. By far the majority of US doctors thought that, if you tested positive, you had a 92% chance of having cancer. They fixated on the 92% figure and transposed it from one outcome to the other, confusing the two. But this is wrong. The probability of a woman testing positive actually having cancer is given in conclusion 3 – 74 out of 184 = 40%. This is because 110 out of the total 184 women tested positive, but did not have cancer.

So if a woman tested positive for breast cancer, the chances of her actually having it are 40%, not 92%. Quite a big difference (and quite an indictment of the test, by the way). And yet 95% of doctors thought that if a woman tested positive she had a 92% likelihood of having cancer.

Sutherland goes on to quote a long list of other situations where doctors and others have comprehensively  misinterpreted the results of studies like this, with varied and sometimes very negative consequences.

The moral of the story is if you want to determine whether one event is associated with another, never attempt to keep the co-occurrence of events in your head. It’s just too complicated. Maintain a written tally of the four possible outcomes and refer to these.


Deep causes

Sutherland concludes the book by speculating that all the hundred or so types of irrationality he has documented can be attributed to five fundamental causes:

  1. Evolution We evolved to make snap decisions, we are brilliant at processing visual information and responding before we’re even aware of it. Conscious thought is slower, and the conscious application of statistics, probability, regression analysis and so on is very slow and laborious. Most people never acquire it.
  2. Brain structure As soon as we start perceiving, learning and remembering the world around us brain cells make connections. The more the experience is repeated, the stronger the connections become. Routines and ruts form, which are hard to budge.
  3. Heuristics Everyone develops mental short-cuts, techniques to help make quick decisions. Not many people bother with the laborious statistical techniques for assessing relative benefits which Sutherland describes.
  4. Failure to use elementary probability and elementary statistics Ignorance is another way of describing this, mass ignorance. Sutherland (being an academic) blames the education system. I, being a pessimist, attribute it to basic human nature. Lots of people just are lazy, lots of people just are stupid, lots of people just are incurious.
  5. Self-serving bias In countless ways people are self-centred, overvalue their judgement and intelligence, overvalue the beliefs of their in-group, refuse to accept it when they’re wrong, refuse to make a fool of themselves in front of others by confessing error or pointing out errors in others (especially the boss) and so on.

I would add two more:

Suggestibility. Humans are just tremendously suggestible.

Say a bunch of positive words to test subjects, then ask them questions on an unrelated topic: they’ll answer positively. Take a different representative sample of subjects and run a bunch of negative words past them, then ask them the same unrelated questions, and their answers will be measurably more negative.

Ask subjects how they get a party started and they will talk and behave in an extrovert manner to the questioner. Ask them how they cope with feeling shy and ill at ease at parties, and they will tend to act shy and speak quieter. Thus, the initial terms or anchor defines the ensuing conversation.

In one experiment a set of subjects were shown one photo of a car crash. Half were asked to describe what they think happened when one car hit another; the other half were asked to describe what they thought happened when one car smashed into the other. The ones given the word ‘smashed’ gave much more melodramatic accounts. Followed up a week later, the subjects were asked to describe what they remembered of the photo. The subjects given the word ‘hit’ fairly accurately described it, whereas the subjects given the word ‘smashed’ invented all kinds of details like a sea of broken glass around the vehicles which simply wasn’t there, which their imaginations had invented, all at the prompting of one word.

Many of the experiments Sutherland quotes demonstrate what you might call higher-level biases: but underling many of them is this simple-or-garden observation, that people are tremendously easily swayed, by both external and internal causes, away from the line of cold logic.

Anthropomorphism Another big underlying cause is anthropomorphism, namely the attribution of human characteristics to objects, events, chances, odds and so on. In other words, people really struggle to accept the high incidence of random accidents. Almost everyone attributes a purpose or intention to almost everything that happens. This means our perceptions of almost everything in life are skewed from the start.

During the war Londoners devised innumerable theories about the pattern of German bombing. After the war, when Luftwaffe records were analysed, it showed the bombing was more or less at random.

The human desire to make sense of things – to see patterns where none exists or to concoct theories… can lead people badly astray. (p.267)

Suspending judgement is about the last thing people are capable of. People are extremely uneasy if things are left unexplained. Most people rush to judgement like water into a sinking ship.

Cures

  • keep an open mind
  • reach a conclusion only after reviewing all the possible evidence
  • it is a sign of strength to change one’s mind
  • seek out evidence which disproves your beliefs
  • do not ignore or distort evidence which disproves your beliefs
  • never make decisions in a hurry or under stress
  • where the evidence points to no obvious decision, don’t take one
  • learn basic statistics and probability
  • substitute mathematical methods (cost-benefit analysis, regression analysis, utility theory) for intuition and subjective judgement

Comments on the book

Out of date

Irrationality was first published in 1992 and this makes the book dated in several ways (maybe this is why the first paperback edition was published by upmarket mass publisher Penguin, whereas the most recent edition was published by the considerably more niche publisher, Pinter & Martin).

In the chapter about irrational business behaviour he quotes quite a few examples from the 1970s and the oil crisis of 1974. These and other examples – such as the long passage about how inefficient the civil service was in the early 1970s – feel incredibly dated now.

And the whole thing was conceived, researched and written before there was an internet or any of the digital technology we take for granted nowadays. Can’t help make wonder how the digital age has changed or added to the long list of biases, prejudices and faulty thinking he gives, and what errors of reason have emerged specific to our fabulous digital technology.

Grumpy

But it also has passages where Sutherland extrapolates out to draw general conclusions and some of these sound more like the grumblings of a grumpy old man than anything based on evidence.

Thus Sutherland whole-heartedly disapproves of ‘American’ health fads, dismisses health foods as masochistic fashion and is particularly scathing about jogging. He thinks ‘fashion’ in any sphere of life is ludicrously irrational. He is dismissive of doctors who he accuses of rejecting statistical evidence, refusing to share information with patients and wildly over-estimating their own diagnostic abilities.

He thinks the publishers of learned scientific journals are more interested in making money out of scientists than in ‘forwarding the progress of science’ (p.185). He thinks the higher average pay that university graduates tend to get is unrelated to their attendance at university and more to do with having well connected middle and upper middle class parents, and thus considers the efforts of successive Education Secretaries to introduce student loans to be unscientific and innumerate (p.186). He criticises Which consumer magazine for using too small samples in its testing (p.215). In an extended passage he summarises Leslie Chapman’s blistering (and very out of date) critique of the civil service, Your Disobedient Servant published in 1978 (pp.69-75).

He really has it in for psychoanalysis which he accuses of all sorts of irrational thinking such as projecting, false association, refusal to investigate negative instances, failing to take into account the likelihood that the patient would have improved anyway, and so on. Half way through the book he gives a thumbnail summary:

Self-deceit exists on a massive scale: Freud was right about that. Where he went wrong was in attributing it all to the libido, the underlying sex drive. (p.197)

In other words, the book is liberally sprinkled with Sutherland’s own personal opinions, which sometimes risk giving it a crankish feel.

On the other hand it’s surprising to see how some hot button issues haven’t changed at all. In the passage about the Prisoners’ Dilemma, Sutherland takes as a real life example the problem the nations of the world were having in 1992 in agreeing to cut back carbon dioxide emissions. Sound familiar?

He also states that the single biggest factor undermining international co-operation was America’s refusal to sign global treaties to limit global warming. In 1992! Plus ça change.

Against stupidity the gods themselves contend in vain

And finally, these are the mistakes made by the most intelligent and best educated among us, people trained to assess and act on evidence.

Neither this nor John Allen Paulos’s books take into account the obvious fact that lots of people are, how shall we put it, of low educational achievement. They begin with poor genetic material, are raised in families where no-one cares about education, are let down by poor schools, and are excluded or otherwise demotivated, with the result that :

  • the average reading age in the UK is 9
  • about one in five Britons (over ten million) are functionally illiterate, and probably about the same rate innumerate

which all contributes to the general festival of irrationality.

Trying to keep those pesky cognitive errors at bay (in fact The Witch by Pieter Bruegel the Elder)

Trying to keep those pesky cognitive errors at bay (otherwise known as The Witch by Pieter Bruegel the Elder)


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Alex’s Adventures In Numberland by Alex Bellos (2010)

Alexander Bellos (born in 1969) is a British writer and broadcaster. He is the author of books about Brazil and mathematics, as well as having a column in The Guardian newspaper. After adventures in Brazil (see his Wikipedia page) he returned to England in 2007 and wrote this, his first book. It spent four months in the Sunday Times bestseller list and led on to five more popular maths books.

It’s a hugely enjoyable read for three reasons:

  1. Bellos immediately establishes a candid, open, good bloke persona, sharing stories from his early job as a reporter on the Brighton Argus, telling some colourful anecdotes about his time in Brazil and then being surprisingly open about the way that, when he moved back to Britain, he had no idea what to do. The tone of the book is immediately modern, accessible and friendly.
  2. However this doesn’t mean he is verbose. The opposite. The book is packed with fascinating information. Every single paragraph, almost every sentence contains a fact or insight which makes you sit up and marvel. It is stufffed with good things.
  3. Lastly, although its central theme is mathematics, it approaches this through a wealth of information from the humanities. There is as much history and psychology and anthropology and cultural studies and philosophy as there is actual maths, and these are all subjects which the average humanities graduate can immediately relate to and assimilate.

Chapter Zero – A Head for Numbers

Alex meets Pierre Pica, a linguist who’s studied the Munduruku people of the Amazon and discovered they have little or no sense of numbers. They only have names for numbers up to five. Also, they cluster numbers together logarithmically i.e. the higher the number, the closer together they clustered them. Same thing is done by kindergarten children who only slowly learn that numbers are evenly spaced, in a linear way.

This may be because small children and the Munduruku don’t count so much as estimate using the ratios between numbers.

It may also be because above a certain number (five) Stone Age man needed to make quick estimates along the lines of, Are there more wild animals / members of the other gang, than us?

Another possibility is that distance appears to us to be logarithmic due to perspective: the first fifty yards we see in close detail, the next fifty yards not so detailed, beyond 100 yards looking smaller, and so on.

It appears that we have to be actively taught when young to overcome our logarithmic instincts, and to apply the rule that each successive whole number is an equal distance from its predecessor and successor i.e. the rational numbers lies along a straight line at regular intervals.

More proof that the logarithmic approach is the deep, hard-wired one is the way most of us revert to its perspective when considering big numbers. As John Allen Paulos laments, people make no end of fuss about discrepancies between 2 or 3 or 4 – but are often merrily oblivious to the difference between a million or a billion, let alone a trillion. For most of us these numbers are just ‘big’.

He goes on to describe experiments done on chimpanzees, monkeys and lions which appear to show that animals have the ability to estimate numbers. And then onto experiments with small babies which appear to show that as soon as they can focus on the outside world, babies can detect changes in number of objects.

And it appears that we also have a further number skill, that guesstimating things – the journey takes 30 or 40 minutes, there were twenty or thirty people at the party, you get a hundred, maybe hundred and fifty peas in a sack. When it comes to these figures almost all of us give rough estimates.

To summarise:

  • we are sensitive to small numbers, acutely so of 1, 2, 3, 4, less so of 5, 6, 7, 8, 9
  • left to our own devices we think logarithmically about larger numbers i.e lose the sense of distinction between them, clump them together
  • we have a good ability to guesstimate medium size numbers – 30, 40, 100

But it was only with the invention of notation, a way of writing numbers down, that we were able to create the linear system of counting (where every number is 1 larger than its predecessor, laid out in a straight line, at regular intervals).

And that this cultural invention enabled human beings to transcend our vague guesstimating abilities, and laid the basis for the systematic manipulation of the world which followed

Chapter One – The Counter Culture

The probable origins of counting lie in stock taking in the early agricultural revolution some 8,000 years ago.

We nowadays count using a number base 10 i.e. the decimal system. But other bases have their virtues, especially base 12. It has more factors i.e. is easier to divide: 12 can be divided neatly by 2, 3, 4 and 6. A quarter of 10 is 2.5 but of 12 is 3. A third of 10 is 3.333 but of 12 is 4. Striking that a version of the duodecimal system (pounds, shillings and pence) hung on in Britain till we finally went metric in the 1970s. There is even a Duodecimal Society of America which still actively campaigns for the superiority of a base 12 counting scheme.

Bellos describes a bewildering variety of other counting systems and bases. In 1716 King Charles XII of Sweden asked Emmanuel Swedenborg to devise a new counting system with a base of 64. The Arara in the Amazon count in pairs, the Renaissance author Luca Paccioli was just one of hundreds who have devised finger-based systems of counting – indeed, the widespread use of base 10 probably stems from the fact that we have ten fingers and toes.

He describes a complicated Chinese system where every part of the hand and fingers has a value which allows you to count up to nearly a billion – on one hand!

The Yupno system which attributes a different value for parts of the body up to its highest number, 33, represented by the penis.

Diagram showing numbers attributed to parts of the body by the Yupno tribe

Diagram showing numbers attributed to parts of the body by the Yupno tribe

There’s another point to make about his whole approach which comes out if we compare him with the popular maths books by John Allen Paulos which I’ve just read.

Paulos clearly sees the need to leaven his explanations of comparative probability and Arrow’s Theorem and so on with lighter material and so his strategy is to chuck into his text things which interest him: corny jokes, anecdotes about baseball, casual random digressions which occur to him in mid-flow. But al his examples clearly 1. emanate from Paulos’s own interests and hobby horses (especially baseball) and 2. they are tacked onto the subjects being discussed.

Bellos, also, has grasped that the general reader needs to be spoonfed maths via generous helpings of other, more easily digestible material. But Bellos’s choice of material arises naturally from the topic under discussion. The humour emerges naturally and easily from the subject matter instead of being tacked on in the form of bad jokes.

You feel yourself in the hands of a master storyteller who has all sorts of wonderful things to explain to you.

In fourth millennium BC, an early counting system was created by pressing a reed into soft clay. By 2700 BC the Sumerians were using cuneiform. And they had number symbols for 1, 10, 60 and 3,600 – a mix of decimal and sexagesimal systems.

Why the Sumerians grouped their numbers in 60s has been described as one of the greatest unresolved mysteries in the history of arithmetic. (p.58)

Measuring in 60s was inherited by the Babylonians, the Egyptians and the Greeks and is why we still measure hours in 60 minutes and the divisions of a circle by 360 degrees.

I didn’t know that after the French Revolution, when the National Convention introduced the decimal system of weights and measures, it also tried to decimalise time, introducing a new system whereby every day would be divided into ten hours, each of a hundred minutes, each divided into 100 seconds. Thus there were a very neat 10 x 100 x 100 = 100,000 seconds in a day. But it failed. An hour of 60 minutes turns out to be a deeply useful division of time, intuitively measurable, and a reasonable amount of time to spend on tasks. The reform was quietly dropped after six months, although revolutionary decimal clocks still exist.

Studies consistently show that Chinese children find it easier to count than European children. This may be because of our system of notation, or the structure of number names. Instead of eleven or twelve, Chinese, Japanese and Koreans say the equivalent of ten one, ten two. 21 and 22 become two ten one and two ten two. It has been shown that this makes it a lot simpler and more intuitive to do basic addition and subtraction.

Bellos goes on to describe the various systems of abacuses which have developed in different cultures, before explaining the phenomenal popularity of abacus counting, abacus clubs, and abacus championships in Japan which helps kids develop the ability to perform anzan, using the mental image of an abacus to help its practitioners to sums at phenomenal speed.

Chapter Two – Behold!

The mystical sense of the deep meaning of numbers, from Pythagoras with his vegetarian religious cult of numbers in 4th century BC Athens to Jerome Carter who advises leading rap stars about the numerological significance of their names.

Euclid and the elegant and pure way he deduced mathematical theorems from a handful of basic axioms.

A description of the basic Platonic shapes leads into the nature of tessalating tiles, and the Arab pioneering of abstract design. The complex designs of the Sierpinski carpet and the Menger sponge. And then the complex and sophisticated world of origami, which has its traditionalists, its pioneers and surprising applications to various fields of advanced science, introducing us to the American guru of modern origami, Robert Lang, and the Japanese rebel, Kazuo Haga, father of Haga’s Theorem.

Chapter Three – Something About Nothing

A bombardment of information about the counting systems of ancient Hindus, Buddhists, about number symbols in Sanskrit, Hebrew, Greek and Latin. How the concept of zero was slowly evolved in India and moved to the Muslim world with the result that the symbols we use nowadays are known as the Arabic numerals.

A digression into ‘a set of arithmetical tricks known as Vedic Mathematics ‘ devised by a young Indian swami at the start of the twentieth century, Bharati Krishna Tirthaji, based on a series of 16 aphorisms which he found in the ancient holy texts known as the Vedas.

Shankaracharya is a commonly used title of heads of monasteries called mathas in the Advaita Vedanta tradition. Tirthaji was the Shankaracharya of the monastery at Puri. Bellos goes to visit the current Shankaracharya who explains the closeness, in fact the identity, of mathematics and Hindu spirituality.

Chapter Four – Life of Pi

An entire chapter about pi which turns out not only to be a fundamental aspect of calculating radiuses and diameters and volumes of circles and cubes, but also to have a long history of mathematicians vying with each other to work out its value to as many decimal places as possible (we currently know the value of pi to 2.7 trillion decimal places) and the surprising history of people who have set records reciting the value if pi.

Thus, in 2006, retired Japanese engineer Akira Haraguchi set a world record for reciting the value of pi to the first 100,000 decimal places from memory! It took 16 hours with five minute beaks every two hours to eat rice balls and drink some water.

There are several types or classes of numbers:

  • natural numbers – 1, 2, 3, 4, 5, 6, 7…
  • integers – all the natural numbers, but including the negative ones as well – …-3, -2, -1, 0, 1, 2, 3…
  • fractions
  • which are also called rational numbers
  • numbers which cannot be written as fractions are called irrational numbers
  • transcendent numbers – ‘a transcendental number is an irrational number that cannot be described by an equation with a finite number of terms’

The qualities of the heptagonal 50p coin and the related qualities of the Reuleux triangle.

Chapter Five – The x-factor

The origin of algebra (in Arab mathematicians).

Bellos makes the big historical point that for the Greeks (Pythagoras, Plato, Euclid) maths was geometric. They thought of maths as being about shapes – circles, triangles, squares and so on. These shapes had hidden properties which maths revealed, thus giving – the Pythagoreans thought – insight into the secret deeper values of the world.

It is only with the introduction of algebra in the 17th century (Bellos attributes its widespread adoption to Descartes’s Method in the 1640s) that it is possible to fly free of shapes into whole new worlds of abstract numbers and formulae.

Logarithms turn the difficult operation of multiplication into the simpler operation of addition. If X x Y = Z, then log X + log Y = log Z. They were invented by a Scottish laird John Napier, and publicised in a huge book of logarithmic tables published in 1614. Englishman Henry Briggs established logarithms to base 10 in 1628. In 1620 Englishman Edmund Gunter marked logarithms on a ruler. Later in the 1620s Englishman William Oughtred placed two logarithmic rulers next to each other to create the slide rule.

Three hundred years of dominance by the slide rule was brought to a screeching halt by the launch of the first pocket calculator in 1972.

Quadratic equations are equations with an x and an x², e.g. 3x² + 2x – 4 = 0. ‘Quadratics have become so crucial to the understanding of the world, that it is no exaggeration to say that they underpin modern science’ (p.200).

Chapter Six – Playtime

Number games. The origin of Sudoku, which is Japanese for ‘the number must appear only once’. There are some 5 billion ways for numbers to be arranged in a table of nine cells so that the sum of any row or column is the same.

There have, apparently, only been four international puzzle crazes with a mathematical slant – the tangram, the Fifteen puzzle, Rubik’s cube and Sudoku – and Bellos describes the origin and nature and solutions to all four. More than 300 million cubes have seen sold since Ernö Rubik came up with the idea in 1974. Bellos gives us the latest records set in the hyper-competitive sport of speedcubing: the current record of restoring a copletely scrambled cube to order (i.e. all the faces of one colour) is 7.08 seconds, a record held by Erik Akkersdijk, a 19-year-old Dutch student.

A visit to the annual Gathering for Gardner, honouring Martin Gardner, one of the greatest popularisers of mathematical games and puzzles who Bellos visits. The origin of the ambigram, and the computer game Tetris.

Chapter Seven – Secrets of Succession

The joy of sequences. Prime numbers.

The fundamental theorem of arithmetic – In number theory, the fundamental theorem of arithmetic, also called the unique factorization theorem or the unique-prime-factorization theorem, states that every integer greater than 1 either is a prime number itself or can be represented as the product of prime numbers.

The Goldbach conjecture – one of the oldest and best-known unsolved problems in number theory and all of mathematics. It states that, Every even integer greater than 2 can be expressed as the sum of two primes. The conjecture has been shown to hold for all integers less than 4 × 1018, but remains unproven despite considerable effort.

Neil Sloane’s idea of persistence – The number of steps it takes to get to a single digit by multiplying all the digits of the preceding number to obtain a second number, then multiplying all the digits of that number to get a third number, and so on until you get down to a single digit. 88 has a persistence of three.

88 → 8 x 8 = 64 → 6 x 4 = 24 → 2 x 4 = 8

John Horton Conway’s idea of the powertrain – For any number abcd its powertrain goes to abcd, in the case of numbers with an odd number of digits the final one has no power, abcde’s powertrain is abcde.

The Recamán sequence Subtract if you can, unless a) it would result in a negative number or b) the number is already in the sequence. The result is:

0, 1, 3, 6, 2, 7, 13, 20, 12, 21, 11….

Gijswijt’s sequence a self-describing sequence where each term counts the maximum number of repeated blocks of numbers in the sequence immediately preceding that term.

1, 1, 2, 1, 1, 2, 2, 2, 3, 1, 1, 2, 1, 1, 2, 2, 2, 3, 2, 1, …

Perfect number A perfect number is any number that is equal to the sum of its factors. Thus 6 – its factors (the numbers which divided into it) are 1, 2 and 3. Which also add up to (are the sum of) 6. The next perfect number is 28 because its factors – 1, 2, 4, 7, 14 – add up to 28. And so on.

Amicable numbers A number is amicable if the sum of the factors of the first number equals the second number, and if the sum of the factors of the second number equals the first. The factors of 220 are 1, 2, 4, 5, 10, 11, 20, 22, 44, 55 and 110. Added together these make 284. The factors of 284 are 1, 2, 4, 71 and 142. Added together they make 220!

Sociable numbers In 1918 Paul Poulet invented the term sociable numbers. ‘The members of aliquot cycles of length greater than 2 are often called sociable numbers. The smallest two such cycles have length 5 and 28’

Mersenne’s prime A prime number which can be written in the form 2n – 1 a prime number that is one less than a power of two. That is, it is a prime number of the form Mn = 2n − 1 for some integer n. The exponents n which give Mersenne primes are 2, 3, 5, 7, 13, 17, 19, 31, … and the resulting Mersenne primes are 3, 7, 31, 127, 8191, 131071, 524287, 2147483647, …

These and every other sequence ever created by humankind are documented on The On-Line Encyclopedia of Integer Sequences (OEIS), also cited simply as Sloane’s. This is an online database of integer sequences, created and maintained by Neil Sloane while a researcher at AT&T Labs.

Chapter Eight – Gold Finger

The golden section a number found by dividing a line into two parts so that the longer part divided by the smaller part is also equal to the whole length divided by the longer part.

Phi The number is often symbolized using phi, after the 21st letter of the Greek alphabet. In an equation form:

a/b = (a+b)/a = 1.6180339887498948420 …

As with pi (the ratio of the circumference of a circle to its diameter), the digits go on and on, theoretically into infinity. Phi is usually rounded off to 1.618.

The Fibonnaci sequence Each number in the sequence is the sum of the two numbers that precede it. So the sequence goes: 0, 1, 1, 2, 3, 5, 8, 13, 21, 34, and so on. The mathematical equation describing it is Xn+2= Xn+1 + Xn.

as the basis of seeds in flowerheads, arrangement of leaves round a stem, design of nautilus shell and much more.

Chapter Nine – Chance Is A Fine Thing

A chapter about probability and gambling.

Impossibility has a value 0, certainty a value 1, everything else is in between. Probabilities can be expressed as fractions e.g. 1/6 chance of rolling a 6 on a die, or as percentages, 16.6%, or as decimals, 0.16…

The probability is something not happening is 1 minus the probability of that thing happening.

Probability was defined and given mathematical form in 17th century. One contribution was the questions the Chevalier de Méré asked the mathematical prodigy Blaise Pascal. Pascal corresponded with his friend, Pierre de Fermat, and they worked out the bases of probability theory.

Expected value is what you can expect to get out of a bet. Bellos takes us on a tour of the usual suspects – rolling dice, tossing coins, and roulette (invented in France).

Payback percentage if you bet £10 at craps, you can expect – over time – to receive an average of about £9.86 back. In other words craps has a payback percentage of 98.6 percent. European roulette has a payback percentage of 97.3 percent. American roulette, 94.7 percent. On other words, gambling is a fancy way of giving your money away. A miserly slot machine has a payback percentage of 85%. The National Lottery has a payback percentage of 50%.

The law of large numbers The more you play a game of chance, the more likely the results will approach the statistical probability. Toss a coin three times, you might get three heads. Toss a coin a thousand times, the chances are you will get very close the statistical probability of 50% heads.

The law of very large numbers With a large enough sample, outrageous coincidences become likely.

The gambler’s fallacy The mistaken belief that, if something happens more frequently than normal during a given period, it will happen less frequently in the future (or vice versa). In other words, that a random process becomes less random, and more predictable, the more it is repeated.

The birthday paradox The probability that, in a set of n randomly chosen people, some pair of them will have the same birthday. By the pigeonhole principle, the probability reaches 100% when the number of people reaches 367 (since there are only 366 possible birthdays, including February 29). However, 99.9% probability is reached with just 70 people, and 50% probability with 23 people. (These conclusions are based on the assumption that each day of the year (excluding February 29) is equally probable for a birthday.) In other words you only need a group of 23 people to have an evens chance that two of them share a birthday.

The drunkard’s walk

The difficulty of attaining true randomness and the human addiction to finding meaning in anything.

The distinction between playing strategy (best strategy to win a game) and betting strategy (best strategy to maximise your winnings), not always the same.

Chapter Ten – Situation Normal

Carl Friedrich Gauss, the bell curve, normal distribution aka Gaussian distribution. Normal or Gaurrian distribution results in a bell curve. Bellos describes the invention and refinement of the bell curve (he explains that ‘the long tail’ results from a mathematician who envisioned a thin bell curve as looking like two kangaroos facing each other with their long tails heading off in opposite directions). And why

Regression to the mean – if the outcome of an event is determined at least in part by random factors, then an extreme event will probably be followed by one that is less extreme. And recent devastating analyses which show how startlingly random sports achievements are, from leading baseball hitters to Simon Kuper and Stefan Szymanski’s analysis of the form of the England soccer team.

Chapter Eleven – The End of the Line

Two breakthroughs which paved the way for modern i.e. 20th century, maths: the invention of non-Euclidean geometry, specifically the concept of hyperbolic geometry. To picture this draw a triangle on a Pringle. it is recognisably a triangle but all its angles do not add up to 180°, therefore it defies, escapes, eludes all the rule of Euclidean geometry, which were designed for flat 2D surfaces.

Bellos introduces us to Daina Taimina, a maths prof at Cornell University, who invented a way of crocheting hyperbolic surfaces. The result looks curly, like curly kale or the surface of coral.

Anyway, the breakaway from flat 2-D Euclidean space led to theories about curved geometry, either convex like a sphere, or hyperbolic like the pringle. It was this notion of curved space, which paved the way for Einstein’s breakthrough ideas in the early 20th century.

The second big breakthrough was Georg Cantor’s discovery that you can have many different types of infinity. Until Cantor the mathematical tradition from the ancient Greeks to Galileo and Newton had fought shy of infinity which threatened to disrupt so many formulae.

Cantor’s breakthrough was to stop thinking about numbers, and instead think of sets. This is demonstrated through the paradoxes of Hilbert’s Hotel. You need to buckle your safety belt to understand it.

Thoughts

This is easily the best book about maths I’ve ever read. It gives you a panoramic history of the subject which starts with innumerate cavemen and takes us to the edge of Einstein’s great discoveries. But Bellos adds to it all kinds of levels and abilities.

He is engaging and candid and funny. He is fantastically authoritative, taking us gently into forests of daunting mathematical theory without placing a foot wrong. He’s a great explainer. He knows a good story when he sees one, and how to tell it engagingly. And in every chapter there is a ‘human angle’ as he describes his own personal meetings and interviews with many of the (living) key players in the world of contemporary maths, games and puzzles.

Like the Ian Stewart book but on a vastly bigger scale, Bellos makes you feel what it is like to be a mathematician, not just interested in nature’s patterns (the basis of Stewart’s book, Nature’s Numbers) but in the beauty of mathematical theories and discoveries for their own sakes. (This comes over very strongly in chapter seven with its description of some of the weirdest and wackiest number sequences dreamed up by the human mind.) I’ve often read scientists describing the beauty of mathematical theories, but Bellos’s book really helps you develop a feel for this kind of beauty.

For me, I think three broad conclusions emerged:

1. Most mathematicians are in it for the fun. Setting yourself, and solving, mathematical puzzles is obviously extremely rewarding. Maths includes the vast territory of puzzles and games, such as the Sudoku and so on he describes in chapter six. Obviously it has all sorts of real-world application in physics, engineering and so on, but Bellos’s book really brings over that a true understanding of maths begins in puzzles, games and patterns, and often remains there for a lifetime. Like everything else maths is no highly professionalised the property of tenured professors in universities; and yet even to this day – as throughout its history – contributions can be made by enthusiastic amateurs.

2. As he points out repeatedly, many insights which started out as the hobby horses of obsessives, or arcane breakthroughs on the borders of our understanding, and which have been airily dismissed by the professionals, often end up being useful, having applications no-one dreamed of. Either they help unravel aspects of the physical universe undreamed of when they were discovered, or have been useful to human artificers. Thus the development of random number sequences seemed utterly pointless in the 19th century, but now underlies much internet security.

On a profounder note, Bellos expresses the eerie, mystical sense many mathematicians have that it seems so strange, so pregnant with meaning, that so many of these arcane numbers end up explaining aspects of the world their inventors knew nothing of. Ian Stewart has an admirably pragmatic explanation for this: he speculates that nature uses everything it can find in order to build efficient life forms. Or, to be less teleological, over the past 3 and a half billion years, every combination of useful patterns has been tried out. Given this length of time, and the incalculable variety of life forms which have evolved on this planet, it would be strange if every number system conceivable by one of those life forms – humankind – had not been tried out at one time or another.

3. My third conclusion is that, despite John Allen Paulos’s and Bellos’s insistence, I do not live in a world ever-more bombarded by maths. I don’t gamble on anything, and I don’t follow sports – the two biggest popular areas where maths is important – and the third is the twin areas of surveys and opinion polls (55% of Americans believe in alien abductions etc etc) and the daily blizzard of reports (for example, I see in today’s paper that the ‘Number of primary school children at referral units soars’).

I register their existence but they don’t impact on me for the simple reason that I don’t believe any of them. In 1992 every opinion poll said John Major would lose the general election, but he won with a thumping majority. Since then I haven’t believed any poll about anything. For example almost all the opinion polls predicted a win for Remain in the Brexit vote. Why does any sane person believe opinion polls?

And ‘new and shocking’ reports come out at the rate of a dozen a day and, on closer examination, lots of them turn out to be recycled information, or much much more mundane releases of data sets from which journalists are paid to draw the most shocking and extreme conclusions. Some may be of fleeting interest but once you really grasp that the people reporting them to you are paid to exaggerate and horrify, you soon learn to ignore them.

If you reject or ignore these areas – sport, gambling and the news (made up of rehashed opinion polls, surveys and reports) – then unless you’re in a profession which actively requires the sophisticated manipulation of figures, I’d speculate that most of the rest of us barely come into contact with numbers from one day to the next.

I think that’s the answer to Paulos and Bellos when they are in their ‘why aren’t more people mathematically numerate?’ mode. It’s because maths is difficult, and counter-intuitive, and hard to understand and follow, it is a lot of work, it does make your head ache. Even trying to solve a simple binomial equation hurt my brain.

But I think the biggest reason that ‘we’ are so innumerate is simply that – beautiful, elegant, satisfying and thought-provoking though maths may be to the professionals – maths is more or less irrelevant to most of our day to day lives, most of the time.


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